Lessons from 250 Blog Posts

This week marks a momentous milestone (for me, at least): this is the 250th post that I’ve written on chrisneumann.com.

I never thought I’d actually write for this long, so I thought I would take some time this week to reflect on it. How has my content evolved over the past four and a half years? Does it still resonate with readers? And where should I go next? (If you’re currently reading this on the website, you may have noticed a new look — I’ll dive into the rationale for that shortly.)

Here are some of the lessons I learned after 250 blog posts.

The Backstory

When I moved to Canada in late-2020 to join Panache Ventures, I noticed that there was a lack of entrepreneurial content available for founders there. I had spent the better part of the 5 years prior teaching founders around the world strategies and best practices used by leading Silicon Valley startups (first at 500 Startups and, later, through Commonwealth Ventures). So I thought I’d write about some of them.

But there was one problem.

Over the years, I had written a handful of blog posts, but I could never figure out how to publish content on a consistent schedule. I knew it was possible to write with a weekly cadence (after all, I wrote weekly investor updates for nearly five years at DataHero), but I had never done so with creative or longer-form content.

I mentioned this dilemma in passing to one of my mentors, Marvin Liao, who told me about a course he had recently taken called Write of Passage. The program was the brainchild of an exceptional young writer named David Perell. Despite its name, Write of Passage wasn’t actually a course about writing. At least, not in the strictest sense. Rather, it was a bootcamp designed to teach you how to build systems and processes to support writing and publishing new content on a regular basis (like weekly blog posts). It was exactly what I needed.

It turned out, I wasn’t the only one. The participants in my cohort included many residents of Startupland™, like founders and VCs. But there were also professional athletes, academics and a wide variety of other writers and aspiring writers.

How It Started

Write of Passage was one of those programs that unapologetically threw you in the deep end from the start. The very first session kicked off with a firm dictum from David: in order to stay in the program, you had to publish your first post within one week.

The prompt: “What is the definitive answer to the question that people ask you most often?”

At the time, it had been about six months since news of my joining Panache and moving to Vancouver was announced. In subsequent calls and coffee chats I was repeatedly being asked the same question:

“Why did you come back to Canada?”

On April 13th, 2022, I published the answer to that question and launched this website.

How It’s Going

It’s now been 229 weeks since that first post (for those of you wondering how I reached 250 posts in only 229 weeks, there were several periods of time when I published multiple posts each week — such as during my brief side quest into food blogging.) Over the past 4 ½ years, readership of both my website and the corresponding newsletter have steadily grown (thank you all for that 🙏).

I have no idea what happened in early 2024…

But it hasn’t all been “up-and-to-the-right.”

While website traffic and newsletter subscribers have steadily grown, open rates for the newsletter have slightly declined over the years.

The open rate for my newsletter has held steady around 60% for the past two years (a rate that is generally considered pretty solid, though with AI preview and summary tools becoming so prevalent, it’s increasingly hard to tell). That said, I still wanted to dig into the performance data for both the website and the newsletter.

First, a few thoughts on open rates:

1. Year 1 open rates aren’t meaningful in any way. The early subscriber numbers were so low (and so heavily skewed to people who already knew me personally), that they were unnaturally high.

2. A better metric for overall relevance is unsubscribe rate. With agents making it easier-than-ever to ditch newsletters we don’t read anymore, are people still keeping me in their inbox? It turns out the answer is yes (the 90-day rolling unsubscribe rate for my newsletter is ~0.1%, which is considered very strong — thank you again 🙏)

That said, despite a steady open rate and strong retention, there has unequivocally been more inconsistency in content performance over the past few years. So I started to look at what I’ve been posting and how that’s changed:

1. The content I posted in Years 1 and 2 was overwhelmingly instructional/educational in nature (fundraising best practices, posts about how venture capital worked, etc.). In fact, more than 70% of the first 120 posts I wrote either taught the reader how to do something or explained how something worked.

2. In year 3, I started writing more posts about startup trends, observations about different ecosystems and topics related to mental and physical health. Last year (2025), only 37% of the posts I wrote were instructional/educational in nature.

3. The last 2 years have also seen an (understandable) uptick in posts related to AI.

4. Many of the posts I wrote in years 1 - 3 had an overtly Canadian slant to them. That was very much a by-product of my role as a GP at a Canadian-focused Pre-Seed fund. Since leaving Panache at the end of 2024 to focus on [Redacted], most of the posts that I’ve published were written independent of geography (though I’ve still made a point of writing about trends in the Canadian ecosystem as part of my quarterly 5 Things I Think I Think posts).

What Comes Next

The biggest epiphany going through 250 posts’ worth of data was the degree to which the type of content I’ve published has evolved over the years. The first few years were overwhelmingly educational/instructional in nature because I had a massive backlog of topics that I wanted to write about. Now that I’ve written about most of those, my posts are more focused on trends and observations.

But I’m not done yet.

For starters, it became abundantly clear as I went through Google Analytics data and spoke with founders that a significant portion of my older content had become difficult to find or access. That’s where this redesign comes in. In addition to a cleaner, more streamlined design, there’s a new Topics page that more effectively organizes all of my posts (driven by a complete refactoring of post tags).

I’m also working on a further refactoring related to AEO/SEO/GEO. But I’ll save details of that for a future post.

In the meantime, as I look ahead to (hopefully) another 250 posts on chrisneumann.com, expect more insights, more data and more in-depth posts to help founders, investors and ecosystem supporters around the world make sense of Silicon Valley and beyond.

Thanks for reading 🙏.

Before You Start Fundraising, You Need to Get Acclimated

Last week, I met with 4 different startups based outside of California: one from New York, another in London, a third in Vancouver and the fourth from Toronto. All of these startups are preparing to fundraise in the fall (either for their Seed or Series A round). At some point in each of those conversations, I found myself giving the founders a piece of advice that I hadn’t previously offered with any regularity:

“You should go to San Francisco a few weeks before you start to fundraise. You need to get acclimated.”

It wasn’t all that long ago that the majority of fundraising — even at later stages — was being done mostly online. For founders based outside of the U.S., raising from Silicon Valley VCs took a bit of extra prep work, but for the most part it didn’t matter if you were based in Brisbane, California or Brisbane, Australia. As recently as Q1, most Seed and Series A fundraising processes still began with virtual intro calls.

But over the past few quarters, things have shifted dramatically. Silicon Valley has been speeding up. A lot.

The first half of the year saw valuations for the top 5% of Seed rounds hit unprecedented highs, driven primarily by a surge in preemptive fundraising rounds. At the same time, the culture in Silicon Valley has been evolving to reflect its shift in velocity and intensity, manifesting in ways both big and small.

I hadn’t internalized just how prevalent these changes have been until I was on those calls last week. As I spoke with each of the founders, I found myself subconsciously (and not-so-subconsciously) noticing a variety of tells that made clear that they were not based in the Bay Area. An observation that my mind immediately translated to, “they’re not going fast enough.”

Considering that 2 of the 4 founding teams had previously spent considerable time in Silicon Valley, I was shocked at just how apparent it was to me that they were no longer locals. Some of it was language — there are a lot of new phrases that have entered the San Francisco lexicon as of late (the tongue-in-cheek website SF-isms catalogues some of them). But mostly it was their sense of urgency.

Or lack thereof.

I want to be clear that I’m not suggesting that any of these four startups aren’t operating at a high velocity — they all are — but Silicon Valley founders have upped their intensity and velocity to such a degree that everyone else seems slow by comparison. And in fundraising, just as in life, perception is reality.

Velocity has always been the metric that matters most when it comes to early-stage startups. And in today’s AI-driven landscape, Silicon Valley VCs are paying more attention than ever to how fast startups are going. Fundraising calls are happening in hours instead of days. Meetings are scheduled over text messages instead of through Calendly links. Everything in the ecosystem is happening faster.

Which brings us back to my fundraising advice.

It used to be relatively easy to prepare out-of-town founders for Silicon Valley fundraising by pointing them to a few key phrases, a list of what was “hot or not” in San Francisco at the time and a rubric of what Bay Area VCs would focus on for their stage. But it’s not so simple anymore. Right now many Seed and Series A VCs are struggling to adapt to the changing landscape, so there is no single list of what these investors are looking for to point at. Moreover, Silicon Valley itself is still accelerating.

Which makes it challenging to enumerate exactly what out-of-town founders should do in order to best prepare to pitch Silicon Valley VCs at this particular moment in time.

So I will instead share the advice I gave to each of the four founders I spoke to last week:

1. As you prepare your pitch for Silicon Valley VCs, reduce your level of confidence in feedback from hometown founders and investors (unless they have spent considerable time in the Bay Area recently and/or successfully fundraised from Silicon Valley VCs this year). In all likelihood, their advice is outdated.

2. Counterbalance this by proactively seeking feedback from founders, investors and others with strong current ties to Silicon Valley.

3. If at all possible, spend 2 - 3 weeks in San Francisco immediately prior to kicking off your fundraise. Doing so will:

   • Give you enough time to adjust and acclimate to the “new” pace and culture of Silicon Valley

   • Allow you to tap into the serendipity of Silicon Valley by attending events and meeting other founders

     Provide an opportunity for you to solicit feedback on your pitch and fundraising strategy from Silicon Valley-based founders and investors

4. Expect to do most of your fundraising in person this time around

For founders outside of California who are trying to raise a Seed or Series A round from Silicon Valley VCs this year, I think this is likely to be the best approach given (a) the currently evolving nature of Silicon Valley, and (b) the widening gap in velocity/intensity/urgency between Silicon Valley and the rest of the world.

Note: the above advice is specifically geared towards founders trying to raise Seed or Series A rounds from Silicon Valley VCs. While Pre-Seed founders can certainly benefit from spending time in Silicon Valley, the vast majority of Pre-Seed rounds globally continue to be raised from local investors, so it may not impact your success rate when it comes to fundraising.

Building in Public: Founders Day Edition

Last week, I hosted the third annual Founders Day in Vancouver, BC.

Like the origin stories from many a startup, Founders Day was something of an accidental creation. It was originally born out of casual conversations and was intended to be a one-off event (before Web Summit moved to Vancouver the following year). Put simply, it was an experiment.

But as Eric Ries once famously wrote, “an experiment is more than just a theoretical inquiry; it is also a first product.”

Not only did the local ecosystem embrace the experiment that was Founders Day, by year two it had become abundantly clear that we had tapped in to a deep unmet need amongst founders in Western Canada.

Coming into year three, it was time to start evolving Founders Day into something sustainable.

The Evolution of an Event

The first two Founders Days were prototypes in the truest sense. They were giant meetups built atop a base of duct tape, paperclips and a lot of behind-the-scenes scrambling (if you arrived early enough last year to see Google, Fasken and RBCx employees madly stuffing badges into plastic name tag holders, you know what I’m talking about). The events looked fancy by virtue of being held at the Vancouver Convention Centre, but they were very much delivered in the model of Paul Graham’s famous essay, Do Things that Don’t Scale.

Nice place for a tech meetup, eh?

By the time we kicked off the planning cycle for Founders Day 2026 towards the end of last year, I had zeroed in on three distinct areas in which I wanted to evolve Founders Day:

1. The Venue

For as stunning as the Vancouver Convention Centre is, it’s very much designed for large-scale conferences and poses challenges for hosts of smaller events. For example, the first two Founders Days had no on-site lunch offerings and we had to host the networking portion of the day at a separate venue 15 minutes away (both of which led to a lot of attrition throughout the day).

This year, I wanted to find a venue where we could deliver a more holistic, continuous experience to attendees. I also wanted to see if we could take better advantage of Vancouver’s exceptional August weather.

Look how sunny it is outside…

2. Delivery

Like any good early-stage startup, the first two Founders Days were a success in large part because of the shared willingness of everyone involved to roll up their sleeves and “get it done”. Sponsors showed up at 6:00 am to stuff badges into plastic name tags. Lawyers and bankers scanned attendees at registration and handed out lanyards. Speakers ran around trying to find their fellow panelists and ensure that everyone got on stage at the right time.

That’s fun and exhilarating once or twice, but it’s not sustainable. Especially not when the novelty wears off and the hiccups become more glaring to attendees.

Coming into this year, a big focus was on progressing from the inconsistency and unpredictability of a large, volunteer-driven meetup towards something more intentional and well-executed.

Look! An actual sign with an arrow →

3. Finances

Of course, added infrastructure comes with added costs. To-date, Founders Day has been entirely subsidized by corporate and government sponsors and myself. In order for Founders Day to cement itself as a permanent event in the annual Startupland™ calendar, it needs to be built atop a foundation that is long-term sustainable.

That means, like any startup, we needed to start the long march towards break-even.

The Journey towards Product-Market Fit

Continuing along with the startup analogy, year three of Founders Day came with many of the same questions that all early-stage startups face as they progress towards product-market fit:

• Will free MVP users pay for it?

• Can you maintain what makes the core offering special while adding new features and making it more robust?

• How do you navigate conflicting user feedback and decide on a roadmap and priorities?

• How will you evaluate the success of the new version?

We made a number of changes this year to both the event and the organization/infrastructure behind-the-scenes. In other words, we rebuilt the MVP from the ground up, added a bunch of new features and released version 3.0 to the world.

If I were to write technical release notes for this year’s Founders Day, they would look something like this:

Release Notes - Founders Day 3.0

• New branding and design language

• Completely redesigned UI/UX (new venue)

• Improved user onboarding (actual conference badges, expanded registration area with redesigned staffing, improved signage)

• Redefined user roles

  • Blue = Founders, students

  • Orange = Speakers, mentors, ecosystem champions

  • Brown = Sponsors, investors

  • White = Staff, volunteers

• Enhanced in-app user support (on-site F&B)

• Improved and expanded partner integrations (more sponsors and community partners, many of whom exhibited at Founders Day)

• Platform and stability upgrades

• Misc. bug fixes

Enhanced user support 🍻

What does all of that look like, practically speaking? Here are some of the bigger changes we made for Founders Day 2026:

• By far, the biggest change to Founders Day was the move from the Vancouver Convention Centre to a new outdoor venue. That was a huge undertaking, as it meant moving from a “turn key” venue to one where we had to bring everything in ourselves (from the stage, A/V setup and seating to fencing, garbage, and even porta potties).

• The shift from “turn key” venue to custom experience wasn’t limited to the stage show. For the first two years of Founders Day, the networking event took place at a bar about 15 minutes from the convention centre. For year three, I wanted everything to be in one place. We brought in food trucks, concession stands, coffee bars, local beer and wine vendors and even an ice cream truck (the latter courtesy of local startup IcePanel). That kind of effort required procurement, power and permits. Lots and lots of permits…🤦‍♂️

• Completely rethinking the venue for Founders Day meant a massive expansion to the team. The first two events relied heavily on convention centre staff for much of the behind-the-scenes logistics. For year three, we had to assemble a full-blown event and production team from scratch. That included event planners, a stage team, A/V staff, videographers and photographers, on-site security and more. Plus a whole lot of volunteers (shout out to Chris Hobbs for recruiting, training and supervising all of the amazing Founders Day volunteers 🙏).

• Another seemingly simple but significant effort was on the design side. Founders Day 1.0 had a Luma page and a LinkedIn post. Version 2.0 had a Luma page, a LinkedIn post and a SquareSpace website. Founders Day 3.0 had my long-time collaborator Gail Yui. In the months leading up to this year’s Founders Day, Gail performed a top-to-bottom branding exercise that touched every aspect of the event, from signage and attendee badges to exhibiter booths and volunteer t-shirts to beer cans and bucket hats (plus, of course, the LinkedIn page).

For all of the changes we made to this year’s event, we tried hard to stay true to the original vision of Founders Day: to facilitate and encourage connections between founders. In his seminal book, Startup Communities, Brad Feld observed that,

“Building a startup community is not a zero-sum game in which there are winners and losers: if everyone engages, they and the entire community can all be winners.”

This year’s Founders Day had nearly 100 experienced founders and investors speaking to and mentoring up-and-coming founders — many of whom flew in just for this event.

These speakers flew in from San Francisco, LA, Toronto and Seattle ✈️

The Results?

So what did attendees think of Founders Day 2026?

🫠

The thing about building in public is that if you’re doing something that matters to people, then they are going to have opinions.

Strong opinions.

And that’s okay. In fact, it’s great!

Genuine customer feedback is a signal that people care about what you’re building. They may not agree with everything you’re doing. They may not like all of the decisions you make. They might get really loud and upset when things break. But that means they care about your product and the problem you’re solving.

And it’s infinitely better than silence. (It’s also why the field of product management exists.)

If the volume of attendee feedback alone is any indication, then Founders Day is trending in the right direction:

• Founders Day 2024: 7 people provided feedback

• Founders Day 2025: 37 people provided feedback

• Founders Day 2026: 102 people provided feedback (so far…)

Of course, that’s not the only metric that matters. So here is my honest review of Founders Day 2026:

Founders Day 2026: The Good, The Bad and the Ugly

Let’s start with the good:

• From a product-market fit perspective, the biggest win of Founders Day 2026 was that we had almost as many founders, investors and ecosystem supporters buy paid tickets as attended for free in 2025. (We didn’t have as many registrations as last year, but that was to be expected given how many people register for free events without giving much thought to whether or not they actually plan to attend.)

• At a more granular level, attendance figures for many ticket categories, including prospective founders/students, investors and ecosystem supporters, were up significantly compared to last year.

• Other than running out of cold brew coffee towards the end of the day, the logistics for the food trucks, bars and concessions all went off without a hitch.

• The registration process — which was a disaster in years past — was smooth and seamless.

• Attendee feedback on the founder mentoring and networking portions of Founders Day 2026 was through the roof. 📈

• We ever-so-slightly beat our revenue objective for this year’s event (revenue = sponsorship dollars + ticket sales).

• Finally, we got strong subjective feedback from the majority of attendees at this years event, including a 4.3/5.0 event rating on Luma and broadly positive feedback both publicly on social media and privately through attendee surveys.

Next, the bad:

• Overall attendance was slightly down compared to last year. We already know some of the reasons for this (e.g. marketing for this year’s event started later than planned due to delays in securing the venue). In the coming weeks, we will dig deeper into attendance statistics and feedback to see what other lessons are to be had.

• Some of the decisions we made around the venue layout and configuration led to challenges with the A/V setup (e.g. in some areas of the venue the sound was too loud while in others it was inaudible).

• Although we met our revenue target for this year’s event, expenses significantly exceeded our original estimates (primarily due to delays and unforeseen challenges with the new venue). Founders Day 2026 was never projected to break even, but the overruns definitely led to a larger deficit than planned.

Finally, the ugly:

• This biggest miss of this year’s event came from the main stage seating layout. Our team spent significant time and effort developing contingency plans for rain, but we didn’t anticipate that last Thursday would be one of the hottest days of the year in Vancouver. The result? For significant portions of the day, it was entirely too hot and sunny for most people to watch the main stage presentations from the audience seating.

• The change in audience flow resulting from the heat led to a number of additional challenges, most notably on the audio side. The speakers that lined the outside of the seating area weren’t configured to overcome the ambient noise from 400+ people mingling in close quarters. That meant many of the attendees standing in the shade were unable to clearly hear the panelists for significant portions of the day (though, rest assured, all of the sessions were recorded and we’ll post the videos soon!).

What’s Next for Founders Day?

Despite the hiccups that happened with this year’s event, Founders Day 2026 was an unquestionable success.

It delivered on the core value proposition we originally set forth while making considerable improvements over the “MVP” of years one and two. We also made meaningful progress on each of the three high-level objectives defined at the beginning of our planning cycle, which is a big deal when it comes to evolving into something that is long-term sustainable.

Of course, there is still plenty of work to be done on the journey towards product-market fit. Founders Day 3.0 had its fair share of “bugs” and there remains a healthy backlog of feature requests. In the coming weeks, we’ll dig deep into all of the feedback we received from speakers, mentors, sponsors and attendees and unpack the many lessons and learning’s from Founders Day 2026.

After that, it’s time to get to work on Founders Day 2027!

We’ve already got a tentative date soft-circled and clear ideas for how to make next year’s event even better, so stay tuned.

In the meantime, I want to thank all of the vendors, volunteers, speakers, sponsors, mentors and founders who made Founders Day 2026 happen. This year’s event wouldn’t have been possible without each and everyone one of you.

Thank you to our many corporate and government partners, including:

• Presenting Partner: Fasken Emerging Tech

• Gold Partner: Innovate BC

• Silver Partners: AWS, Conference Badge, DuploCloud, IcePanel, Launch, New Ventures BC, Osler, Remitly and Web Summit Vancouver

And thank you to the many incredible people who contributed to Founders Day 2026 in ways big and small, including: Alex Conconi, Alex Norman, Alexandra Greenhill, Ali Pejman, Allen Pike, Amin Yazdani, Andrew Fursman, Andrew Harries, Andrew Vilcsak, Anthonia Ogundele, Arif Khimani, Ath Caramanolis, Bijan Sanii, Bill Tam, Brandon Waselnuk, Chris Albinson, Chris Hobbs, Colin Harris, Conrad Whelan, Daniel Eberhard, Darrell Kopke, David Luba, Dennis Pilarinos, Derrick Emsley, Diraj Goel, Edoardo de Martin, Edward Chiang, Gary Agnew, Glen Lougheed, Handol Kim, Ian MacKinnon, Irene Dorsman, Jack Newton, Jacob Shadbolt, Joel Hansen, Josh Nilson, Karm Sumal, Landseer Enga, Mayor Ken Sim, Kenndal McArdle, Kim Kaplan, Kris Hartvigsen, Michael Buhr, Michael Henson, Nejeed Kassam, Noah Stanford, Olivier Vincent, Praveen Varshney, Ray Walia, Reza Sanaie, Reza Arbabian, Serge Salager, Shivam Kishore, Sophia Millar, Susan Su, Tanis Jorge, Tifanee Po, TJ Rak, TX Zhuo, Vik Kambli, Villi Iltchev, William Johnson, Wilson Tang and Yen Lee (sorry if I missed anyone!!).

See you all at Founders Day 2027.

Stop with the AI Slop, Part 2

Tomasz Tunguz recently wrote about his experiences incorporating AI as part of his writing process. He observed that,

“The problem with AI as a ghost writer: everyone uses the same ghost writer. AI’s voice isn’t the author’s.”

Since ChatGPT first came onto the scene, I’ve made a point of periodically testing new models to see if they could accurately reproduce my voice in writing. Years of blog content and social media posts has provided me with a solid set of training data. It turns out that even the earliest models were remarkably good at analyzing my writing style. They could pull out phrases that I constantly use, my preferred filler words, linguistic fingerprints and so on.

But for all of their promise, I’ve never managed to get an AI model to write even a single paragraph that isn’t clearly and obviously someone else’s voice. But does that actually matter these days?

Much like Tomasz, I periodically get emails from readers asking about the authenticity of my content (or, in some cases, expressing their appreciation for something I wrote that was clearly not AI-generated). In his post, Tomasz hypothesized that,

“In the age of slop, readers test authenticity.”

I think he’s right on that. Increasingly, I find myself reading posts, articles, emails and even text messages with the not-so-subconscious question, “was this written by AI?” going through my head.

Nobody who received this email questioned if it was from a human… 😂

A few months ago, I sent out emails to a number of people in my network asking if they would volunteer as mentors for this year’s Founders Day. It was a pretty simple email that included high-level details about the event plus the ask (“Will you mentor this year?”). Most of the responses were a few words or less (“I’m in!” or “Sorry, I’m out of town that week.”), but one of them stuck out:

“Hi Chris,

Great to hear from you, and count me in. I'd be glad to mentor again this year.

The new format sounds excellent. Moving everything to South Flats and giving it a festival feel is a smart change, and having the conference, mentoring, and networking party all in one place will make the day flow much better.

The mentor ask works for me. Happy to wear the lei and spend time in the mentor area during the day, so just send the signup sheet once logistics firm up and I'll pick a slot. The mentor and speaker dinner sounds great too, so keep me posted on the date.

I'll keep the details to myself until the announcement goes out. Looking forward to August 20.

Thanks,

XXX”

I immediately texted the sender,

His response?

Since AI came on the scene, a subset of the residents of Startupland™ have become obsessed with efficiency. A number of people I know have spent a mind-boggling amount of time spinning up agents to handle every task imaginable.

And in more than a few cases, that includes an agent to act as the frontline interface for all of their personal communications.

A few months ago, I wrote about the rise of AI slop on social media and how relying on AI to generate posts is now likely to result content that under-performs. I noted that after reading dozens of nearly-identical AI-authored comments, “…my eyes glazed over. Eventually, I stopped reading and responding.”

What happens when the AI slop isn’t confined to LinkedIn and X posts and finds its way into the emails and text messages you send to your coworkers, clients and even your friends?

Lately, I’ve started to receive emails from personal friends and long-time colleagues that were clearly written by AI. Most aren’t quite as egregious as the example above, but most of the time it’s pretty obvious. When I receive such emails, I find myself both less likely to read to the end and less likely to respond to it.

More and more, I find myself less likely to want to email that person at all.

There’s a certain degree of trust that exists in one-to-one communication. For the most part, I assume that if I send you an email, you (meaning, the real you) will read it — or at least scan the header before deciding whether or not to answer it. Similarly, when I receive an email from you, I assume that you (the real you) is the person who wrote the email.

Sure, some people have EAs who read and respond to emails for them. But long-established etiquette is that if a human EA writes an email on someone else’s behalf, they initial it in order to make clear that the email was written by someone else. Rarely do EAs actually ghost-write personal communications (though in Startupland™ that behavior is more common than in the rest of the world).

And while plenty of people use tools like Grammarly to improve their writing and leverage email templates / snippets to be more efficient, you can generally tell that the core was still written by the original author. The voice is still theirs.

So where do we go from here?

On the one hand, part of me wonders if we’re experiencing a similar dynamic to what happened when Calendly first came on the scene (when many people were upset by the “audacity” that someone would dare send them a link to fit into their calendar, rather than engaging in the time-consuming back-and-forth of scheduling). From that perspective, it seems reasonable and broadly net positive to have AI handle communication tasks that don’t really need a human-in-the-loop.

But having AI handle basic scheduling tasks or dealing with customer support is very different from having an agent pretend to be you in conversations with people you know personally. And perhaps that’s the core issue here. There’s a breach of etiquette and trust that seems to be happening with a subset of early adopters of AI. And they’re not fooling anyone.

I’m very transparent about the fact that I use an AI scheduling assistant, But I’ve never, ever had it pretend to be me. And I think that’s important.

At the end of his post, Tomasz noted,

“AI is a poor ghost writer, but a great editor.”

I suspect that in the very near future, we’ll see a similar backlash to AI slop in personal emails to what we’ve seen in social media and cold emails. Use AI as an editor. Offload tasks in a transparent manner to agents. But stop having AI pretend to be you. The incremental gain in productivity is likely costing you more than you realize.

That particular friend I referenced earlier who I emailed about Founders Day? I haven’t sent him a single email since.

Because I know he’s not the one reading it.

What Do VCs Talk About When Nobody’s Listening?

Last week, I hosted an emerging manager summit in San Francisco with more than two dozen early-stage VCs from across North America. GPs from Austin, Toronto, Seattle, Vancouver, Montreal, Missouri, Los Angeles, Halifax and more joined San Francisco and Silicon Valley colleagues for a day of sessions on the changing startup and VC landscapes.

So what exactly do VCs talk about when no one is listening?

Here are 5 topics that were top-of-mind for the VCs at our emerging manager summit:

1. Liquidity

Everyone at the summit was accutely aware of the upcoming end to the SpaceX investor lockup period. The debate amongst the group was how much of an impact would that newfound liquidity have on LPs? Would emerging managers start to see more appetite to invest from family offices and institutional investors who had been waiting on DPI, or would it take another major IPO from the likes of Anthropic or OpenAI for things to shift?

2. Valuations

Like most residents of Startupland™, our group of VCs was eager to discuss the trend of skyrocketing Seed valuations and its potential impacts. With YC’s most recent crop of companies reportedly commanding valuations north of $40M and the most recent Carta data showing the top 5% of Seed valuations surpassing $200M, there was plenty to talk about.

3. Ownership Targets

I’ve previously written about why VCs care a lot about ownership when investing in startups. Skyrocketing valuations are challenging a number of long-held assumptions when it comes to VC fund models.

Most emerging Pre-Seed and Seed funds target 3 - 5% ownership. But rising valuations have made those ownership targets increasingly out of reach — especially for hot companies. Should smaller funds forgo ownership targets and strive to be in the best deals no matter the price? Should they remain disciplined in their approach to investing (even if that means passing on hot companies)? Or perhaps a combination of the two?

Towards the end of the day, our group of GPs was joined by the cofounder of one of Silicon Valley’s largest megafunds, who pulled back the curtain on how multi-billion dollar funds think about price and ownership. That led to an incredible back-and-forth amongst our GPs on the future of early-stage investing and the opportunities for smaller funds.

4. The Changing Age of Founders

Another hot topic at our emerging manager summit was the changing demographics of founders — specifically, age.

For more than a decade, many VCs have held a noticeable bias towards founders in their 30s, as reports repeatedly showed the average age of “successful founders” hovering around the mid- to late-30s. But the rise of AI has turned that on its head. Over the past few years, the average age of VC-backed founders has plummeted. Today, many investors are once again exhibiting a strong preference towards younger founding teams, betting that their AI-native sensibilities will trump any lack of experience.

Several of the GPs in attendance — including our guest megafund manager — shared recent data from their portfolios to quantify the trend. That led to a robust discussion that included the rise of residencies and hacker houses, the pros and cons of degen behavior, and how to evaluate founder velocity vs. experience.

5. The Opportunities in AI

Of course, we couldn’t possibly have had a gathering of tech investors without spending a considerable amount of time talking about tech. More than half of the participating VCs came from technical backgrounds. Not only does that fact have a significant impact on their propensity to invest in napkins, but it enabled us to have deep, thoughtful conversations on the state of AI and its potential future trajectories.

Open vs. closed weights, on-prem vs. cloud, the merits of forward-deployed engineers and thoughts on what will happen when the true cost of AI compute gets passed on to end customers were just a few of the topics we touched on during our technical sessions.

Should I Fundraise in the Summer?

It’s that time of year again.

We just hit the mid-point of Silicon Valley’s summer break and, right on cue, a plethora of VCs started proclaiming that they’re not actually on summer vacation.

I’ve previously written about why summer is a bad time for founders to fundraise. If you haven’t read that post before, I suggest you start by giving it a quick skim. Here’s the tl;dr:

The vast majority of VCs do, in fact, work through the summer. But like everyone else, they do so at a reduced pace. They take summer vacations, spend more time with their kids, run around in the desert dressed up like fuzzy cyberpunk muppets. You know…normal summer stuff.

So it’s not that you can’t raise a round of funding in the summer. But it is logistically harder:

• It takes longer to schedule initial meetings with a VC

• The time between meetings increases

• The amount of time needed for a VC to complete their diligence takes longer (as analysts and others at the firm also take vacations)

The result is that running a fundraising process in the summer takes longer than at other times of the year. Not only that, if you are able to successfully raise a round, you will very likely end up with a lower valuation due to the lack of competition.

But rather than revisit why summer is a bad time to fundraising from a founder’s perspective (seriously, read this post if you haven’t already), I thought I would share a bit of insight into why, each and every year, so many VCs try to push back against that narrative.

Let’s start with the basics: the goal of running a high-velocity fundraising process is to move as many investors as you possibly can through your funnel at roughly the same pace. The approach is designed to maximize the number of VCs that make it to the end of your funnel and finish their diligence process at in parallel. That point is critical because Econ 101 teaches us that competition for a scarce resource leads to increased prices. One VC willing to lead your round is great. But having multiple VCs reach the same conclusion at roughly the same time is what drives up price.

In other words, a strong company gets you a term sheet, but a strong process gets you a valuation.

A few years ago, I wrote about how VCs adjust their approach to investing during periods of reduced deal flow. This particular post was focused on the slowdown that happened post-ZIRP, but it pretty accurately describes how the psychology of investors changes during the summer:

“[During periods] of slow deal flow, VCs by-and-large disassociate themselves from any external pressure to do new deals…The result? A creeping inertia to not make investments…As inertia sets in, investors slow their deal pace. This can mean more meetings with each investor and — crucially — more time between meetings (as VCs no longer feel the time pressure to rush into a deal). The reduction in pace, combined with some VCs stopping making new investments altogether, makes it harder for founders to generate competitive dynamics when running a high-velocity fundraising process.”

Despite the inertia that creeps in during the summer, each year many VCs loudly proclaim that “they’re open” as a means to drive deal flow in a time of reduced competition. They’re hoping that you fundraise in the summer specifically because they know everyone else has that same inertia:

• If they meet you in the summer and get really excited, they can likely ramp up their diligence efforts and reach a conclusion before you’ve booked a first meeting with many of their competitors

• If they can get to a term sheet quick enough, they may be able to win the deal without having to compete on price or terms

• If they’re interested but not enough to go fast, they still get an early look at your company and can slow play the process into the fall (giving them more data points to use in their decision while knowing that they likely won’t lose the deal)

Speaking of getting an early look, summer events is another well-worn approach that VCs use to get a sneak peak into companies that might be fundraising in the near future. Casual meetups and office hours (like those referenced by Forerunner at the start of this post) are one common tactic. Mini-conferences, founder bootcamps and other educational events is another.

Why do you think YC makes such a big deal about Startup School each summer…? 😉

I Totally Missed Your Email

Human etiquette is filled with performative interactions. Like all members of the animal kingdom, we have rituals around dating and mating, fighting and family. But unlike our wild friends, our etiquette has also evolved as a result of the changing nature of electronic communication.

“As per my previous email…”

Take the telephone, for example. It was invented way back in 1876 (150 years ago!), but it wasn’t until the 90s that we had a way to know who was calling before we answered. That’s right youngsters, back when I was a kid, you had to pick up the phone and say “hello?” in order to figure out if the caller was someone you wanted to speak with or a person you had desperately been trying to avoid.

(You also had to physically “pick up” the phone to answer it — none of this tapping or swiping or “Hey, Siri” nonsense…).

Once caller ID became mainstream, the etiquette and expectations around phone calls — especially missed calls — evolved. If you ran into someone whose phone calls you had been avoiding, you could no longer credibly claim that you didn’t know they had called. If you did, they immediately knew you were lying.

We’ve now officially reached that point with email — although a good chunk of the population still doesn’t realize it.

For most of the history of email, we didn’t actually know if the intended recipient opened an email that we sent. “Maybe it went to spam?” became the most common question asked when we didn’t get a response (and, by corollary, “It probably went to spam,” the go-to excuse when asked why we didn’t respond). Corporate email solutions, like Microsoft Exchange, have had the ability to track email opens (known as “read receipts”) for decades, but the functionality was mostly absent from mainstream email platforms.

That changed back in 2019, when an email startup named Superhuman added read receipt functionality to its client using tracking pixels (a concept that had been leveraged for years to deliver website analytics). Privacy advocates were in an uproar over the practice, but it wasn’t long before the backlash died down and other email clients began embedding similar capabilities into their products.

At this point, read receipts have been pretty widely available for more than 5 years, yet many people either don’t know they exist, forget that they exist, or delusionally believe that the person they’re interacting with isn’t using them.

I still regularly get email responses like this:

“I totally missed this email!

<response to the original email>

LMK and so sorry for being late.”

Meanwhile, the read history for the original email I sent looks like this:

We’ve all done this before — reading and re-reading an email before deciding whether or not to respond — and it’s honestly not a big deal if we’re talking about emails between friends or work colleagues. But if you’re a resident of Startupland™ responding to an email from a potential investor, another founder, or someone else you’re trying to build a relationship with, you absolutely need to stop doing this.

For starters, you should presume that the person who sent you the email has read receipts enabled. You should also presume that they might be keeping tabs on whether or not you opened it. Not because they’re weirdly obsessed with you, but because high-throughput email clients like Superhuman now put the open feed front and center:

And for those of you chuckling at this because your AI agent now takes care of all your emails, I promise that, “I didn’t see your email because my agent sucks at filtering,” isn’t going to buy you much credibility either.

In any case, there’s a good chance that many of the people you interact with these days are aware of how long it takes you to respond to their emails. Virtually every VC I know uses Superhuman. As do a significant percentage of founders in my network. Most of the time, your email response behavior isn’t going to make one iota of difference in your life. But if the person you’re responding to is in the process of evaluating you (such as an investor deciding whether or not to back your startup or someone in a position of influence trying to gauge if you respect their time), you might want to rethink how you handle email.

• If an email takes less than a minute to respond to, just do it (this has been best practice for a long time, yet many of us still don’t)

• If a request is going to take time for you to complete, send a quick note of acknowledgement to show your responsiveness

• And most importantly, stop sending emails claiming that “I just saw this” after opening and closing it for weeks

Even if you’re not at the point where you’re willing to trust an agent to fully manage your inbox, with AI now embedded into virtually every email client, there really isn’t a credible reason to let your backlog build up. Let the AI auto-generate quick responses for you and either tweak them or quickly hit send.

More than ever, velocity is the one metric that matters most. And for better or worse, email read receipts now provide a measurable indication of your velocity and how you prioritize things.

Reply quickly or be honest when you don’t. Your reputation will thank me later.

What is a Forward-Deployed Engineer (and Why Should You Care)?

If you’ve been paying any attention to tech media as of late, you’ve undoubtedly seen articles about the rise of AI’s hottest new role: the forward-deployed engineer (FDE). If the term is new to you, let’s start off with a basic definition of what an FDE is:

A forward-deployed engineer is an engineer who is taken from the core product team and “forward-deployed” into a customer environment.

That’s it. It’s not rocket science. An FDE is just a regular ol’ engineer who gets sent out into the field. So why is this such a big deal? And why now?

The History of the Forward-Deployed Engineer

The folks from Palantir’s PR department would have you believe that their company invented the forward-deployed engineers in 2011. Although they can certainly claim credit for having originated the modern job title, the practice of sending engineers from the core product team into the field long predated their adoption of it.

I know this because I built and ran a team of “forward-deployed engineers” back in 2009 (more on that later).

Generally speaking, sending highly-specialized engineers from HQ into customer environments isn’t an optimal use of a company’s resources. Notwithstanding brief trips into the field to get “real-world experience”, product engineers are almost always more valuable working on the product than they are deploying and/or customizing it. That’s why the vast majority of technology companies build separate organizations (staffed with less expensive hires) for field engineering tasks.

But every once in a while, a new technology emerges for which demand spikes before it is mature enough to be deployed by arms-length professional services workers. That happened with application servers in the late-90s. It happened again with big data platforms in the late-00s / early-10s.

And it’s happening today with AI.

What a Forward-Deployed Engineer Really Is (and What It Is Not)

Before we go any further, I think it’s helpful to know what an actual forward-deployed engineer is (especially given how quickly we’ve already progressed in the “hype cycle” of the term).

A true forward-deployed engineer is someone who has spent time working on a company’s core product and is later “forward-deployed” into customer environments in order to help with installation, deployment, customization and/or sales.

Despite what some articles suggest, a forward-deployed engineer is not just a rebranding of a solutions engineer/field engineer/integration engineer. Yes, the title sounds cool (and, yes, there are actual gains to be had by simply giving professional services workers a trendy new title). But the distinction is important as it goes to the unique capabilities that a forward-deployed engineer brings to the table — particularly for early-stage startups.

Solutions engineers and their ilk generally have strong technical backgrounds and experience working in customer environments but they rarely have deep insights into how the product was developed or how it works beneath-the-hood. Their effectiveness comes from the combination of advanced training, access to “employee-only” functionality, and a direct line-of-communication into the engineering department. Ultimately, solutions engineers can be thought of as supercharged power users who specialize in installing, deploying and customizing the product.

The didn’t build it, but they’re really good at installing it

In contrast, forward-deployed engineers understand the how and the why of a product’s operation by virtue of having contributed to its development. As we’ll see later, it is this experience and understanding that is critical to delivering customer value when demand for a new technology surges ahead of the its maturity.

When are Forward-Deployed Engineers Required?

In a typical technology company, the team responsible for installing, deploying and customizing the product for customers exists independently from the product team. This evolution happens surprisingly early on — and for very practical reasons — but demands a key prerequisite: the product must be mature enough that responsibility for installing/deploying/customizing it can be “handed off” to individuals who have little-to-no understanding of how it actually works.

This isn’t usually a challenging requirement. Case in point: the rise of SaaS software was entirely predicated on the notion that most tasks related to installation/deployment/customization could be automated (and those that couldn’t were easily encapsulated into standalone configuration tasks).

If we think about it within the context of the technology adoption lifecycle, most new technologies are relatively mature from an installation/deployment standpoint before early adopters come on board (and absolutely before they “cross the chasm” into the early majority). That’s because startups are usually able to work out the kinks in their deployment processes through beta testers and their earliest customers (innovators).

But what happens when customer demand surges before the product is ready? Or more precisely, what happens when customer demand surges before the process for installing/deploying/customizing the product is ready?

That’s what we are currently seeing with AI.

And while we’re not used to this dynamic after 10+ years of relying on easy-to-install vertical SaaS solutions, historically speaking it’s fairly common.

To illustrate this, let’s take a look at the rise of big data.

A Case Study in Forward-Deployed Engineers

For those of you who are too young to remember, there was a time not so long ago when large-scale data analytics was impossible. At the turn of the millennia — a decade before Snowflake or Databricks were founded — complex analytics could only be performed on data that was physically collocated on a single server. In those days, we already had web servers and mobile devices generating tons of data. We also had systems capable of storing all that data. But if you wanted to perform anything more than the most rudimentary statistical analysis on it…too bad.

By the mid-noughts, a handful of startups were trying to figure out how to make complex distributed analytics a reality. I was the first engineer at one such startup, Aster Data, which was founded by three of my friends from grad school.

We were much younger in those days…

By 2007, we had a handful of notable customers and enough revenue to raise our Series A. We used those funds to hire a number of experienced sales reps to scale our go-to-market efforts. And scale they did. The promise of distributed data analytics was so clear and compelling that demand surged. Fortune 500 companies were tripping over each other to schedule trials and pilots with Aster Data and our competitors. But we quickly discovered that our ability to install/deploy/configure the product couldn’t keep up with sales (and we weren’t alone in that regard).

Our first attempt to build an independent field engineering organization began as most such efforts do. In parallel to hiring our first sales reps, we brought on a number of experienced “pre-sales” and “post-sales” engineers from companies like Oracle and Business Objects. These individuals had spent years working alongside sales reps to understand the technical requirements of prospective customers and subsequently deploy database software into their organizations. Yet every single one of them struggled upon joining Aster Data.

The issue? Our product — and distributed data analytics technology more broadly — wasn’t mature enough to be deployed by individuals who didn’t have a deep understanding of how it worked beneath-the-hood. The installation and configuration of those early “big data” systems depended on a litany of variables, including the nature of a customer’s data, the types of queries they intended to ask of it, and even the brand and configuration of the servers that they planned to deploy it on. Our core R&D team — and those of our competitors — were still trying to understand and quantify exactly how all of these variables coexisted, so it was unreasonable (and, in fact, impossible) for anyone outside of the core product team to take on this responsibility.

Having failed multiple times to scale our field organization with traditional hires, in late-2008 I was tasked with figuring out a path forward. And there was only one solution we could come up with: to “deputize” some of our core product engineers into the field.

If you’ve ever tried to convince an engineer to trade in their IDE for the opportunity to be joined at the hip with an enterprise sales rep, it’s not exactly an easy sell. But we were able to convince four of our early engineers to sign on for 6-month field deployments (including two who relocated to New York and Chicago for their stints).

The results were incredible. But almost as important as the increase in sales was the fact that the strategy bought us enough time for the product to mature to the point that it could finally support a truly independent field organization (which we started building after raising our Series B).

Why Forward-Deployed Engineers are Critical to AI Adoption

By this point, the parallels between what’s happening with AI and my big data anecdote should be pretty clear.

Much like with big data, the enticing potential of AI has caused demand to surge amongst early adopters well before the processes for installing/deploying/customizing these products have matured. We can already see the impact of that imbalance in the pitiful numbers of companies that have managed to successfully get these systems into production.

One dirty little secret of the big data era was that a significant percentage of the industry’s early revenue came from R&D spend, as Fortune 500 companies tried to figure out how to get actual value from these systems. Sounds a lot like early token spend, doesn’t it?

Go on…

The parallels don’t stop there.

A few weeks ago, I wrote about the return of solution selling as the preferred sales methodology for AI. With AI technology significantly ahead of where the market is, sales teams are returning to a go-to-market approach that focuses on selling solutions to business problems. The return of forward-deployed engineers is a well-worn strategy for taking those early customers into deployment while we await the maturation of the technology.

But there is one big difference from what happened two decades ago. Both founders and VCs today understand the critical role that forward-deployed engineers can play in making sure these early customers are successful. Which is why the hype around FDEs is almost as loud as AI itself. Instead of wasting valuable time trying to build traditional field organizations, many AI companies are skipping right to engineers. And their VCs are following close behind with support.

A few weeks ago, a16z announced a fellowship for forward-deployed engineers. Such programs are normally launched as a means for VCs to find new founders to invest in. But in this case, if a16z can accelerate the development of the individuals who are critical to deploying early AI systems, the impact on their portfolio companies will be massive.

(And if they become known as the VC who understands the best way to get nascent AI products into production…well, that will undoubtedly help them win future deals.)

In the coming years, AI will mature and we’ll get to a point where arms-length professional services teams can once again drive the majority of installation/deployment/configuration (at which point the title forward-deployed engineer will return to being little more than the “ninja” of professional services). But I suspect that we’re a few years away from that.

In the meantime, if you’re struggling to get from sale to production (or even from interest to pilot), don’t be afraid to forward-deploy core engineering resources to make it happen. It can be scary at first to think about slowing down your product roadmap, but in the long run, it’s 1,000% worth it.

Cycling the Great Glen Way with Kids

Earlier this year, I had a business trip scheduled to Edinburgh to meet with my friends at Codebase. The trip happened to coincide with my son’s spring school break, so I decided to take him along for the week.

I wanted to make sure we did more than just stay in the city for our trip, so I started researching off-the-beaten-path adventures that might appeal to my energetic 9 year old. Eventually, I came across the Great Glen Way, a scenic 79 mile (127 km) trail from Fort William to Inverness in Scotland’s famed Highlands. The path starts at the base of Ben Nevis, the UK’s highest mountain, and runs north-east along the Caladonian Canal and alongside some of the country’s famous lochs (notably Loch Ness).

My son does a lot of mountain biking. Growing up between Vancouver and San Francisco, he can frequently be found climbing Mount Tam, exploring the trails above Mount Seymour or bombing down Grouse Mountain. While a 79 mile mountain bike ride might seem unrealistic to many, given that he regularly does rides of 10 miles or more after school, the Great Glen Way seemed like an appropriate — albeit challenging — adventure.

My 9 year old and his “apprentice”

The Great Glen Way is mostly promoted as a hiking trail, but it’s becoming increasingly popular with mountain bikers. There are bike shops in both Fort William and Inverness that rent bikes (“bike hires”) for one-way journeys.

Unfortunately, it was very difficult for me to find detailed descriptions on what to expect — particularly as it related to kids. I stumbled upon a few blog posts with photos of proud parents with their youngsters and some brief commentary scattered across social media sites, but nothing that really laid out whether or not the Great Glen Way is actually kid-appropriate.

Nonetheless, we took the plunge and decided to go for it. And now that we have (successfully) completed cycling the Great Glen Way, I thought I’d share the details that I wished I had before the trip. Here are the sections if you want to skip ahead:

• What is the Great Glen Way?

• Is the Great Glen Way Appropriate for Kids?

• Is the Great Glen Way Appropriate for Parents? (seriously)

• Renting Bikes to Cycle the Great Glen Way

• How to Divide the Great Glen Way into Stages when Cycling with Kids (our experience cycling the Great Glen Way)

• Alternate Itineraries for Cycling the Great Glen Way (if I knew then what I know now)

• Packing for Cycling the Great Glen Way

• Accommodations for Cycling the Great Glen Way

• Getting to/from the Great Glen Way

• Weather Considerations when Cycling the Great Glen Way

• Final Thoughts

With no further ado, I present to you Chris Neumann’s guide to cycling the Great Glen Way with kids!

What is the Great Glen Way?

The Great Glen Way is a 79 mile (127 km) hiking and biking path that runs between Fort William and Inverness. It was originally created as a hiking path (which is why most of the posts you find on the internet about it relate to walking). But it’s also a great path for cycling that’s increasingly popular with mountain bikers.

While it is possible to traverse the Great Glen Way in either direction, the most common route starts at Fort William on the coast and ends at the regional capital of Inverness in the north. Having completed it, I would agree that the route from Fort William to Inverness is definitely the better way for bikes.

Is the Great Glen Way Appropriate for Kids?

The Great Glen Way is not a particularly technical path from a mountain biking perspective. That said, it is not without its challenges. There are lots of inclines, some of which will likely require you to push your bike — and potentially your child’s — uphill (more on that later). If your child is not an avid bike rider and relatively athletic overall, I would hesitate to recommend this. But if they are, cycling the Great Glen Way can be a wonderful, fulfilling challenge.

At a high level, I would suggest that all participants:

• Regularly and confidently ride a bike, including going up and down hills

• Be able to cycle at least 10 miles on flat roads with relative ease (as a point of comparison, the Vancouver seawall is 13 miles / 22 km and takes my kids about an hour to complete)

• Have some experience / familiarity with trail riding and/or mountain biking

• Be able to run around and exercise for prolonged periods of time without getting tired or breaking down in tears

If this reminds you of your kids, then they might enjoy the Great Glen Way

Is the Great Glen Way Appropriate for Parents?

It’s not just the kids you have to think about!

Cycling the Great Glen Way is a legitimate workout. As I mentioned above, it’s not a particularly technical ride, but you are likely to end up with several long days of biking (potentially 6 hours or more). Moreover, unless your kids are extremely strong riders, you are going to have a few extended periods of time when you are pushing your bikes uphill (and, potentially, both your bike and theirs during some of the steeper segments). Add to that the fact that you’ll inevitably be carrying the lion’s share of any luggage and you need to be in decent shape.

I’m not nearly as avid a rider as my kids, but I do exercise regularly. I certainly felt like I earned by evening pint at the end of each day, but I never felt close to exhaustion (nor did my son).

The start of our adventure

Renting Bikes to Cycle the Great Glen Way

There are a number of bike shops that rent bikes (“bike hires”) for one-way trips to cycle the Great Glen Way. That said, not all of them have kids bikes for hire, so make sure to call in advance.

We rented from the folks at Off Beat Bikes in Fort William. They had the most rental options for kids and were very helpful in making sure we got the right equipment. Not only that, when a change in our flight caused us to arrive later than we intended, they offered to come into the shop on a day when it was closed so that we could get our bikes and not have to otherwise adjust our plans (thank you Damian! 🙏)

We rented standard hardtail mountain bikes for both of us, which came with helmets and a repair kit in case of emergency (there are also electric bike options, but since those aren’t any available for kids, it seemed silly for me to have an e-bike whilst my son was doing hard work!).

Our rental bikes

We also rented panniers (saddle bags) for my bike to carry some of our belongings. Many of the posts about cycling the Great Glen Way encourage riders to forgo panniers and make sure that they can carry everything on their back. That might be realistic if you’re a local, but if you’re coming to Scotland from abroad, chances are you have more stuff than you would want to carry on your back during a long ride. Having panniers also leaves easy room for sandwiches, drinks and extra snacks for the day.

How to Divide the Great Glen Way into Stages when Cycling with Kids

Figuring out how to divide up the stages of the Great Glen Way was one of the hardest parts of planning this trip.

Most of the articles and posts on the internet relate to hiking (which typically takes 5 - 7 days) or are clearly written for avid adult mountain bikers (generally presented as a 3-day journey). Based on our experience, I would recommend either 4 or 5 days when cycling the Great Glen Way with kids.

We broke up our journey into 4 stages/days:

1. Fort William to Invergarry (25.36 miles)

2. Invergarry to Fort Augustus (8.21 miles)

3. Fort Augustus to Drumnadrochit (21.68 miles)

4. Drumnadrochit to Inverness (21.71 miles)

Below, I go into detail on our experience with each stage. Later on, I’ll share some thoughts on alternate itineraries that I think might make sense in hindsight.

Note: all distances, elevation changes, etc. are based on data collected by my Apple Watch’s built-in Workout app. I have no clue how accurate this app is nor how it compares to dedicated cycling apps like Strava, so take all measurements with a grain of salt.

Day 1: Fort William to Invergarry

Fort William to Invergarry

Day 1 Summary

• Distance travelled: 25.36 miles

• Active biking time: 4:52

• Total time including breaks: 6:01

• Elevation gain: 1,358 ft (415 max)

• Description: The Great Glen Way from Fort William to Invergarry is mostly flat and runs alongside Loch Lochy and Loch Oich. It’s generally an easy ride and serves as a great start to the trip (though, in our case, an unexpected detour caused by public works added an extra 90 minutes to our first day).

Day 1 Experience

Our first day started late, thanks to our flight into Edinburgh being delayed. Instead of picking up our bikes the day before and leaving right after breakfast, we had to get them in the morning (shout out to Damian from Off Beat Bikes for coming in on his day off to get us setup!). After getting our equipment set and our panniers packed, we grabbed some snacks and sandwiches from a nearby shop and headed out.

Damian pointed us to the starting point of the Great Glen Way near the edge of town. We easily found the first of many light blue markers to indicate the path and we were off on our adventure!

The start of our first stage took us along Fort William’s seaside. It was about 45 minutes of easy riding until we reached the first stopping point: Neptune’s Staircase (the UK’s longest staircase-style lock). Although we had barely started cycling, it was already noon, so we decided to stop at a nearby cafe for lunch.

After lunch, we set off for the rest of our day.

The section of the Great Glen Way between Fort William and Invergarry is generally described as one of the easiest, as the majority of it runs alongside the lochs and canals. Unfortunately, there was a diversion between Gairlochy and Invergarry that made our first day more difficult than expected.

The works were definitely not completed “early in 2026”

The Great Glen Way’s website provides up-to-date details on any diversions or issues with the path, so you should check it regularly in the lead up to your trip. Unfortunately for us, the recommended alternative for cyclists was not a feasible option, as we were planning to stay in Invergarry for the night. We quickly discovered why the website stated that, “…the diversion route is a little trickier to travel on a bike”.

Our easy ride along the canals was replaced with more than an hour of pushing our bikes up a hill that was too steep for my 9 year old to ride 🤦‍♂️.

While the detour took us further up into the hills than we had expected on day one, it wasn’t all bad news. The extra elevation gave us an excuse to pull out our sidekick for the journey: a tiny DJI Mini 3 drone.

Official videographer

This pint-sized drone is both perfect for kids while being small and light enough to not add much weight to the journey (I kept it strapped to my bike’s rack for easy access during our travels). Throughout our trip, we took countless photos and videos, which my son later turned into a short film about his adventure.

The detour provided our first look at the lochs from above, as well as the first of many waterfalls we encountered along the Great Glen Way.

Overall, the diversion probably added 90 minutes to the trek. A little intense for the first day, but nothing we couldn’t handle. After a lengthy cruise down from the hills, we arrived at the Invergarry Hotel where we unloaded our gear and enjoyed the largest plate of fish and chips my son had ever seen.

Day 2: Invergarry to Fort Augustus

Invergarry to Fort Augustus

Day 2 Summary

• Distance travelled: 8.21 miles

• Active biking time: 1:56

• Total time including breaks: 2:06

• Elevation gain: 411 ft (461 max)

• Description: The Great Glen Way from Invergarry to Fort Augustus is a short ride that starts in the hills just above the shore of Loch Oich and finishes alongside the canal between Loch Oich and Loch Ness. It’s a quick, easy trek that left us with plenty of time to explore the town at the southern tip of Scotland’s most famous lake.

Day 2 Experience

I intentionally planned for a light second day of cycling the Great Glen Way, as I figured that the combination of jet lag and a long first day might benefit from some rest.

Day 2 started with a short (~15 minute) uphill climb, followed by a few miles along a easy-going logging road.

At the top of the hill, we took a break to get some more video with our trusty drone. While getting our sidekick setup, we encountered the first of several unexpected “Top Gun” moments, as Royal Air Force jets ripped across the lochs on training runs.

Sadly, we did not get any photos of the RAF jets

After our break, we cruised back down to loch-level and leisurely cycled along the canals towards Loch Ness and into Fort Augustus in time for lunch.

The afternoon respite was appreciated by both of us after 24 hours of travel from North America and a full day of biking. We spent the afternoon exploring the town, sampling several of the ice cream shops along the canals and enjoying an early dinner at one of the local pubs.

Day 3: Fort Augustus to Drumnadrochit

In contrast to our leisurely Day 2, our third day of cycling was a long one (6 ½ hours cycling time / 7 ½ hours total travel time). I’ll break the recap into two parts, which I’ll revisit in the following section about alternate itineraries for cycling the Great Glen Way.

• Day 3a (morning): Fort Augustus to Invermoriston

• Day 3b (afternoon): Invermoriston to Drumnadrochit

Fort Augustus to Invermorriston

Invermorriston to Drumnadrochit

Day 3 Summary

• Distance travelled: 21.68 miles

• Active biking time: 6:35

• Total time including breaks: 7:32

• Elevation gain: 3,085 ft (971 max)

• Description: The Great Glen Way from Fort Augustus to Drumnadrochit consists of two sections: a mostly flat, easy ride from Fort Augustus to Invermoriston and more challenging section further up into the hills between Invermoriston and Drumnadrochit. The second section includes several extended climbs, which gave this stage the largest total elevation gain of our journey.

Day 3 Experience

The morning section from Fort Augustus to Invermoriston (“section 3a”) was relatively easy and quite similar to Day 2. There were a few ups-and-downs, but for the most part the trail tracked fairly close to loch-level.

Along the route, we encountered the first of several “forks in the road” that form part of the Great Glen Way. Each fork leads to a “high road” and a “low road” with signage that includes detailed maps and descriptions of each route. Generally speaking, the “high roads” provide better views and scenic opportunities, but require additional climbs. In contrast, the “low roads” typically follow logging roads with easier riding but miss out on some of the views. We made a point of choosing the low roads at each opportunity, mostly because it was unclear how steep the inclines were and how much extra time they would add to our journey.

High road or low road…?

We took 2 ½ hours to complete the morning section and reached Invermoriston just before noon, stopping at a local cafe for lunch. After that, we set off on the trail to Drumnadrochit (“section 3b”).

Immediately after leaving town, you head up a set of switchbacks that go on for several miles with virtually no flats. For a strong adult rider, it would be a manageable (albeit lengthy) climb. For a 9 year old, it meant extended periods pushing the bike uphill.

Once you reach the top, you’re met with a very active logging road. The ride itself became much easier at that point and there was a certain adventure to riding amongst hundreds of giant logs.

Eventually, we headed downhill, only to start another — even longer — uphill climb.

All things told, I would guess that we spent ⅔ of this section on climbs. That makes the journey from Invermoriston to Drumnadrochit one of the more challenging segments of the Great Glen Way. But there were still plenty of great moments to enjoy, including more waterfalls, bridges and viewpoints.

After a full afternoon of riding, we cruised into Invermoriston with a brisk descent and finished at the welcome sight of the Loch Ness Inn.

Drumnadrochit is the home of Urquhart Castle and the jumping off point for many Loch Ness-related adventures. Unfortunately, our late arrival left us with little time (or energy) to explore. This was the only disappointing part of our adventure — and a point I revisit below in discussing alternate routes to consider.

Day 4: Drumnadrochit to Inverness

Drumnadrochit to Inverness

Day 4 Summary

• Distance travelled: 21.71 miles

• Active biking time: 7:05

• Total time including breaks: 7:44

• Elevation gain: 1,852 ft (1,213 max)

• Description: The Great Glen Way from Drumnadrochit to Inverness starts with the steepest climb of the entire journey, high up into the hills above Urquhart Castle. But the climb was absolutely worth it. At the top, we were greeted with a magical forest filled with surprises that eventually opened up into a quaint farming community nestled in the Highlands. After a brisk descent back down to loch-level, the final stretch on a running path alongside River Ness led us to our final destination: Inverness Castle.

Day 4 Experience

The final stage of the Great Glen Way had the most challenging start to any of our stages, starting with a steep climb from Drumnadrochit high up into the hills above Loch Ness. The early part of the trail was clearly designed for hikers rather than mountain bikes, which meant a lot of walking and a few situations where I had to push both bikes uphill (as my son could not physically lift his bike up some of the gnarlier segments).

More climbing

Even though the initial climb was tough, there was plenty to see along the way that kept it enjoyable. The trail passes by many farms (and lots of sheep!) and we got buzzed a few more times by RAF jets whilst we were walking along. The forest eventually flattens out, leading to some great riding with a few unexpected surprises along the way (which I won’t spoil).

After awhile, the forest gives way to a country road that winds through a quaint farming community. The plateau views above Inverness are stunning, though it’s quite windy (so be prepared). We spent about an hour riding amongst farms before our final reward: a massive paved downhill towards Inverness.

(Note: the final descent towards Inverness is a significant downhill on an active road, so make sure your child is comfortable riding roads with steep downhill gradients safely.)

At the bottom of the hill, there were a few final miles of flat riding on a running path alongside the River Ness before we finally reached the city of Inverness.

The official end of the Great Glen Way is at Inverness Castle. But across the street, the folks at the Castle Tavern happily give out “certificates of completion” to kids who successfully complete the Great Glen Way. We sat down for a well-earned pint / juice and celebrated our achievement before heading to our hotel for the night.

Alternate Itineraries for Cycling the Great Glen Way

Having completed the Great Glen Way, there are three alternate itineraries that I would consider with kids, based primarily on the difficulty of section 3b (Invermorriston to Drumnadrochit) and the impact it had on our time in Drumnadrochit:

Alternate Itinerary #1 (4 Days)

The first alternate itinerary I would consider would shift the segment from Fort Augustus to Invermoriston (our segment 3a above) to Day 2. Whilst we absolutely loved the Lovat Hotel and a shortened Day 2 served as a welcome respite after an unexpectedly difficult Day 1, it left us with such a long third day that we had no time to enjoy Drumnadrochit.

That meant we didn’t have time to explore Urquhart Castle, take a boat trip onto Loch Ness, or search for Nessie. Which really wasn’t cool.

This alternate route would be:

• Day 1: Fort William to Invergarry (Medium without diversion / hard with diversion)

• Day 2: Invergarry to Invermoriston (Medium)

• Day 3: Invermoriston to Drumnadrochit (Medium)

• Day 4: Drumnadrochit to Inverness (Hard)

Alternate Itinerary #2 (4 Days)

A number of itineraries posted on the internet start with Day 1 going all the way from Fort William to Fort Augustus. I think this would actually be a reasonable approach, provided that there is no diversion in place.

The first segment would certainly be lengthy, but given that it’s almost entirely flat (without a diversion in place) it wouldn’t be much harder than what we encountered with the diversion.

This alternate route would be:

• Day 1: Fort William to Fort Augustus (Hard without diversion / not recommended with diversion)

• Day 2: Fort Augustus to Invermoriston (Easy)

• Day 3: Invermoriston to Drumnadrochit (Medium)

• Day 4: Drumnadrochit to Inverness (Hard)

Alternate Itinerary #3 (5 Days)

If your schedule allows, completing the Great Glen Way across five days instead of four is another option that would allow for even more time to explore and enjoy the lochs and highlands.

In this case, I would suggest completing the stage from Fort Augustus to Drumnadrochit across two days (i.e. splitting up our stages 3a and 3b above):

• Day 1: Fort William to Invergarry (Medium without diversion / hard with diversion)

• Day 2: Invergarry to Fort Augustus (Easy)

• Day 3: Fort Augustus to Invermorison (Easy)

• Day 4: Invermoriston to Drumnadrochit (Medium)

• Day 5: Drumnadrochit to Inverness (Hard)

Packing for Cycling the Great Glen Way

When it comes to traveling with kids, packing is always a challenge. Do you bring more clothes and extras knowing that likely things are going to go wrong, or do you pack lightly and deal with the consequences?

Coming across the Atlantic, we travelled with two large backpacks (rucksacks), containing all of our clothes, toiletries and biking necessities, a few items for the long airplane rides (e.g. headphones and books) plus my work necessities (work-appropriate clothes, laptop, etc.). If it weren’t for the fact that this adventure was combined with a work trip, we probably could have cut our weight by half, but it was nonetheless manageable.

My son had an Osprey Ace 38L backpack while I used my wife’s Osprey Fairview 40L travel backpack (which is a much more appropriate size for cycling than my significantly larger 65-liter hiking backpack.)

Walking to the plane

As I mentioned earlier, I rented panniers (saddle bags) for my bike. This was specifically because I knew that our backpacks would be far too heavy to wear on the ride. Each morning, we transferred the majority of our clothes and all of our heavy items (electronics, extra shoes, etc.) into the panniers, leaving us with relatively light backpacks for the day. We also picked up sandwiches and some snacks each morning, which went into the panniers.

(I should note that there are courier services available that will transport luggage between towns along the Great Glen Way, but that wasn’t something we looked into.)

Essentials

I won’t go into full details about each-and-every item we packed. What I will say is that you should think in terms of layers when packing clothes (if you spend any time in San Francisco, you know what I’m talking about). We each had short-sleeve and long-sleeve shirts, a warmer sweater / sweatshirt, a light jacket and a couple of pairs of comfortable athletic pants. We added and removed layers multiple times each day in response to the changing weather and wind. We also each had two pairs of shoes (one pair of rugged, all-weather hiking shoes for riding and another pair of shoes for walking around) plus extra socks just in case.

In addition to clothing and toiletries, key items we packed included:

• Water containers (either a hydration pack for your backpack or a very large water bottle)

• Sunscreen

• Bug repellant (there are lots of midges depending on the time of year)

• Hiking/athletic snacks (energy bars/chews/gels/etc.)

• Basic bike repair knowledge (make sure you know how to perform basic repair tasks, including replacing a flat tire and resetting a chain that falls off)

And, most importantly: patience.

It goes without saying that, as a parent, you need to approach an adventure like this with the right mindset. Even if it’s not physically challenging for them, riding the Great Glen Way is mentally challenging for kids. Take as many breaks as you need to. Indulge in whatever distractions and exploration they want to do. Don’t worry if you’re “on time” for anything. And definitely don’t skimp on giving out snacks (there’s no reason for anyone to be hangry!).

Things We Didn’t Need to Pack But I’m Glad We Did

There were a few things we didn’t use and/or weren’t strictly necessary, but I’m glad we packed. These included:

• Rain clothes — We each had a pair of easy-to-pack waterproof pants and a rain jacket from REI. We never needed to pull them out — as it only ever rained lightly during our travels — but given the unpredictable weather in Scotland, I’m glad we had them (more on that below).

• Small medical kit - Thankfully, we had no injuries, but making sure you’re prepared for the unexpected is important with any adventure.

• Power bank - My Iniu 65W power bank added another extra couple of pounds of weight to the load. While we never used it, my phone was close to 0% on several occasions (in no small part due to the many photos and videos we took). We often went for hours without seeing anyone else, so I would have hated to not have a phone available if an emergency took place or something went wrong.

• Drone - Definitely not a “must have” but it certainly added fun to the trip. We brought our small DJI Mini 3 drone with us and used it during many of our breaks to document the journey. (In the UK, you are required to have a drone license in order to operate a personal drone, so if you bring one make sure that you and your kids complete their online “driving tests”.)

• Baseball gloves - My son loves playing baseball and didn’t want to “miss out” on any practice time while we were in Scotland. We brought along our gloves (and a ball) and attached them to the panniers with carabiners. They were a bit bulky on some of the narrow trails, but I was happy to carry them for some more father-son moments.

• Books - My son reads a lot. As easy as it would have been to pack a Kindle, my wife and I had long ago decided that we were going to prioritize physical books as a key part of his learning experience. And he definitely read a lot that week.

An extra 5 pounds that I was (mostly) happy to carry

Accommodations for Cycling the Great Glen Way

This is really important: you must book your accommodations for every single night of your journey in advance. In fact, you need to do it well in advance!

The towns along the Great Glen Way have limited accomodations (generally one or two small hotels, plus a handful of bed-and-breakfasts). During the high season, many of the rooms are taken up by tour groups, leaving relatively few options available for booking. If you take only one thing away from this post, it should be this: the moment you decide to cycle the Great Glen Way and choose your route, book your accommodations before doing or planning anything else!

Here are the places we stayed along our route, each of which I would gladly recommend and stay at again:

• Fort William: Guisachan Guesthouse

• Invergarry: Invergarry Hotel

• Fort Augustus: The Lovat

• Drumnadrochit: Loch Ness Inn & Bunk Inn

The Invergarry Hotel has only 13 rooms. There are two hotels in Invergarry.

Getting to/from the Great Glen Way

Traveling to and from the Great Glen Way is easy by train.

The scenic West Highland Line runs from Glasgow to Fort William and there are multiple train operators that go daily between Edinburgh and Inverness. We flew into Edinburgh airport, took a taxi to Glasgow and then rode the West Highland Line to Fort William. At the end of our ride (after a good night’s sleep in Inverness) we took the train back down to Edinburgh. In both cases, the train ride was a little over 3 hours and easy to book through ScotRail.

Weather Considerations when Cycling the Great Glen Way

The weather in Scotland can be quite finicky (though if you’re coming from Vancouver or the Pacific Northwest, you’ll be very familiar with it). We had some light showers on the first two days of our journey, but otherwise the weather was sunny and clear.

When planning to cycle the Great Glen Way, pay particular attention to the time of year and the expected weather. It is not realistic to cycle the Great Glen Way with kids if it is raining more than lightly. Aside from the fact that biking in the open rain isn’t that much fun to begin with, significant portions of the Great Glen Way are likely to be difficult, if not impossible, to traverse by bike if turned into mud — especially not with panniers.

While the sections alongside the canals are durable, the logging roads upon which much of the Great Glen Way takes place are open to the elements and not overly robust. In addition, some of the steeper trails — most notably the climb out of Drumnadrochit on the final day — would be virtually impossible to utilize in poor conditions.

Thankfully, there are options for traveling from one town to another should your plans get derailed by weather (such as buses and taxis).

Final Thoughts

If you made it all the way here, then I offer you my hearty congratulations (and thanks for reading! 🙏).

Completing the Great Glen Way with my 9 year old son was a fantastic experience for both of us. While we did have to push our bikes uphill on some of the sections, nothing ever felt unbearable. The views at the top were incredible and there were countless opportunities for exploration (including wonderful educational stations located throughout the trail).

Bottom line: cycling the Great Glen Way was a wonderful experience that I highly recommend if your kids are into biking. It takes a bit of extra effort, planning and patience to make it through the journey, but the reward in terms of their feelings of accomplishment and the memories you’ll make along the way are well worth it.

It’s fun, fulfilling, and it builds character 😉

Things I Think I Think - Q2 2026

There is a magical time once every 4 years when the world comes together around the beautiful game. Given all of the geopolitical changes that have taken place over the past few years, it’s hard not to smile at the fact that cohost United States will play its first elimination game today, on Canada Day, while Canada will next take to the pitch on the 4th of July.

Let’s go Canada! 🇨🇦

Set against the backdrop of this summer’s competition for global sport supremacy, here are 5 Things I Think I Think - Q2 2026 Edition:

1. Fast and then Slow

The frantic pace of investment that characterized the first quarter of 2026 continued into Q2. Megafunds, in particular, continued to throw around their proverbial weight, with numerous preemptive rounds happening at the start of the quarter (especially at Series A and B). I suspect that when the statistics for Q2 eventually see the light of day, we’ll see that valuations for the top 5% of companies continued to climb sharply through Q1 and into Q2.

But a funny thing happened as May rolled around: the pace of deals started to slow. Gradually, then suddenly.

In particular, the preemption of Series A and B rounds that was prevalent during the first third of the year dropped off rather dramatically towards the end of Q2. I watched a number of VCs that had been aggressively pursuing preemptive deals downshift their activity mid-quarter. Almost in sync, a number of founders I know who were looking down the barrel of preemptive term sheets stepped back from the alter, with plans to revisit in the fall.

It’s not often that you see VCs and founders adjust their activities in parallel. In my inaugural “Things I Think I Think” post back in 2023, one of my observations was about Canadian founders lagging in their acceptance of and adjustment to changes that were happening in the market post-ZIRP. So what happened in Q2 was quite unusual (but something I view as a strong positive). It wasn’t so much a correction in the fundraising market as a mutual, unspoken agreement by both sides to hit the pause button.

Coming into Q2, I had spoken with both VCs and founders who felt that they had no choice but to play the “preemption game”. As alluded to in my Q4 2025 update, investors fearful of missing out on the next OpenAI or Anthropic were driving “…a degree of preemption and FOMO for hypergrowth AI startups that’s on par (if not greater) than what happened during ZIRP.” At the same time, a number of founders I spoke with felt like they had an obligation to entertain preemptive investor interest. Many of them were spending considerable cycles on investor meetings even though they already had plenty of money in the bank.

By the time June came around, the slowdown in activity had expanded well beyond the “cease fire” in preemptive investments. Many VCs I know — from Pre-Seed to Series B — had all but stopped taking new meetings by the start of June. Perhaps it was a similar desire to hit pause and revisit their AI-related investment theses. Perhaps it was simply a weariness after more than a year of frenetic activity. Regardless, this summer is going to be a particularly bad time to fundraise (but a great time to be heads down on your business).

2. The IPOs are Coming! The IPOs are Coming!

Q2 saw the first of three potentially massive tech liquidity events with SpaceX’s record-breaking IPO. But it was the other two IPOs on the horizon — from Anthropic and OpenAI — that had a more immediate impact on the behavior of many VCs.

As I alluded to above, a lot of the high-octane investor behavior over the past year has been driven by VCs desperately trying to replicate investments in Anthropic and OpenAI. Both companies have achieved unprecedented user adoption, revenue growth and — most appreciated by investors — valuation growth (aka markups). And, until recently, both seemed on a path that would quickly translate those paper gains into similarly unprecedented IPOs (DPI!).

But what seemed like surefire wins suddenly became not-so-certain. Anthropic’s smooth sailing hit bumpy seas as it repeatedly found itself in conflict with the U.S. government, while ongoing questions about OpenAI’s business fundamentals has led to speculation that it may delay its IPO until 2027.

Pete the Cat, early-stage VC

As the shine began to come off these two industry darlings, VCs slowly started to remove their rose-colored AI glasses. The slowdown in preemptive activity I described above was very much triggered by the recognition that, despite their unprecedented growth trajectories, the path from inception to IPO for AI-based companies is still a bumpy one.

To be clear, investors are by no means giving up on AI (many are still wearing very thick rose-colored AI glasses, albeit with a slightly lighter tint). The fact that Anthropic and Open AI have hit bumps in the road won’t damper VC enthusiasm for AI’s industry-disrupting potential. Rather, investors are adjusting their expectations when it comes to the trajectories of these companies, particularly as it relates to time-to-liquidity. Ultimately, that will affect the rate at which preemptive rounds occur and the valuations at which those rounds happen.

But make no mistake, once fall comes around, VCs will once again be champing at the bit to invest in the latest-and-greatest AI startups.

3. Agents Cross the Chasm

When I wrote my end-of-year update six months ago, nobody had heard of moltbot clawdbot OpenClaw. By Q1, prominent VCs were showing up on podcasts wearing lobster costumes. But the technology was still barely usable. We were still very much at the Homebrew Computer Club phase of the technology adoption lifecycle.

But like many things related to AI, the rate of progression from barely usable open source “projects” to relatively-stable early “products” has been unprecedented. This past quarter, a number of companies came to market with purpose-built agent products, ranging from more mature open source projects, like Hermes, to agents for managing family calendars. Howie, an email scheduling assistant that I previously wrote about, recently released “Howie Blue”, a full-blown personal agent that integrates with both email and iMessage (hence the name).

My friend Hiten did a great job of describing the value that many early adopters got from working with nascent agent platforms, though I’m not sure that the general populace had nearly as much ROI to gain from adopting the technology so early. But with so many agent-based products now coming to market, the bar has never been lower to start using AI agents.

I expect that adoption rates of agent-based products will skyrocket as we head into the back half of the year, especially in Startupland™. For founders and investors alike, the takeaway should be this: if you aren’t already using agents in some form or another (not just within your company, but you personally) take some time this summer to get started. It doesn’t matter if you’re rolling your own open source agent or signing up for one of the many turnkey solutions hitting the market. Do something.

Continuing to sit on the sidelines won’t land you in a “permanent underclass” (despite what many in Silicon Valley continue to believe), but it will absolutely leave you at an increasing competitive disadvantage.

4. Canadian VC on the Brink

For the past few quarters, the ongoing bifurcation of venture capital has led to a relatively small number of big VC firms capturing an increasing percentage of LP dollars. This shift is happening all over the world, but the particular manner in which it has manifested in Canada has the potential to completely devastate the country’s tech sector.

RBCx recently published its mid-year report on Canada’s VC market, which included a staggering claim: as of the end of 2025, the country’s emerging managers (new VCs who are on their first, second or third fund) have raised 36% less capital than projected. For a country that already has too few early-stage VCs, a lack of fundraising by emerging managers is nothing less than an existential threat to its entire tech sector.

A lack of support for emerging managers isn’t a new phenomenon in Canada. In fact, I wrote about it 3 years ago. But the implications of the current prolonged drought has the country on the precipice of disaster — whether or not its leaders realize it.

Why? Emerging managers overwhelmingly invest at the earliest stages. They also tend to bring new ideas and new perspectives to startup ecosystems. That frequently leads them to be the first check into companies with very different profiles to what “old guard” VCs back, which is key to an ecosystem’s ability to innovate and drive long-term growth. Lisa Cawley, Managing Director of Screendoor, a leading fund-of-funds that invests exclusively in U.S.-based emerging managers, described the critical role of new VCs to the Wall Street Journal last year,

“New VC firms matter; they have an opportunity to drive competition and disrupt incumbent complacency. The question shouldn’t be ‘How many VCs,’ but why are there so many mediocre ones?”

That said, a dip in the number of early-stage VCs in an ecosystem typically doesn’t threaten its long-term survival. But time is not on Canada’s side. Its unique existential threat comes from the fact that its neighbor to the south is home to the tech world’s largest, fastest-moving and most risk-taking capital market. At a time when fewer Canadian VCs are willing (or able) to write the first check into first-time founders, a growing number of local founders have simply stopped looking for capital at home. Instead, they’re going straight to Silicon Valley.

And in many cases, those first-time Canadian founders are choosing to move to the U.S. as part of the process.

A handful of efforts have recently emerged trying to address the lack of capital flowing to emerging managers in Canada — notably the launch of the Canadian Startup Capital Association (CSCA) in April — but the country needs to make some bold, systemic moves fast. The last time Canada experienced a dip in the number of active VC firms, most Silicon Valley VCs were unwilling to invest in Canadian startups. That’s no longer the case.

If 2026 ends with a similar lack of fundraising success for Canada’s emerging managers, by this time next year there may not be much of a startup pipeline for the rest of the ecosystem to support.

5. We Lost a Giant

Last week, Om Malik passed away after a prolonged health battle. Countless posts and articles have been written about him in the days since. This observation from John Gruber does a good job of capturing how many of us in the tech industry currently feel,

“it is a profound irony that a man with such a big and beautiful figurative heart could have such a lousy literal one.”

I only met Om a handful of times over the years, so I can’t say that I knew him well, but his work and legacy had a profound impact on my journey.

His namesake publication, Gigaom, was unlike any other tech publication at the time (or since). It seamlessly blended the “breaking news”-style coverage of Silicon Valley that was on the rise with a deeper level of analysis — about both technology and business — that simply didn’t exist anywhere else. The approach stemmed from Om’s personal style of journalism, which Stacey Higginbotham described thusly,

“He was the smartest guy writing about really geeky tech and putting it into context. He was able to discuss the nuts and bolts of technology and then extrapolate what new advances would mean and how people would react.”

Gigaom focused primarily on infrastructure and enterprise software, which put both Aster Data and DataHero squarely in its coverage box. In 2009, the publication brought on a dedicated infrastructure/data writer named Derrick Harris, who I quickly got to know and soon became friends with. He shared his own thoughts on Om’s passing here.

For more than 5 years, my professional world existed very much within the orbit of Gigaom. I got to know many of the exceptional writers that passed through its doors and had the privilege of speaking at several of the company’s influential conferences. To this day, the way in which I view tech journalism and its potential for positively influencing the world while holding people in power accountable is overwhelmingly influenced by my years interacting with the team at Gigaom.

In a world where tech media is increasingly driven by algorithms and agendas, the type of deep, thoughtful writing that Om championed is frustratingly hard to come by. If you haven’t already checked out Crazy Stupid Tech, the blog Om launched last year with Fred Vogelstein, I strongly encourage you to do so.

The Cost of Hubris

A few weeks into my first batch as an EIR at 500 Startups, we held a week-long series of talks about fundraising. In those days, fundraising best practices weren’t as widely known as they are today, so the topics we covered were new to virtually all of the founders participating in the program.

Towards the end of the week, I was chatting with Marvin Liao — head of the firm’s flagship accelerator — when one of the founders approached us to discuss his fundraising process. This particular founder was one of the strongest in the batch. He had bootstrapped his company to an impressive amount of revenue, enough so that he should have been able to easily raise a competitive Seed round. But there was a catch.

Despite being part of a mentorship-based accelerator, this particular founder had zero interest in listening to anyone’s advice.

On that particular day, this founder came towards us not to ask questions, but to vent. You see, he had just returned from Sand Hill Road after pitching a top tier VC — his dream investor — and, suffice to say, it did not go well.

Why not? For starters, this founder hadn’t spent any time preparing his fundraising pitch. He hadn’t worked on it, refined it or practiced it. Not once.

Despite an entire week of programming about fundraising, and despite partner-after-partner-after-partner urging him to hold off on meeting with any VCs until he was ready, this founder decided that he knew better then everyone else and sauntered into the offices of [redacted] without so much as a slide.

And he totally, completely, unequivocally sh*t the bed.

It was so bad that the partner he met with at the tier one VC texted Marvin immediately after the meeting to ask, “What the hell was that dumpster fire?”

Watching this founder recount the experience to us was like watching a car wreck in slow motion. His reflection on what went wrong (or, more precisely, his complete lack of self-reflection) was astonishing to me. The entire conversation consisted of him complaining about how clueless the VC was, without so much of a inkling of recognition that he might have gone in unprepared.

When he eventually finished venting and walked away, I stood there with what must have looked like an utterly gobsmacked look on my face. Marvin turned towards me, smiled, and whispered,

“There’s always one.”

After the founder left, I asked him to explain.

“There’s always one,” Marvin continued. “One founder who thinks they’re special. One founder who thinks the rules don’t apply to them. One founder who thinks they know better than everyone else.”

“Every. Single. Batch.”

As my tenure at 500 Startups continued, I was astonished by the accuracy of Marvin’s observation. Every single batch, there was a founder who did this. A founder who took the accelerator’s investment, accepted a place in the batch, and immediately upon arrival decided that they needed none of the advice or education the program had to offer.

Hubris is a funny thing. You have to have a certain amount of hubris to start a company to begin with — entrepreneurship demands the audacious belief that you can create something out of nothing — but the line between confidence and cockiness is a thin one. And landing on the wrong side of it can have a detrimental impact on the trajectory of your company. Whether you realize it or not.

In the 10+ years since that first encounter, I’ve seen similar stories play out time and time again. Oftentimes when founders fall victim to hubris, the results are fatal to their startups. Those that do manage to survive frequently end up so far off course that the company never comes close to reaching its full potential.

I’ve observed some patterns when it comes to founder hubris and wanted to share them in the hope that I can help you to avoid its trap. Here are some common themes I’ve seen over the years:

Early Success

I’ve found that disproportionate hubris is often present in founders who achieved uncommon early success and/or hit significant milestones on their first try. Examples include:

• Unusually strong early user or revenue growth

• Unexpected virality or marketing notoriety

• An unusually easy first fundraise

Founders who achieve such quick wins without realizing how unusual they are often attribute their early success to skill rather than other factors (such as luck, preexisting connections or just good timing). The result is frequently a form of complacency — sort of like when you ace the first few quizzes in a class, get used to how easy it is, and presume you don’t have to study for subsequent ones.

Charisma

In my experience, there is a strong correlation between a founder’s charisma and the likelihood that they develop hubris early in their journey. This is especially pronounced when they have an easy time raising their first round of funding.

In most cases, the initial round of funding (angel and/or Pre-Seed) is driven by narrative. Many founders with strong charisma have an easier time raising their first round specifically because of their storytelling and persuasive abilities. Where things can go sideways is in subsequent funding rounds, when investment decisions are driven more by analysis of early traction, unit economics and so on. I’ve seen many founders who breezed through their Pre-Seed round run full speed into a brick wall when raising subsequent rounds specifically due to a lack of preparation caused by hubris. Moreover, many such founders vastly overestimate the degree to which they can overcome weaknesses in their pitch and/or business with their charisma.

Small Town Founders

This might seem paradoxical, but I’ve found that early hubris is more common in founders who come from outside of Silicon Valley than in founders based in the Bay Area. For as confident and cocky as some Silicon Valley founders come across, they tend to be very well informed about the competitive landscape and the expectations of both customers and investors. Founders from smaller cities — especially ones who get early wins — are often disproportionately lifted up by their ecosystem and can unknowingly end up with big-fish-in-small-pond syndrome before achieving any actual success.

Many years ago, I was introduced to a promising young founder from a small ecosystem whose SaaS startup had surpassed $1M ARR in their first year (this was well before the rise of AI, when doing so was really, really hard). In discussing their early traction, it was immediately obvious to me that the company had a leaky bucket caused by an incredibly high churn rate. Although top-line revenue was growing, it was driven by unsustainable marketing spend. I tried my best to encourage this founder to address the company’s churn rate and its unit economics before approaching Silicon Valley Seed VCs (as they would immediately dig into whether or not the revenue was “real”), but she would hear none of it. Bolstered by local cheerleaders, startup awards and fawning media coverage, she went out and spent nearly 9 months trying to raise a Seed round. Despite countless VCs giving her nearly-identical feedback, she was unwilling (or unable) to change course. The fundraise ultimately failed and the once promising company was acqui-hired shortly thereafter.

Solo Founders

Solo founders are particularly prone to falling victim to hubris because they often don’t have voices around them to provide critical feedback and who they are willing to listen to. I’ve seen many solo founders over the years who simply ignored feedback from employees, advisors and even investors if it didn’t reinforce their preconceived views. When hubris raises its ugly head, it’s almost impossible for someone new to pierce the veil. In contrast, a trusted cofounder can often break through all but the most stubborn cases of intransigence.

One last point before I close — in Silicon Valley, hubris doesn’t just prevent you from hearing helpful advice or critical feedback. It can close doors that you never realized were open. Pay-it-forward culture is a very real thing. But an important corollary is that in an ecosystem filled with people who genuinely want to help, immediately rejecting advice or feedback that doesn’t reinforce your previously-held beliefs sticks out like a sore thumb.

If you read my post from a few weeks ago on snakes and ladders, what I’m talking about here is access to ladders. Many of the people trying to help you can also point you to a ladder, but whether or not they do so will depend on how you react. You don’t have to agree with everyone who offers advice or opinions (in fact, you most certainly shouldn’t). But you should at least listen to what they have to say. Otherwise, you will likely never know what other help they might have been willing to offer.

Instead of pointing you towards a ladder, those individuals will simply redirect their time and efforts towards one of the thousands of other founders hungry for their help.

When it comes to startups, the cost of founder hubris is high. And over time, it also compounds.

On Resilience, Rockets and IPOs

Plenty of articles have been written about the history of SpaceX. Stories of how the company nearly failed after its first three rockets exploded. About how it almost ran out of cash during the financial crisis and Elon Musk had to borrow money to keep it afloat. About how its recent IPO minted the world’s first trillionaire.

This is not one of those stories.

Nearly 25 years ago, I arrived at Stanford as a wide-eyed Canadian kid excited to study computer science at one of the best schools in the world. I did my undergrad at Simon Fraser University, which I imagine was a pretty typical CS experience in those days (insofar as the computer science kids were mostly the weirdos in the corner who no one else talked to).

Stanford was different. Most people truly have no idea just how special a place it is. At Stanford, everyone is an uber nerd in whatever field they chose to study. Computer science was one of the larger graduate programs in those days, but there were programs and sub-programs for just about every field imaginable, from financial mathematics to international policy.

There’s no drive in the world quite like this one

Almost everyone at Stanford lives on campus, so you meet all sorts of exceptional people from different programs. I ended up with a bunch of friends who were in aeronautics and astronautics (colloquially knows as “aero-astro”). Kids who were studying to be literal rocket scientists.

Masters degree programs are generally short (1-2 years), so it wasn’t long before conversations shifted from how excited we all were to be at Stanford to what we were going to do next. As graduation approached, I noticed that many of my aero-astro friends didn’t have the same level of excitement as the rest of our group. I recall asking one of those friends about his post-Stanford plans. He shrugged his shoulders,

“There aren’t that many good jobs,” he lamented. “You can work for a bloated dinosaur like Lockheed or Northrop, try to get a government job (NASA, ESA, etc.) or go into academia. That’s about it.”

I was pretty shocked to hear him say that. These were some of the smarted people I had ever met, yet there seemed to be no path forward in their chosen field other than becoming a cog-in-the-wheel at a giant corporate. At a time when fast-growing software companies like Google, Amazon and Apple were hiring just about anyone they could, it was a sharp contrast to my own experience.

A few weeks later, I was hanging out with another aero-astro friend and again got to talking about our summer plans. She casually mentioned that she was about to join a startup. Apparently, a member of the famed PayPal mafia had a background in physics and decided to use his newfound wealth to try to start a new rocket company.

After graduation, my friend moved to LA and joined Space Exploration Technologies Corporation. That was 23 years ago.

The original SpaceX “office” was in a nondescript warehouse in El Segundo, a fairly industrial corner of west LA just north of the beach towns of Manhattan Beach, Hermosa Beach and Redondo Beach. I remember visiting it for the first time and being shocked to see a full-sized rocket being assembled just down the street from strip malls and drive-thrus.

SpaceX’s original office

At a time when Silicon Valley offices were already overflowing with perks and creature comforts, the SpaceX warehouse was an exercise in austerity. There were no foosball tables. No video games. Just computers flashing with CAD designs and piles of wires, metal sheets and manufacturing equipment. (Actually, there was one fun item in the office — Elon owned one of the first Segways and he was eager to show anyone who stopped by what the “future” of urban transportation looked like.)

Bizarrely, I once spent a Saturday afternoon driving one of these around the original Merlin engine

In contrast to typical software companies, the employees of SpaceX weren’t shipping something new every day. They didn’t get the dopamine hits from watching a new product go viral or reading the reviews about a feature they’d just released. They met up as a team each day before work, went surfing to build camaraderie (pretty cool, if you ask me) and then headed into the office to toil away. And they quietly did that for years.

The first launch attempt happened in 2006, 4 years after SpaceX was founded. The first successful launch took another 2 years. That’s 6 years from the founding of the company until the first rocket made it into orbit.

Aster Data went from founding to being acquired by Teradata in 5.5 years. DataHero was acquired 4.5 years after it was founded. It took longer for the SpaceX team to complete a single “end-to-end test” than it did for either of the startups I was a part of to complete their entire lifespan.

Now multiply that by 4.

Most people in Startupland™ can’t fathom the idea of working for a single company for more than twenty years. To be a “lifer” in tech is generally seen as a negative. The implication is that you got comfortable. You couldn’t keep up. You lost your drive and your ambition.

Silicon Valley’s culture is far more mercenary than missionary. Many engineers hop from startup to startup, collecting stock options and increasingly ludicrous salaries with little regard for what they’re actually building. The skillsets of most people in tech are so transferable and so in-demand that an incredible number move on the minute things get uncomfortable (or the moment they see a shinier opportunity). I’ve lost track of how many people I’ve met who brag about being an early employee at Uber, Pinterest or some other hotshot company, only to discover that they barely lasted a year there.

Until recently, “going to another startup” simply wasn’t possible for aero-astro engineers. For the early team at SpaceX, failure meant having to go work for a bloated corporate. Or worse, the government. There was no fallback plan.

This weekend, a number of those early SpaceX employees woke up to find themselves on the receiving end of generational wealth. Each and every one earned it in a way that few people in Startupland™ can relate to: a two decade-long grind that, for most part, was completely unglamorous. It’s the furthest thing from an overnight success that one can imagine and I am genuinely happy for each and every one of them.

At a time when AI is making it easier than ever for founders to pivot and early employees to jump ship, I’m reminded about what Silicon Valley used to be about: the weirdos in the corner quietly and unglamorously trying to change the world.

Let’s get back to that.

What If You Fire Them?

This past week, Startupland™’s corner of social media was abuzz after podcaster Greg Isenberg posted a “horror story” from his days as a founder. As the week wore on, founders around the world quote-tweeted the original post with their own tales of VC misbehavior (yes, I’m still calling it a “quote-tweet”). Things took a sharp turn Friday morning, when Cloudflare CEO and Cofounder Matthew Prince shared some of his own experiences.

…and named names.

The third anecdote he shared — about Midas List investor Vinod Khosla — set the internet ablaze.

Rather than dive into the particulars of Matthew’s experience (which plenty of netizens have already done), I want to explore a topic that we don’t often talk about when it comes to startups and fundraising: what happens when a VC likes the CEO, but doesn’t have conviction about the rest of the founding team?

When it comes to fundraising and fundraising advice, we frequently talk about founders as a single unit. We refer to the characteristics of the “founding team” and write blog posts (like this one) about frameworks that VCs use to evaluate them. But the reality is that not all founders are equal in the eyes of prospective investors.

There is the CEO, and then there is everyone else.

Now, before you rush to pitchforks, it’s important to understand that there’s logic to this thinking. For starters, the CEO is (in theory at least), the person who is ultimately responsible for all decisions. The buck stops with them. Moreover, there’s a reasonable likelihood that at least one of the cofounders pitching the VC will be gone within a few years. A recent Carta report looked at more than 22,000 VC-backed companies with 2-3 cofounders. More than 25% of them had at least one cofounder leave by year 4:

The two VC-backed companies that I was a part of — Aster Data, where I was the first employee, and DataHero, where I was the CEO — both had a cofounder leave by year 4. And many of the companies that I’ve invested in over the years have had one or more cofounders leave relatively early on.

There are wide variety of reasons why a cofounder may leave a startup, but there are several situations that occur frequently enough that VCs actively watch for them during fundraising meetings:

• Interpersonal conflicts between cofounders

• Lack of alignment (particularly to the company’s mission and values)

• Inability to take feedback / have their assumptions challenged

• Lack of growth mindset (this one is more difficult to interview for, but what investors are keeping an eye out for are signals that a cofounder might not be willing or able to evolve fast enough to keep pace with the rest of the company)

More often than not, if a prospective investors sees signs of one or more of the situations listed above, they will simply pass on the opportunity. But there is one case where some VCs will take a deeper look despite the warning signs: when they are excited about the CEO but are less infatuated with one or more of the cofounders.

Over the years, I’ve had this happen to me a number of times. After meeting an impressive CEO with an ambitious vision, strong background and clear founder-market fit, I met their cofounders and…

Believe it or not, it’s actually quite unusual to meet a founding team made up of individuals who aren’t at the same level as each other. Most high-achieving people (particularly CEOs) surround themselves by other, similarly-impressive individuals. On those rare occasions when I’m introduced to cofounders that come off as a significant step down from the CEO, it’s actually rather jarring.

My first question in such a situation is always, “did I get it wrong?” I’ll usually try to diligence the cofounder quickly (often by leveraging backchannel references) in order to figure out if my initial read was incorrect. If my suspicions are confirmed, the next question I need to answer is, “is the CEO aware that their cofounder…isn’t strong?”

Before I go any further, I want to acknowledge that this entire topic is very subjective. What I consider to be “strong” and what other people consider to be “strong” can vary wildly (which is why it’s so important when fundraising to fill your fundraising funnel with a large set of potential investors). The reality is that VC investing is far more art than science — particularly at the early stages. So while it might feel uncomfortable to think that investors are picking apart your founding team like this, understanding what’s happening (and why) can make a big difference in your outcome.

I should also point out that the stage of a company plays a big part in the ramifications of an underperforming cofounder. It is generally challenging to replace a cofounder at the early stages. On the other hand, at later stages (e.g. Series C) it’s not uncommon to see cofounders moved into different roles as experienced executives are brought in to lead specific functions. For the remainder of this post, I’ll focus on ridiculously early startups — where I spend most of my time.

In my experience, a significant “competency mismatch” between a CEO and another cofounder at the early stages usually falls into one of three categories:

1. The CEO is aware of the mismatch and has nonetheless chosen to cofound a company with this individual

2. The CEO is subconsciously aware of the mismatch but is hoping they are wrong

3. The CEO is completely oblivious to the mismatch

Let’s look at each of these scenarios:

1. The CEO is aware of the mismatch and has nonetheless chosen to cofound a company with this individual

In some cases, a strong CEO will intentionally choose to include one or more less experienced individuals as part of the founding team. For example, a senior CEO might have junior cofounders filling independent contributor roles, knowing that they will likely have to hire leadership “above them” at some point. Provided that there is transparency around this, it can be a healthy long-term situation (I’ve invested in several companies with this dynamic).

That said, a founding team with an intentionally large competency gap between the CEO and other cofounders can also be a strong negative signal. For example, it might indicate that the CEO isn’t comfortable managing people who are at or above their level or that they are unable to recruit strong cofounders. Both situations imply dynamics that are almost always fatal to a company, which is why experienced VCs will avoid such startups at all costs.

2. The CEO is subconsciously aware of the mismatch but is hoping they are wrong

In this situation, the CEO has a gut feeling that their cofounder might not be up to the task, but goes along with it anyways. In my experience, this mostly happens with first-time founders who haven’t previously dealt with the ramifications of an underperforming cofounder.

3. The CEO is completely oblivious to the mismatch

A great engineer will rarely cofound a company with a mediocre engineer. Similarly, an exceptional business cofounder will rarely cofound a company with salesperson or marketer who is mid. But what happens when cofounders have completely different backgrounds?

I’ve met multiple companies over the years that had an exceptional technical CEO but a goofball “business cofounder”. I’ve also met founding CEOs with incredible business backgrounds who didn’t realize that their technical cofounder was a dud.

So how do VCs deal with situations like the ones described above?

While I’ve never told a founder outright that they should fire their cofounders, I’ve have shared cofounder-related feedback with a handful of CEOs over the years. Many VCs are reticent to give feedback, but every once in awhile we meet a CEO who’s both objectively impressive and seems open to “out-of-the-box” feedback. In cases where I sense that the CEO either doesn’t realize the competency mismatch or perhaps does, but doesn’t want to admit it, I will occasionally offer feedback on their cofounders.

I only ever do this 1×1 and always verbally (either in person or on a call). But unlike the situation described by Matthew above, it’s never been as part of an offer to invest. Rather, it’s always been a follow-on conversation after deciding to pass on the company.

At the end of the day, the situation described by Matthew is an unusual one. But Vinod’s experience — of meeting a CEO that he was excited by but cofounders that he found to be less impressive — happens a lot more than you probably realize.

If you sense something that something’s off after a VC meets your cofounders, consider asking them about it. Here’s a great question to try:

“After meeting my cofounders, are you more or less likely to want to invest. Why?”

Regardless of the the outcome, you’ll learn something new.

How AI Helped Me Prioritize the Important-But-Not-Urgent

I am a huge fan of executive coaches. I think every founder should hire one as early in their career as they possibly can.

One of the most memorable conversations I had with an executive coach took place almost 15 years ago, back when I was the CEO of DataHero. On one of our bi-weekly calls, I was lamenting the fact that I hadn’t made meaningful progress on some personal goals that I had, when my coach paused me mid-sentence with a calm but piercing comment that I can still hear more than a decade later.

“The reason you haven’t made any progress,” she calmly observed, “is because you absolutely suck at prioritizing the important-but-not-urgent.”

Thanks Camille… 🤣

My coach at the time, Camille Preston, was generally soft spoken, but she didn’t mince words when she needed to get a point across. And on that day, she definitely made her point.

I was always very good at completing “P0” (top priority) tasks, but would often let “P1” (second tier) tasks languish. With her help, I developed strategies to ensure that I made regular progress on some of the important-but-not-urgent tasks on both my personal and professional todo lists. Strategies that have served me well to this day.

In the weeks that followed, many of the important-but-not-urgent tasks that had quietly lived on in my todo lists were completed, but others remained stubbornly untouched. I worked with Camille to unpack the reasons why, and eventually realized that I had been subconsciously performing ROI calculations on each task on my important-but-not-urgent list before deciding whether or not to “pop” it off the stack.

So what does this have to do with AI?

The emergence of AI — and agents, in particular — has completely upended the ROI calculations for many of the tasks that languished for months (or years!) on my important-but-not-urgent list. It’s made tasks that didn’t make sense to me from an opportunity cost perspective suddenly very reasonable. And I bet it can do the same for you.

One Example of How I Use AI

Let me share one example of how I’m leveraging AI to get important-but-not-urgent tasks done to make it real.

Since you’re reading this post, you’re hopefully well aware that I write a weekly blog post about startups, the business of venture capital and tech ecosystems (if not, go here right now and signup for my newsletter!). Every Wednesday morning, I distribute a new post that I’ve written in three ways:

1. I publish the original post on my website

2. I email a copy of it to all of my newsletter subscribers using Kit

3. I post a link to it on my LinkedIn page

This is certainly not the most sophisticated — or comprehensive — content distribution strategy, but it’s worked pretty well for me until now. That said, there are two additions that have been relatively high on my important-but-not-urgent list for some time yet remained untouched until recently:

1. Cross-posting links to new blog posts on Reddit

2. Repurposing old blog posts as social media content

Neither one of these tasks is particularly complex. In fact, both are well understood as low-hanging fruit for content creators who are looking to grow their audiences. So why hadn’t I done them already?

Because I was never able to justify the ROI.

Unlike a lot of content creators, I don’t generate income from my newsletter or any of the content that I create. A writer who actively monetizes their content can quite easily justify spending 1-2 hours per day strategically posting on social media or hiring a social media manager to do it for them, since it’s part of their core business, but for me the juice was never worth the squeeze. That math changed with agents.

Here’s how I now leverage agents to perform these two tasks with ease:

1. Cross-posting links to new blog posts on Reddit

One common tactic used to drive traffic to a blog is to search for active threads on social media that discuss the topic of a blog post and add a comment that links to the post. Reddit, in particular, is a very popular platform for this.

While the idea is straightforward, it’s actually very time-consuming to do it manually — particularly the process of searching for relevant threads. But AI makes it almost instantaneous.

Each time I publish a new blog post, my agent reads the post and then searches Reddit for active threads that it believes relate to the topic of the post. It returns to me a list of up to 10 posts ranked in terms of relevance, audience reach and comment quality.

For each thread, I have it come up with several draft comments that could lead readers to visit my post. Using these as inspiration, I visit each of the threads flagged by my agent, scan them briefly to make sure that they’re actually relevant, and then post a comment with the blog link.

Before AI, it easily would have taken me 2 - 3 hours per week to identify relevant threads and post comments to Reddit (which is why I never did it). With my agent’s help, it takes me about 10 minutes.

2. Repurposing old blog posts for new social media content

Another thing I’ve wanted to do for awhile is to repurpose old blog posts as social media content. At this point, I’ve got literally hundreds of posts worth of content to draw from, but it was never enough of a priority for me to justify the time it would take. Once again, AI helps me do it in minutes.

Each week, I have my agent randomly select 3 blog posts that I’ve written that are at least 18 months old. For each one, I ask it to create 3 different draft social media posts based on the content. Unlike the posts I make when I first publish the content, these ones aren’t designed to drive traffic to my website. Rather, they’re meant to elicit feedback, start conversations and (hopefully) gain a few new followers.

I specifically ask my agent to select 3 different posts so that I can choose one that feels relevant based on what’s going on in the world that week. And I ask it to create 3 distinct draft posts as inspiration, since (surprise surprise) I have zero intention of copy-pasting any of them. Instead, I choose the topic that feels the most timely to me and quickly write a social media post that’s influenced by the 3 drafts my agent created.

Once again, the entire process takes me less than 10 minutes each week (vs. several hours if I were to do it manually).

My Current Philosophy when Using AI

The examples above are just two of the tasks on my important-but-not-urgent list for which AI completely changed the ROI calculations. And I’ve got many more.

Of course, at this point you might be wondering why I bother doing any of the work myself. Why not let the agent post the comments and automate the entire process (plenty of other people have done just that)?

The answer can be found in the R ('Return’) in ROI.

First, consider the direct output of the tasks. The deluge of AI-generated comments on social media have significantly decreased their effectiveness, in no small part due to how obvious it is when a comment was written by AI. Spending 10 minutes of my time each week authoring these posts has a dramatic impact on their effectiveness (moreover, it ensures that I avoid the negative implications of my social media accounts being identified as sources of AI slop).

Second, think about the indirect benefits of performing the task manually. In the case of cross-posting to Reddit, I gain insights from reading through the threads that my agent identifies before I post links to them. In other words, the return for me is not just measured in traffic to my website, it’s in additional learnings that I didn’t previously have.

Oh…and there’s also the fact that the platforms themselves are actively working on identifying and blocking AI-generated comments:

Popping up a level, my current philosophy when it comes to leveraging AI for important-but-not-urgent tasks is to automate the time-consuming parts of the task that I don’t find value in (searching for relevant Reddit threads, brainstorming how to turn a long-form blog post into a short social media post), while selfishly keeping the parts of the tasks that I do find value in (reading relevant Reddit threads, taking the time to write the final form of a post in my voice).

Garry Tan recently reflected on this in a post about near-term opportunities for agent frameworks — distinguishing between the high-value “CEO stuff” and the things that are “not fun, not interesting, but have to be done”:

In his most recent biannual technology report, Benedict Evans described AI as “giving you infinite interns.” I think that’s one of the best descriptions I’ve heard yet (and it maps very well to how I think about agents).

The reason why so many of my important-but-not-urgent tasks languished on my todo list for so long was never because they were too hard. It was because they were too time-consuming (and from an ROI perspective, I couldn’t justify the amount of time it would take for me to do them nor the cost to hire someone else to).

But now that I have infinite interns at my disposal, I can offload the parts of each task that are “not fun, not interesting, but have to be done.” What remains is the “CEO stuff” — and a much smaller denominator for calculating ROI.

So take a look at each task on your important-but-not-urgent list and think, “if I have access to infinite interns, is that enough to finally get it done?”

The Return of Solution Selling

In the late-90s and early-2000s, a sales methodology known as “solution selling” was the dominant approach for selling B2B technology products. The approach all but disappeared in the 2010s as the rise of the internet led to customers who were far more educated and informed about the market than their predecessors.

The rise of AI is upending B2B sales once again, and suddenly what’s old is new. If you’re a founder (or sales rep) selling B2B technology products, here’s what you need to know.

A Brief History of Sales Methodologies

In 1994, Michael T. Bosworth, a former software sales exec who had spent 10 years at Xerox during its heyday in the late-70s and early-80s, published a groundbreaking sales book called Solution Selling: Creating Buyers in Difficult Selling Markets. The book described a methodology that he developed by analyzing the behaviors of Xerox’s top performing sales reps.

The key concept behind solution selling is that it focuses on selling a solution to a customer’s business problems, rather than on selling the product itself. Here is how the book described the challenge,

“When products or services are hard to describe, intangible, have long sell cycles, or are expensive, chances are they're difficult to sell. In situations like this, conventional sales techniques not only don't help, they may in fact hinder success. Solution Selling is a process to take the guesswork out of difficult-to-sell, intangible products and services.”

Solution selling quickly became the dominant approach for selling enterprise software and hardware products and remained so for nearly two decades. At Aster Data, we hired one of Silicon Valley’s top sales leaders, Mark Cranney (previously VP of Sales for Ben Horowitz’s company, Opsware), and many exceptional salespeople from companies that were famous for their enterprise sales prowess, including Opsware, Business Objects, PTC and Teradata. All of them were experts in variations of solution selling (and it’s no understatement to say that the education and experience I received working alongside so many incredible sales leaders had a profound impact on my career!)

But something fundamental changed in the early 2010s. Solution selling was based on the premise that the product(s) you were selling were too complex for most customers to understand. With the rise of the internet came a customer base that increasingly had done their research beforehand. In many cases, customers knew more about a vendor’s product than the sales reps did.

In 2012, Harvard Business Review wrote a blistering article titled The End of Solution Sales, which unpacked how a rise in customer education had rendered solution selling all but dead. At that time, a new sales methodology was already on the rise. One that anticipated customers who were far more educated about both their problem and the products available to solve them: challenger selling.

Introduced a year earlier in the book, The Challenger Sale: Taking Control of the Customer Conversation, the challenger sales methodology focuses on injecting insights into a prospective customer’s understanding of their problems and potential solutions. Rather than positioning the sales rep as the ultimate problem solver, it embraces the reality of well-informed customers while maintaining the notion that the sales rep is the “expert”:

“Instead of bludgeoning customers with endless facts and features about their company and products, Challengers approach customers with unique insights about how they can save or make money. They tailor their sales message to the customer's specific needs and objectives. Rather than acquiescing to the customer's every demand or objection, they are assertive, pushing back when necessary and taking control of the sale.”

Challenger selling quickly ascended to replace solution selling as the dominant sales methodology in B2B technology sales and has remained so for the past 15 years.

Until now.

How AI is Changing Sales

The rise of AI has upended technology sales once again, though perhaps not in the way you might expect.

If you were to listen to all of the Silicon Valley tech bros, you might be under the impression that traditional sales is altogether dead. “Agents will do all of the buying and selling,” “human sales reps are going to be extinct,” and so on. But that couldn’t be further from the truth.

A few weeks ago, I wrote about how building with AI is like mowing lawns. Founders in Silicon Valley are rushing to build and adopt AI platforms to go faster, but elsewhere in the world most people and businesses are still trying to wrap their heads around what’s happening.

“Everyone in the Bay Area is trying to build and scale as fast as they possibly can,…but elsewhere in the world, a much more basic question is being asked. From students to business owners, SMBs to enterprises, the #1 question being asked is, “what does this mean for me?” Everyone knows that AI is coming. But most have no idea what to do about it.”

While the “agentification” of sales is unquestionably underway in product categories dominated by self-service offerings, B2B sales (especially outside of Silicon Valley) remains — and will remain — predominantly human-driven. But there is a key shift that is essential for founders to understand: in stark contrast to the past decade, today many B2B customers no longer feel well-informed or confident about the options available to them.

In other words, AI has caused a significant portion of B2B buyers to effectively “devolve” to a level of understanding of and confidence about technology that is more akin to the 90s than the past decade. They still know what their business problems are, but they are no longer confident in how (or if) technology can solve them.

Which means challenger selling isn’t going to work. But solution selling will.

What Founders (and Sales Reps) Should Do

If you are a founder building a B2B product designed for anyone other than developers or power users of AI, or a sales rep selling such a product, order a copy of Solution Selling (or its 2003 follow-up, The New Solution Selling) and read it front-to-back. The examples in both books are extremely dated at this point — not to mention many of the cultural references — but if you focus on the underlying concepts of understanding a prospective customer’s business problems and how to position your offering as a solution to those problems, it will quickly become clear why this approach makes sense in an age of AI.

(As a side note, I have a feeling that if we one day look back at the effectiveness of sales organizations in these early days of AI, we will find that the many of the top sales execs were older ones — reps who originally learned solution selling and were able to quickly and seamlessly switch back to that approach).

Bottom line: there is a bifurcation in sales methodologies underway. If you are building and selling a (non self-service) product for developers or other AI power users, then you should likely continue with challenger selling as your core methodology. But if you are selling to buyers who are less confident and/or knowledgable about AI, using solution selling will likely enable you to close sales at a rate your competitors can’t match.

Time to switch gears

Stop with the AI Slop

A few weeks ago, I travelled to Saskatoon, Saskatchewan to give the opening keynote for Uniting the Prairies, a conference that brings together founders, investors and ecosystem supporters from across Canada’s prairie provinces. Both the conference and my hosts were fantastic and my talk seemed well received, but I was completely unprepared for what happened the next day.

The morning after my talk, as I sat bleary-eyed in an Uber in the way that only a redeye can leave you, I picked up my phone to see hundreds of notifications from LinkedIn.

“X mentioned you in a post”

“X commented on Y’s post that mentioned you”

“X reacted to Y’s post that mentioned you”

My initial excitement quickly gave way to confusion as I scrolled through the pages of notifications. All of the posts I was mentioned in — literally dozens of them — were virtually identical.

At first, I wondered if it might be some form of spam. But why on earth would anyone spam me over a conference talk? And then it hit me.

Every LinkedIn post about my talk had been written by AI.

Not a few of them. Not most of them. Every. Single. One.

At this point, it’s obvious to anyone with half a brain when a social media post has been generated by AI. The bullet lists denoted by emojis no human ever uses. The wistful tone that reads as though the author was trying their absolute hardest to ghost write for a Morgan Freeman-narrated documentary (or, more aptly, a circa 2006 Yelp review). The hashtags upon hashtags upon hashtags.

Each post was nearly a page long. “Attention-grabbing” intros gave way to “reviews” of the various speakers and activities that took place at the conference. Here are two examples:

Fun fact: I have never used the phrase “play their own game” in any talk, podcast or blog post — it was a phrase the conference organizers added to the online agenda for my keynote.

After a while, my eyes glazed over. Eventually, I stopped reading and responding. Reading through so many nearly-identical posts left me wondering: what’s the point?

I don’t mean that as an existential “what is the meaning of life?” sort of question. But, rather, why go through the time and effort of creating a post like this to begin with?

In contrast to the comic above, none of these posts were created from a single bullet point. In each case, the author would have needed to build and refine their prompt (in some cases, it was clear that the post simply pulled details from the conference website and made the rest up, but many appeared to include actual insights from the author’s experience at the conference). After that, they would need to iterate and refine the results in order to create the final post.

At this point of the AI hype cycle, a lot of us have simply accepted that “AI can do things” better/faster/cheaper than we can, without really thinking about whether or not that’s actually true. Social media posting is a great case study.

For years, social media influencers taught us that there was a “right way” to write content / build online audiences / drive traffic. AI offered the promise of getting outlier results without having to go through the hassle of actually learning how to do it ourselves. But here’s the thing: the “attention-grabbing” strategies that worked on social media two years ago were effective specifically because the posts were outliers in their content and/or structure. When everyone uses AI that’s been trained on the same content marketing strategies, the resulting output is not an outlier. Because the strategies no longer work.

AI might indeed make it faster or cheaper to post on social media, but it doesn’t actually do it better (at least, not if your metric for better is some form of “gets a human to pay attention”). In other words, relying on AI to generate social media posts is now likely to result in a post that under-performs when it comes to the KPI that matters.

This dynamic is actually nothing new — in fact, it’s very well understood in the world of finance. It’s referred to as alpha decay.

In finance, alpha refers to the ability of a strategy to outperform the market (VCs spend a lot of time in search of alpha). Over time, outperforming strategies become more widely known and practiced, leading their effectiveness to diminish (alpha decay). “Attention-grabbing” social media strategies worked because they were outliers — they had alpha — but now that AI defaults to using such approaches when crafting posts, their effectiveness has all but disappeared.

I suspect that we’re going to see this dynamic play out across a variety of AI-related activities in the very near future. As more people chase the efficiency gains offered by AI, the output will converge and the alpha will rapidly decline.

Which brings me back to my earlier question: what’s the point?

Consider the following thought exercise based on my anecdote above:

• Let’s assume that it takes an average person 10 minutes to write an effective LinkedIn post about a tech conference by hand

• Let’s further assume that to create one with AI takes 5 minutes

If the human-authored post drives 100 interactions (because it is still unique in some meaningful way) while the AI-authored one drives only 50, is it worth it?

What if I told you the 50 reactions to the AI-authored post are mostly bots and people reacting out of obligation (e.g. you’re my friend so I’m going to like it no matter what)?

If we presume that a similar alpha decay is taking place across a wide variety of tasks as we increase our use of AI, then I would posit the following:

Before you rush to do the thing with AI, think about whether or not it’s worth doing at all. What output are you expecting/hoping for? Is there alpha in doing the task the way you’re doing it today? If that alpha were to disappear, is it worth doing it at all?

AI might be cheaper/faster, but if it’s not actually better (and you’re not willing to take the time to do the thing by hand) then…maybe just don’t do it?

Why Building with AI is Like Mowing Lawns

My first entrepreneurial endeavor (lemonade stands notwithstanding) was a lawn care “business” I started with a friend back when we were in middle school. We each had a lawnmower — okay, technically speaking they were our parents’ lawnmowers — and we went around the neighborhood looking for houses with long grass. We would knock on each such door and ask the homeowners if they would like us to mow their lawn.

Before long, we had a list of regular customers whose lawns we would cut every week or two. We did this for several seasons (until we were old enough to get “real” jobs). At our peak, we were each making a couple hundred dollars per week — which was a ton of money for a middle school kid in the early 90s!

I spent a lot of money on video games 🎮

Fast forward to today, and I think AI is about to provide a similar opportunity for intrepid young entrepreneurs. This time though, it’s not lawnmowers or power washers or painting supplies that will provide the leverage with which to build a business from scratch. It’s the knowledge of how to build with AI.

“Would you like us to install your AI?”

There are a variety of opinions when it comes to where the big opportunities for AI lie. And your answer very much depends on your perspective.

In Silicon Valley, it’s all about building scalable infrastructure. “Pickaxes and shovels,” as the saying goes. Everyone in the Bay Area is trying to build and scale as fast as they possibly can, in the hope that their platform will be one of the winners.

But elsewhere in the world, a much more basic question is being asked. From students to business owners, SMBs to enterprises, the #1 question being asked is, “what does this mean for me?” Everyone knows that AI is coming. But most have no idea what to do about it.

It’s as if millions of homeowners are staring out of their windows, watching the grass grow longer and longer but without any clue what to do about it.

While some reports claim that SMB adoption of AI is skyrocketing, the Marks Group, a consultancy that specializes in small businesses, sees a different reality,

“They’re playing with chatbots like ChatGPT, Gemini, Copilot, Claude and Grok. They’re using these platforms for research. They’re getting help crafting emails.

…[but] core adoption — where AI agents are being used to reconcile accounts, place orders, send emails, converse with customers, apply cash, analyze transactions and produce quotes, estimates and proposals automatically based on historical transactions — is nowhere near happening at small businesses.”

And it’s not just small business owners that are struggling to adopt AI. a16z recently released a report on enterprise adoption of AI, which found that even the world’s largest companies are barely scratching the surface when it comes to AI.

Moreover, the vast majority of AI adoption thus far has been in and around software development.

So what does this have to do with lawn care?

Right now, there is a massive opportunity for founders who are willing to simply knock on doors and metaphorically ask, “do you need your lawn cut?”

Marvin Liao recently described this opportunity in terms of age:

“…there is an arbitrage now between the generation above us, which don’t know how to use all of the things that the 17-year-olds know how to use.

If you were to ask me the best way to make money in the world today, it is to take advantage of the fact that there is a large subsection of the population that not only have all the money but, secondly, don’t know how to do a lot of things that most young people already know how to do. And if you can leverage that correctly you can actually make quite a lot of money.”

There are an incredible number of young people who have or are quickly developing the ability to build with AI. At the other end of the spectrum are countless business owners, managers, and individuals who have real problems to be solved, budget to solve those problems but for whatever reason (time, interest, ability, etc.) aren’t in a position to figure out how to do it themselves.

Silicon Valley would have you believe that either (a) every human is going to become a prompt engineer, or (b) there will soon be a permanent underclass populated exclusively by those who aren’t AI native. Both of these are very stereotypical Silicon Valley viewpoints (remember when everyone was going to learn how to write SQL..?).

In fact, the most likely outcome is that a large number of astute entrepreneurs will make considerable amounts of money by servicing the many businesses and individuals who aren’t AI native but have budget to solve their problems. These opportunities won’t be as sexy as the latest and greatest uber-for-fintech-for-agents platform, but I promise there is real money to be made pursuing them.

A lot of real money.

But capturing this value will require a skill that many technical founders struggle with: the ability (and willingness) to unflinchingly listen to prospective customers and build for their needs. The path to success for these businesses will have far more in common with building a consulting company than a traditional product startup:

1. Market Research — Reach out to potential clients and interview them about their biggest challenges and what specific problems they have budget to solve.

2. Initial Engagement — After landing on a problem area, build an initial, custom solution for one or more clients (while making sure you own the resulting IP).

3. Attempt to Resell — Reach out to additional, similar prospects and see if they have the same problem. If so, attempt to service them with the previously-created solution (or as much of it as can be reused).

4. Productize — After completing multiple engagements with the same general solution, productize your work and bring it to market at scale.

While this approach sounds easy enough, it’s actually quite hard for many founders. In recent months, I’ve met multiple founding teams who, despite having credible prospects tell them very directly what their biggest problem was, chose instead to build something different in the “hope” of capturing a market.

I think that a big reason for this is that, as an industry, we’ve spent the better part of the past twenty years trivializing consulting-first startups as “lifestyle businesses” whilst idolizing the potential of product-first startups. But AI will flip that (at least, when it comes to how vertical solutions get built).

So if you’re a founder, a student, or anyone else who’s holding an AI “lawnmower” and trying to figure out what to do next…try knocking on your neighbor’s door.

(You can also ring the doorbell)

What’s Going On With Accelerators?

I’ve written a lot lately about the ongoing bifurcation of venture capital and its implications for fundraising (both in my quarterly updates and in dedicated posts, like this one on early-stage investing).

One prediction I made last year was that we would start to see more early-stage investors lean in to the “hands-on” styles of investing that were more common in years past. As megafunds ramped up their early-stage activity, many Seed VCs would be crowded out. They would in turn head upstream to the “safety” of Pre-Seed. The increased competition at Pre-Seed would force investors to find new ways to differentiate themselves in the eyes of both founders and LPs.

And that would lead to more accelerators,

“…we’re seeing a resurgence of both small, dedicated accelerators and offerings from Seed-specialist VCs…it feels like the pendulum is swinging solidly back from the “hands-off” investing style of the ZIRP era to the more “hands-on” style of years past. At a time when AI is making it cheaper than ever to get a company off the ground, I think we’re going to quickly see a new level of competition amongst credible accelerators (and between accelerators and pre-seed VCs).”

Sure enough, the accelerator landscape has gotten a lot more crowded since I wrote that post.

Since the beginning of the year, megafund a16z significantly ramped up their speedrun team (I might have done reference calls for some people they were looking to hire 👀). They followed that up by launching a new fellowship program called “alpha” a few weeks ago.

Speaking of alpha, the big dog of accelerators, YC, didn’t sit long with its earlier assertion that, “…the total number of startups going through the program each year will hold steady at about 500…” The recently completed W26 batch had nearly 200 companies (i.e. they’re currently on pace to invest in 800 startups in 2026).

And that’s just the start. Here is some of the other activity that took place across the accelerator landscape during the first quarter of 2026:

• London-founded fellowship program Entrepreneurs First completed its move to San Francisco and unveiled a fresh $200M fund

• Accelerator upstart Neo announced a new Residency program for college students

• Montreal-based AI research institute Mila launched a new venture-building program for AI research scientists as part of a $100M “venture scientist fund” announced earlier in the year

• South Park Commons shared its plans to raise a new $500M fund for its self-proclaimed “anti-accelerator”

Taken together, it might seem like there’s now an overabundance of programs for founders to choose from. But if you look closer, what we’re seeing is actually a clustering around two very specific approaches to hands-on investing:

1. Accelerators as the New MBA

2. Fellowships as the New Montessori

Let’s dig deeper into each of these trends.

Accelerators as the New MBA

In the early days of accelerators, programs like YC, Techstars and 500 Startups didn’t have nearly the prestige of today’s industry leaders. In fact, it was quite the opposite. Amongst many founders and investors in the startup world, accelerators were seen as something of a crutch. They were the thing you went to if you couldn’t figure it out on your own.

Fast-forward 20 years and the perception is very different. Not only are accelerators broadly accepted as a reasonable path for first-time founders to take, but having simply attended a top accelerator is seen by many as a mark of credibility and prestige. Sound familiar?

“You got into Harvard…you must be smart!”

“You got into YC…you must be smart!”

Last year, David Crow wrote about the increasing similarities between top accelerators and universities. He noted that,

“In the past, ambitious graduates invested in themselves by going to grad school. They spent $100,000 on an MBA, law degree, or medical program as their path to impact.

Today, ambitious people might choose YC or Speedrun instead…

YC and Speedrun are not just accelerators; they’re the new professional schools of venture.”

I’ll take it a step further: not only are ambitious individuals increasingly looking at top accelerators as a credible path to advance their careers, accelerators are increasingly selecting founders in ways that look a lot like how elite MBAs choose students.

And I’m not the only one.

I recently caught up with a friend who spent many years as a VC at one of Silicon Valley’s top-tier funds (he also happens to have an MBA from a prominent business school). In discussing the evolution of the early-stage landscape, he suggested that top accelerators have very intentionally moved towards a model for selecting founders that mirrors how top MBA programs select students:

“At this point, [top accelerators] know the “shape” of founders that Tier 1 VCs like to invest in. The schools they went to, the companies on their resume, the traction points that matter. The things that get an IC* comfortable investing in a company that maybe hasn’t done anything yet.

It’s the same way MBA programs cater to top employers. What undergrad did the student go to? Where did they intern? What test scores do they need if they came from a lesser-known school? They’re trying to maximize the chances that an incoming student will land a job with a name brand employer, regardless of what they actually do during business school.”

* investment committee

If you read my recent post on Hunters vs. Farmers, you might be getting a sense of deja vu. That’s because what we’re talking about here is the approach that “hunters” typically take, but within the context of a segment of venture that we historically think of as “farmers”:

“Early-stage hunters focus on pedigree and traction as their primary signals. Things like:

• Graduating from a top school or program (Stanford, MIT, Waterloo, IIT Bombay, Thiel Fellowship, etc.)

• Early employees that left “hot” companies

• Repeat founders

• Hot sectors

• Virality / significant early traction

They’re generally betting on the correlation between pedigree and outcome (or, at least, pedigree and quick markups).”

This is exactly what elite MBA programs do. They bet on the correlation between pedigree and outcome, where outcome is “gets hired by a top-tier employer”. Today’s top accelerators are increasingly converging on a similar model. And you can see it in their marketing,

“Want to maximize your chances of landing a job with [top employer]? Apply to Harvard!”

“Want to maximize your chances of raising a round from [top VC]? Apply to YC!”

This certainly isn’t a bad approach — for either the accelerators or the founders.

That said, it’s worth noting that what’s happening at the top of the accelerator pyramid right now is very much influenced by a considerable imbalance in supply and demand. More and more qualified founders are looking for the “cheat codes” that come with the brand recognition and alumni networks of top accelerators. Yet there are very few programs that credibly deliver consistent outcomes along these dimensions (particularly in the aftermath of 500 Startups and Techstars both effectively failing). With so many qualified startups and so few spaces available in each program, founder pedigree naturally becomes a more prominent factor in selection.

Which means that a significant number of ambitious founders — especially founders outside of California and those from schools, companies and backgrounds that don’t neatly fit the typical Silicon Valley mold — are struggling to gain acceptance into these elite programs.

When the supply-demand curve is so imbalanced that an entire country doesn’t make the cut

So why aren’t we seeing more “elite MBA programs” emerge if the supply-demand curve is so imbalanced?

Despite the incredible demand for top tier Silicon Valley-based accelerators, only two platforms founded in the past decade have found success: Neo starting in 2017 and speedrun (from a16z) in 2023.

It turns out that creating a full-fledged accelerator platform from scratch is hard. It takes a lot of resources, investors who are experienced evaluating startups with virtually no traction, and an incredible number of high-quality, properly incentivized mentors. Creating a high-quality accelerator is, in fact, really, really hard.

But it is doable. Not only that, with so much latent opportunity — especially when it comes to startups outside of California — more elite Silicon Valley-based platforms are undoubtedly going to emerge. It’s just a question of when.

In the meantime, the majority of early-stage investors that have started rolling up their sleeves are taking a different approach. One that focuses almost entirely on the potential of individual founders while forgoing much of the complexity of a full-blown accelerator…

Fellowships as the New Montessori

If accelerators like YC and speedrun are the new MBA, then fellowship programs like South Park Commons, HF0 and Entepreneurs First are the new Montessori school.

If you’re unfamiliar with the term “Montessori”, it is an approach to early childhood education that focuses on encouraging children’s natural interests rather than providing formal, structured education. Montessori programs are designed around student-directed work, with a particular emphasis on uninterrupted work periods. The approach is based on the idea that children are naturally eager for knowledge and the primary role of teachers is to guide and mentor them.

At a high level, Montessori schools take a group of highly-motivated individuals and place them in a room with a handful of experienced, light-touch mentors in the hope of creating magic.

A Montessori “hacker house”

Which brings us to fellowships.

Fellowship programs invest in aspiring founders based primarily on their experience and pedigrees. These individuals are placed into a cohort and participate in activities designed to guide them towards founding high-potential companies (with a particular emphasis on ideation and cofounder matching). In other words, they take a group of highly-motivated individuals and place them in a room with a handful of experienced, light-touch mentors in the hope of creating magic.

Over the past few years, the number of fellowship programs has exploded. Not only are there an increasing number of standalone platforms (like South Park Commons, HF0 and Entepreneurs First), but many existing VCs have launched fellowship offerings as a means to increase their access to high-potential founders at the earliest stages. Some examples include a16z’s “alpha” fellowship (mentioned above), Conviction Partners’ “Embed” program, and Afore Capital’s “Founder in Residency” program.

Earlier, I alluded to the fact that fellowship programs forgo much of the complexity of a full-blown accelerator. Let me expand on that point — as it’s key to understanding why so many fellowship programs are emerging.

Both fellowship programs and Montessori schools are rooted in the notion that individual participants are highly-motivated and eager for knowledge. The corollary of that belief is that mentors need not be heavy-handed (either in their depth of programming or the help they provide). Montessori programs don’t so much teach children as they guide them on where to look for their own answers. Similarly, fellowship programs don’t focus on the type of “startup 101” programming that accelerators historically delivered. Instead, they provide frameworks for aspiring founders to search for answers while making introductions and connections to help them progress.

Guess what? That approach means fewer mentors, less time and effort developing programming, and significantly lower costs.

The simplest form of a fellowship offering is a VC partner providing regular mentorship and occasional connections to an aspiring founder. Which is exactly what many VCs have done for years through entrepreneur-in-residence (EIR) programs. From the perspective of traditional VCs, fellowship programs are little more than the cohort-ization (is that a word?) of something they were already doing.

Want to have your mind blown even further? Y Combinator — the world’s foremost accelerator — actually started out more like a fellowship program. Here is how Paul Graham originally described YC (then referred to as the “Summer Founders Program”):

The Summer Founders Program preserves many features of a conventional summer job. You have to move here (Cambridge) for the summer, as with a regular summer job. We give you enough money to live on for a summer, as with a regular summer job. You get to work on real problems, as you would in a good summer job. But instead of working for an existing company, you'll be working for your own; instead showing up at some office building at 9 AM, you can work when and where you like; and instead of salary, the money you get will be seed funding.

…

We'll have some smart people who are willing to talk over your plans with you, and suggest pitfalls and new ideas. We may also have connections to companies you'd like to do deals with. But how much you want to take advantage of our advice and connections is up to you.

We'll organize dinner once a week for all the Summer Founders, so you can meet one another and compare notes. We'll try to get some expert in technology, business, or law to speak at each dinner. But beyond that we'll be hands-off.

The first batch of YC’s “fellowship program”

To be clear, today’s top-tier fellowship programs provide significantly more that just a la carte mentoring and connections. They are full-blown platforms with programming and mentorship strategies that have been developed and iterated over many years. But the low “entry price” of starting a basic fellowship program, combined with the dramatic supply and demand imbalance I alluded to earlier (more and more founders looking for “cheat codes” but relatively few credible accelerators), is driving what I believe to be just the start of a wave of new fellowship offerings.

To recap:

1. The bifurcation of venture capital is forcing many VCs to invest earlier-and-earlier

2. Increased competition at the Pre-Seed stage is driving those investors to find new ways to differentiate themselves — which, for many, involves getting more hands-on with founders

3. Creating a new accelerator is difficult and prohibitively expensive for most VCs (a16z can afford to throw a ton of money at creating a new accelerator, but the funds who are moving upstream specifically because they can’t afford to compete against a16z most certainly cannot)

4. However, “systematizing” mentorship and/or scaling an existing EIR program is much more approachable for most VCs (and easy to justify from an ROI standpoint)

Bottom line: expect to see more and more fellowship programs emerge in the coming months (particularly from mid-sized Seed funds that are trying to figure out how to effectively compete at Pre-Seed).

On Terms and Terminology

Before I wrap things up, I want to share two final thoughts on terms and terminology:

On Terms

Many accelerators and fellowships are increasingly trumpeting large numbers when it comes to their investment amount. It’s not uncommon to see programs seemingly offering $1M of investment to startups.

But don’t believe everything you read.

The vast majority of accelerators and fellowships make either milestone-based or follow-on based investments. That means that (a) you might not receive the full amount, and (b) if you do, you may end up giving away a much higher portion of your company than you realized.

Consider the following examples:

• Y Combinator

  • Top-line number: $500K

  • Actual initial investment: $125K for 7%

  • Follow-on investment: $375K (MFN)

• a16z Speedrun

  • Top-line number: $1M

  • Actual initial investment: $500K for 10%

  • Follow-on investment: $500K (contingent on follow-on funding)

• Entrepreneurs First (US)

  • Top-line number: $250K

  • Actual initial investment: $125K for 8%

  • Follow-on investment: $125K (MFN)

• South Park Commons

  • Top-line number: $1M

  • Actual initial investment: $400K for 7%

  • Follow-on investment: $600K (contingent on follow-on funding)

Strictly speaking, there’s nothing wrong with this approach (in fact, it very much represents a standardization of the traditional venture capital strategy of “investing early and doubling down on winners”). But as a founder, it’s important that you read the fine print (here is a somewhat dated post on accelerator terms that I wrote a few years ago).

On Terminology

I’m not going dive into the etymology of (or debate over) terms related to accelerators / incubators / startup schools / etc., but I do think it’s important to share one point as it relates to fellowships (as they’re relatively new on the startup landscape and the language is still in flux):

The term “residency” is often used interchangeably with “fellowship” (e.g. Neo refers to its fellowship program as “Neo Residency”). However, it is also increasingly being used to differentiate between full-blown fellowship programs and lighter-touch coworking offerings that standalone fellowship programs are using to attract potential candidates (e.g. the Entrepreneurs First Residency and the South Park Commons Residency).

If you are considering a fellowship program, be sure to pay attention to the terminology and make sure you understand exactly what you’re applying to (lest you mistake one for the other).

Snakes and Ladders

I spend a lot of time traveling back and forth between San Francisco and other cities across North America and the UK.

Every time I leave the Bay Area, I find that my internal clock naturally slows down, as it adjusts to the pace of life in whatever city I’m visiting. Conversely, the moment my flight lands at SFO, it ramps back up. My good friend Marvin Liao wrote about this last year (referencing a short but insightful post from Sriram Krishnan the year prior).

This particular phenomenon isn’t new to anyone in tech. Silicon Valley has always operated at a higher velocity than other startup ecosystems (similar to how New York has a different gear than comparable cities when it comes to other forms of white collar work). But over the past 18 months, something has been happening.

Silicon Valley has been speeding up.

And most people outside of the Bay Area — including founders, ecosystem supporters and even many VCs — have no clue just how wide the chasm has become.

The Resurgence of Silicon Valley

Over the past year, there have been a number of signals hinting at Silicon Valley’s resurgence. For example, the PitchBook-NVCA Venture Monitor, which provides a quarterly snapshot of the US venture landscape, has shown a steady increase in the percentage of US VC investment going to companies based in the San Francisco Bay Area (on both a dollar and deal count basis):

Source: PitchBook-NVCA Venture Monitor, Q1 2023 - Q1 2026

A report recently published by Silicon Valley Bank showed that, since 2022, the rate of VC-backed company formation has plummeted in every major city in America, except for San Francisco…where new company formation has skyrocketed:

Meanwhile, rent in San Francisco is increasing at the highest rate in the US and is on pace to surpass NYC for one- and two-bedroom units.

“In San Francisco, rents are surging, with one-bedrooms climbing 16.1% and two-bedrooms up 19% year-over-year, as a return-to-office push and optimism around AI-driven hiring pull high-income workers back into an already supply-constrained market.”

Taken alone — or even together — these signals don’t necessarily indicate a shift in “how” Silicon Valley is operating as an ecosystem. After all, San Francisco has been a gold rush town since the 1800s. People in tech rushed to the Bay Area during the dotcom boom in the late 90s and then again as the recovery from the 2008 financial crisis accelerated in the early 2010s. But this time is different.

Each time I’ve returned to the Bay over the past 18 months, it’s seemed faster than when I left. And each time I travelled to another city, the slowdown felt more pronounced. The contrast more jarring. It was as if Silicon Valley was accelerating and evolving in near real-time, while other ecosystems remained static.

What’s Going On?

Last year, tech media started publishing articles about Silicon Valley embracing “996”. The implication of these articles was that the acceleration happening in tech could simply and easily be attributed to startup employees working longer hours. But that explanation rang hollow to me.

While the idea of working 996 (9AM to 9PM, 6 days/week) seems shocking to many people, it’s actually nothing new for Silicon Valley. Back when I worked in startups, a 12-hour workday was pretty normal (I actually have a draft blog post on the topic which I have yet to get around to finishing…). I personally think the media reaction has a lot more to do with how many visitors to Startupland™ during the ZIRP era didn’t actually work that hard, but that’s a topic for another day.

From where I sat, there had to be something else going on.

It took a conversation that I had with Charles Hudson last fall — when I was brainstorming for an experiment that would become Game On — to provide the lightbulb moment. We were discussing the fact that founders seemed to be executing faster in San Francisco than they had been before. Charles had observed something similar and had invited several of his portfolio founders from outside of California to visit for “field trips” (short visits to San Francisco during which they would work out of the Precursor Ventures office).

Charles shared with me a story about one such founder, who was working at the Precursor office on a Friday afternoon when he ran into a bug with an API that he was building on top of (the anecdote is paraphrased as follows):

Founder: “I just ran into a bug with X, so I’m blocked.”

Charles: “What are you going to do about it?”

Founder: “I filed a ticket.”

Charles: “And then?”

Founder: “And then what…?”

Charles: “What else did you do?”

A‍t this point, the founder looked dumbfounded.

Charles: “Are you really going to just file a ticket and call it a day?”

Founder: “What else am I supposed to do?”

Charles: “How about I connect you with the CEO?” ‍

A few minutes later, the founder was describing the bug to the company’s CEO. Within an hour, it was fixed.

Snakes and Ladders

I’ve been thinking about that anecdote — any many similar ones that I’ve heard since — and I believe that the best metaphor for what’s going on in Silicon Valley right now is the board game snakes and ladders.

Founders in SF have always benefited from high-value networks, but over the past couple of years they’ve become far more aggressive in how they leverage them. Have a bug? Reach out to the CEO. Want early access to the next release? Get your VC to connect you to the CEO. Trying to get into that invite only party with the who’s who of your sector? Reach out to the party organizer (aka the CEO).

These days, founders up and down Silicon Valley unapologetically search for and leverage “ladders” in order to skip steps. They’ve become far more aggressive at this than I’ve ever seen before — going into social debt to a degree that would have been considered inappropriate (and, frankly, cringe-worthy) only a few years ago. But these days, it’s increasingly perceived as a socially-acceptable form of ambition.

These founders are sprinting and scrambling as fast as they possibly can up each and every ladder they find. Occasionally, they screw up and slide back down a “snake”. But no one in the valley bats an eyelash. There are no negative social implications. Meanwhile, founders everywhere else in the world are dutifully running back and forth along the left-to-right game squares. Some of them are trying to go faster (aka 996), but all of them continue to follow the linear, back-and-forth path.

Have you ever heard of anyone winning a game of snakes and ladders without climbing a ladder? Me neither…

One of the experiments we performed during the “Game On” program last January involved introducing the 35 visiting Canadian founders to some unexpected ladders. On day two of the program, we had Google’s Global Founder Advocate, John Alioto, join us. He sat down in front of our visiting founders with a simple offer,

“Tell me anything you want access to anywhere in Google, and I’ll make it happen.”

One of the founders in the room raised their hand and mentioned that they had been on a waiting list for a pre-release product for 3 months. John smiled, typed a few things into his computer, and several moments later declared that they had access to it. Everyone’s eyes widened.

Over the course of the morning, he repeated similar unlocks for many of the founders in the room. In mere moments, these founders climbed ladders that they had been dutifully marching towards for weeks or months. John unlocked doors that were previously closed to them, with no idea as to when (or if) they might be opened.

That’s a daily occurrence for Silicon Valley’s highest-velocity founders.

The Fog of War

Popping up a level, it’s important to address the topic of information asymmetry in the current startup landscape.

Whether you are a founder, an investor or an ecosystem supporter, it’s essential that you understand that there has been a significant reduction in the information flow emanating from Silicon Valley. The “fog of war” between the Bay Area and the rest of the world has gotten thicker. “Snake and ladders” is but a single example of the many changes that have taken place in how San Francisco startups operate that aren’t yet apparent to the outside world.

Historically, information and innovation flowed fairly reliable out of Silicon Valley. Each time a new idea would arise — whether technical, business process, or otherwise — it would first disperse throughout local Bay Area networks. A month or two later, some number of people would share it with the wider world through blog posts, Twitter threads and videos. Within a quarter or two, the majority of the world’s tech ecosystems were up-to-speed.

That’s not happening anymore.

Technological innovations are still widely and reliably distributed online (you need only look at the speed with which OpenClaw took the world by storm to be convinced of that). But when it comes to business processes, go-to-market strategies, best practices and other innovations, very little information is leaving the Bay Area these days.

There are three reasons for this:

1. The intensity of AI-driven competition has resulted in many people deprioritizing non-critical content creation

2. An increasing percentage of the content that does get created is useless, AI-generated slop

3. Within Silicon Valley, information sharing has overwhelmingly shifted from public forums to private group chats and closed events

When taken together, the result is that founders, investors and ecosystem builders outside of Silicon Valley are increasingly out-of-touch with what’s happening on the ground in San Francisco for no other reason than that no one is telling them.

In the past six months, I’ve seen numerous founding teams from outside of Silicon Valley visit the Bay Area, only to discover that their knowledge — about technology, competition, customer interest, and more — was significantly out of date. Despite having every belief that they were operating at the bleeding edge of their industry, they discovered that they were, in fact, very far behind.

I’m not sure when (or if) the flow of information from Silicon Valley to the outside world will return to it’s previous rate. For now, I can simply offer this: if your goal is to create a globally competitive tech company, you should presume that what you think you know about what’s happening Silicon Valley is significantly outdated. At worst, it’s flat-out wrong.

The solution? Go on a field trip. Get on a plane, spend a few weeks in San Francisco during the summer. And see for yourself.

For founders building outside of Silicon Valley, it’s the new playbook.

Go Touch Grass

Last week, I wrote about a question that is increasingly top-of-mind for many residents of Startupland™: is agentic programming addictive?

I’ve received as many responses to my post asserting that, “this is normal…if you’re a founder you should have some level of addiction…” as I did emails expressing some form of, “thank you for writing this…it describes exactly how I’ve been feeling as of late,” (which to me is a pretty good indication that I’m on to something).

As someone who’s founded a number of startups over the years, I have some experience when it comes to late night coding binges. I personally feel like there are some real differences at play now that AI is in the mix. Of course, it could just be that I’m a boomer past my prime…

I will say this: as a parent, I find myself increasingly motivated to be thoughtful and intentional when it comes to our current AI-driven obsession. The question of “how much screen time is appropriate?” existed long before I was born. With the addition of AI — and its productive and addictive possibilities — that question seems even more prudent.

For both adults and kids alike, I think that it’s essential to maintain a connection to activities that are not impacted by AI. That’s why I concluded my post on the potential addictiveness of agentic programming with the following suggestion:

“…taking time away from your agents is important not only for your general health and well-being, but because our ability to think, create and invent depends on it.

So take a break. Make a point each day to step out of the AI- and social media-driven dopamine loops and touch grass. Not only is it okay to go outside, it’s essential.”

I thought that this week I would share some of the small but meaningful ways that my family and I “slow things down” in order to take a break from the dopamine-driven cycles of Startupland™:

1. No Technology at the Dinner Table

I’m a big believer in family dinners. It’s not always easy to pull off, but establishing a daily or weekly ritual with family or friends provides time for everyone to catch up, share stories and build connection.

One change we made in the Neumann household (that was harder than it seemed when we started) was to ban technology at the dinner table. That means no cell phones, no Apple Watches, and no questions to “Google”, “Siri” or “Alexa” (we actually unplug our Google Home before eating dinner because we are so used to interacting with it).

Remember the days when someone had a question and you actually discussed and debated the answer…? Turns out, you can still do that.

2. Listening to Vinyl Records

The resurgence of vinyl has been on the upswing for awhile. But that was mostly for audiophiles who couldn’t shut up about how much better their sound system was than yours. We jumped on the vinyl bandwagon for an entirely different reason: in order to stop our kids from skipping around when listening to music.

We noticed that, at a young age, our kids often struggled to listen to entire songs, much less albums. In some cases they would skip ahead. In others, they would restart a song multiple times before it finished. This isn’t anything particularly new, but it’s a lot more prevalent with digital music. As our kids got older, the frequency with which the soundtrack of our lives became measured in 15 second increments became unbearable.

Our solution: to buy a record player and give everyone in the family “credits” to buy their favorite albums.

Now, the only music we have on during dinner comes from a record player. We take turns picking music and, once someone puts on a particular record, it cannot be changed until it’s done. Not only has it given our children a better appreciation for music (they’ve had to learn how to handle and change vinyl records), everyone has gained/regained an appreciation for albums as a distinct work of art.

(Bonus points: there are no vinyl “brain rot” albums 😉).

3. Gardening

Another hobby that we’ve increased the amount of family time we spend on is gardening. As a kid, I spend countless hours learning to garden with my grandfather, who dedicated much of his retirement to meticulously tending one of the most fantastic vegetable gardens you could possibly imagine (the rest of his time was focused on fly fishing).

In today’s era of farm-to-table groceries, it’s hard to justify economically the time and effort that goes into growing vegetables in an urban setting, but the practice itself is both calming and centering.

And AI isn’t going to make those cherry tomatoes grow any faster.

4. Cooking

It’s no secret that I love to cook. In fact, it’s one of the things that recharges me. I cook multiple times each week, whether I’m by myself, with my family or when hosting a dinner party.

I’ve long-since learned to not try to multitask whilst cooking (no better way to burn dinner than by accidentally falling down an AI rabbit hole). Moreover, it’s a skill that very much can only be perfected through practice. The internet might give you the perfect recipe for pan-seared duck breast, but chances are you won’t get it right the first time. Or the 10th…

5. Board Game Night

Video games are fun, but it’s hard to beat the energy and laughter that comes from playing board games.

We try to find at least one night each week to play board games with our kids. Some nights it’s old faithfuls like chess or Monopoly. Other nights it’s strategy games like Ticket to Ride or Carcassonne.

It doesn’t matter if it’s 15 minutes or 3 hours, putting down the screens to play a game while sitting around the table provides a type of dopamine hit that AI simply can’t deliver.

6. Playing / Coaching Sports

Speaking of games, playing and/or coaching sports is one of the best ways I know of to disconnect.

I’m the type of person who desperately needs regular exercise (I workout almost every morning), but going to the gym and/or working out with my trainer is more like a daily routine than it is a true disconnect. For me, the competitiveness and camaraderie of sports is where the magic happens.

As a parent, I love coaching my kids’ sports teams. I also love playing sports. Whether it’s team sports like soccer, hockey and baseball or individual sports like skiing, swimming or rock climbing, the combination of physicality, competitiveness and disconnect provides an effective mental and physical reset.

There are plenty of other ways to “touch grass”, from reading a book to camping (and fly fishing!) to playing a musical instrument. Whatever you do, try to find 20 minutes a day to disconnect from all of your agents, breath deeply, and relax.

I promise you’ll have more energy, more stamina and more focus.

And, as I said last week, those agents aren’t going anywhere 😉.