A couple of weeks ago I went to Ai4 in Vegas to see what’s transacting in the world of AI. I’ll be writing up more on that next week. But, in the meantime, I discovered the luxury watch market and how it works. Now, I’m fully aware this is its own niche with fierce fans and strong opinions, imprecision in my market segmentation, along with facts that I’m likely to butcher while writing this, so don’t rage DM me watch nerds ⌚🤓. This is just a look into a whole market and subculture I didn’t know even existed.

Most hotels on the Strip have effectively a shopping mall attached to them. The fancier hotels have high end brands like Tiffany, Prada, Gucci, etc. in their malls. For example, there are effectively 5 Tiffany stores on the strip alone. And the idea is that - there are no discounts to be had - you’ve traveled from somewhere to ... indulge... and what happens? You get a little tipsy? You just won some money? You don’t have to walk far to be able to be relieved of that cash. But watches, they have their own little economy that fits into this narrative.

What’s in the window is not for sale

Being guided by Daniyal Liaqat, a watch aficionado, as we wandered the Grand Canal Shoppes at the Venetian, I learned that if you walk into a Rolex store, for example, you can’t actually buy almost anything that’s on display. They may have a couple watches in stock, but those are usually on the order of $50,000 or so.

The watch you’ve been lusting after is likely not in stock at all and there’s a multi year queue to get it. You can get in line like a good citizen and wait your turn (but it’s not clear that your “turn” is as simple as being next on “the list”), or you can start buying watches and develop a relationship with the salesperson / retailer, who has a large amount of discretion about who they sell which watches to and when. A salesperson at A. Lange & Söhne told me that when they get a watch in stock, he gives his “next in queue” 24 hours to come and buy otherwise he goes to the next person on the list, no matter where they live.

As an aside, my understanding is that buying hard-to-get Ferraris and Hermès Birkin bags operate in a similar manner. I’d love to pretend I knew this firsthand from my buying patterns, but Apple’s offered me a big fat nothing given they own at least one of my kidneys at this point.

What’s not in the window is for sale

What blew my mind were the stainless steel watches. Many brands have what, on paper, should be cheaper watches that are not made of gold and diamonds but stainless steel. The thing is, you can’t buy them first. They’re not cheap, relatively speaking, even at the MSRP, but you effectively cannot buy them unless you’ve invested into a relationship with a given dealer and very likely having to have bought a few mid-five figure watches. One example is the Patek Philippe Aquanaut 5167A, a steel watch that costs about $27,000 but you can’t buy it without the right relationships and history. And then, if you want to skip the queue, on the secondary market, as of this writing, it is worth $71,000, a 162% premium. The dealer at Vacheron Constantin told me their super popular stainless steel model, the Overseas, is $25,000 - well below the other watch prices - but he wouldn’t display it as it would be an education conversation, not a sales one. And so it goes. You have to earn the right to buy.

Why not charge more?

Why don’t they just raise the price? Why do they let secondary markets capture the difference? Well, Thierry Stern, the president of Patek Philippe, told FT that “a steel watch has to be at a steel price”, and it can’t cost more than the more precious metal ones or ones that are technically more complicated. They are also making only so many watches so flooding the market with steel watches would leave money on the table for other, more premium watches they could be making. So we’ve got an engineered artificial scarcity situation going on here in order to keep the luxury brands perceived value high.

Here’s where it gets really crazy - like “you need an economics degree” crazy. And Rolex, from what I can tell, is at the forefront of this. Why sell a Daytona 126500 watch for $17k MSRP when you could get $32k for it? The primary benefit is marketing; now they can say without saying: “our $17k watch is so desirable that people are willing to pay $32k for it.” (It’s worth noting that Rolex does not claim to have a spend-to-qualify rule). And, should you be lucky enough to buy it, you feel privileged like you’ve won some sort of secret lottery iykyk. And, it keeps steel prices rational. And, a recent study (readable summary here) has found that foregoing short term profits actually can increase long term profits.

And, finally, it shields them from the collapse of the secondary market. If, say, Rolex just kept raising the prices based on demand, if the demand dropped for some reason, they’d have to cut prices. But luxury brands don’t cut prices. So they don’t have to worry about that - the secondary market can. After all, normally, watches devalue the second you buy them.

Who gets the call?

So you have a $17k watch that’s really worth $32k... how do you decide who gets one? It’s not a “just move to the next person on the list”, because that person could just make $15k later that day. This then becomes a line up of not customers but merchants, which is not what a brand would want, hence the human being with judgment standing between you and the watch. In this case, price isn’t the decision maker, it’s relationships, and the rationale does make sense in this wacky market. And the salesperson deciding whether you’re a customer or a secondary market merchant is also the person who can tell that you’re not ready and just show you a gold watch instead. From my side of the counter, I’m being screened and sold to at the same time.

As an aside, a crazy example of this going wrong is in the book Apple in China, where iPhone lineups in China were not what they seem - some were organized purchasing schemes.

But this isn’t about tech, Bob

Of course, cough, I spent most of my time at Ai4. So walking back from the malls to the conference, I came back with a different perspective. Not how much AI compute costs, but who’s allowed to buy it. But that’s next week’s post.

Daniyal is on a list, by the way. Somewhere out there a Rolex dealer has his phone number and control over his weekend two years from now.

I’m old. Old enough to have been through multiple tech boom and bust cycles (I started in the dotcom one as a front-end developer). And this time around I’m watching the largest pile of private capital in history, and almost all of the marketing attached to it, pointed at one thing: removing the need for software developers. At the same time I’m seeing the complexity of managing all of this increase (for now??), for example these net new technologies:

• OpenRouter for routing your AI requests to the best / cheapest model, and a crazy leaderboard that I’m sure you can have fun placing some weird Kalshi bets on

• E2B, a tool that provides enterprises a place to run their agents so they don’t break everything (the OpenAI rogue hacker AIs notwithstanding)

• MCPs, the model context protocol that allows AI to connect to existing systems in a way that works for them

Amazon.com makes no money

Which reminds me of Amazon back in the day. When Amazon IPO’ed in 1997, they spent years promising they would be profitable, and weren’t for a long time. I remember thinking that I’d never seen a public company say that and better yet, get away with it. These days they’d likely have just stayed private. But they started by selling books, and then built a massive distribution network and, since loading a truck with other stuff that’s not just books wasn’t super hard, voila, they became the everything store. Around the same time, companies like pets.com, the mascot of dotcom failures of the time, and other retailers like Webvan were tanking horribly.

But then, post-bust in the early 2000s, something else was brewing. Amazon was decentralizing their infrastructure and needed simple programmatic access to it for their own teams so they started slowly building what became AWS. It didn’t hurt that they had learned how to scale massively and had solved for burst problems like Black Friday, leaving them with spare compute the rest of the time. So, they pushed it out to the public as Amazon Web Services, and once launched, anyone could spin up an infinitely scalable internet company without needing capital for the machines, maintenance, data centers, and all the other complexity. They then turned their focus to enterprises and said “we can host your infrastructure better than you can, so let us help you there too”, and it worked.

That leaves us the question of how Amazon actually makes money. In 2025 that was $80 billion in operating income, and more than half of it, about $45.6 billion, came from AWS, from renting out the plumbing they first built for themselves. Most of what’s left is advertising. Amazon doesn’t break out the ad profit, but it books $68 billion in ad revenue at margins some analysts put at around 40%, which is roughly $27 billion. Add that to AWS and you’re at something like nine-tenths of the entire company’s profit. Which leaves the everything store, the trucks and the boxes and the warehouses, as the sliver at the bottom, clearing a margin somewhere around one percent. The bookstore turned out to be a cloud provider with an ad network stapled to the side. Who could have predicted that?

The chatbot is the front door

So what does this mean right now? Stating the obvious, the chat window is not the business. A heavily subsidized $20 per month does not scale to the valuations being thrown around. But that doesn’t mean chats aren’t doing heavy lifting for the AI companies themselves, much like Amazon’s storefront did. It’s the front door and the habit-building machine that’s being created, your “homepage,” so to speak, back when that was a thing worth fighting over. And, even as Amazon has turned their storefront into an ad machine to monetize that surface more profitably, we are still paying something to access these companies’ front doors.

Claude Code is another version of the same game: acquisition and retention of their users. It started as a side project in Boris Cherny’s first week at Anthropic, an AppleScript toy he wired up so Claude could read his music library, and by the time they launched it publicly, over 80% of the company’s own engineers were using it every day. This accrues far more value than a simple subscription alone.

So that brings us to the billion (trillion?) dollar question: what horribly expensive internal problem is so big that someone ends up renting out their solution? If creating AWS was a chore before it was a business, someone is choring (I created a gerund!) as we speak to fix their operational mess (routing, token minning vs maxxing, keeping murderous agents at bay), and it will actually be the product that gets stapled to the front door.

I don’t think anyone knows what the chore is (despite what you may see on X), and that lines up with what I’m hearing from both entrepreneurs and enterprises alike. But it won’t be categorized as an AI thing per se, just as AWS has nothing to do with selling books.

Somewhere in the mess

So “replacing all developers” was the shiny thing to look at but, if I’m right, like all shiny things in this space, it likely means we’re looking at the wrong thing, he says while staring at his metaverse NFT. I’m also well aware of the fact that the internet was based on open, free protocols (HTTP, DNS, TCP/IP, SMTP) that were publicly funded, and that AI is privately built and funded right down to the Nvidia metal. Even the open-weight models that look like a gift can be un-gifted (see Meta stopping right before Behemoth in April of 2025). So the analogy isn’t perfect, making it even harder to get it right. But, like all of history, it rhymes.

Somewhere in this mess is a business model that is gestating, despite all the hype and what is being claimed with certainty. It may emerge from the ashes of startups being built right now. What I can say with certainty is that it’s not what we’re all staring at, as I write this on my Aeron chair, acquired for free from the last pile of ashes with the wrong business model.

AI4

Speaking of nobody knowing the chore: next week I’ll be at AI4 in Las Vegas (August 4-6), in a room full business leaders trying to untangle AI. So here’s a real ask: What do you actually want to know about how big companies are thinking about AI? What would you put to them if you had the badge and the room? Hit reply and tell me. I’ll carry your questions in and report back what I actually find, not what I hear in the keynotes. Get them to me before Aug 3 and I’ll go hunting.

Where You’ll Find Me

• AI4, Las Vegas, August 4-6. Come say hi if you’re there. I’m always up for a hallway conversation about which business model is currently on fire.

• SaaS North, Ottawa, November 3-5. I’ll be hosting a shin-dig at this event, subscribers get dibs. Stay tuned!

The batch he skipped. Sand Hill North invested in zero YC companies this batch, which, for them, is abnormal. The batch was built for one number, revenue, ARR as a headline (or is it “R” when it’s a new company?). Ryan’s read: a million in ARR is cheap to hit now. Spin up AI middleware that helps companies stand up agents, ride a problem everyone has this quarter, and the revenue arrives fast. Fast and spiky is not the same as durable, and paying today’s valuation for it means underwriting a trajectory nobody can see yet.

Strongest batch in history, asterisk. Every model called it the best batch ever. Carta’s Q1 numbers say the median seed valuation is roughly flat while the 95th and 99th percentiles go vertical. More money, fewer deals, all of it concentrating into the best of the best. Two companies landing at a $175M valuation isn’t a miracle, it’s the 99th percentile showing up right where you’d expect in a pool of two hundred. The funds that look like geniuses win on deal flow, not a better sausage machine. Ryan’s line: you pick the people who were going to succeed on the way in, and they succeed on the way out.

The spreadsheet died. Five years ago you could put a SaaS company on a spreadsheet and know if it was venture scale. That formula is gone and nothing has replaced it. What Ryan’s hunting now are models that couldn’t have existed before AI, leaning on the idea of Sarah Tavel’s “sell the work, not the software.” Charging two grand to replace an outcome instead of fifty bucks to rent a tool. One example is Terranox, which Ryan invested in, a company using AI to predict where the uranium is, raise money to buy the mining rights, drill, and if you’re right, sell the mine. Which leads to my favorite quote of the episode:

“Sure, they have zero revenue between now and when they find uranium. This is more like the very old venture, the king of Spain sending a fleet of ships across the ocean to find spices or gold.”

You’re renting the foundation. The whole Fable / Mythos thing also got me thinking. The internet was public infrastructure by birth. These AI companies’ models are not. AI is private infrastructure, and everyone building on it is a renter whose landlord has a cost floor well above zero and can change the terms whenever the IPO calendar says so. Mythos is the cautionary tale: it shipped, the U.S. government decided non-Americans couldn’t touch it, Anthropic killed it rather than fire its own team, and it came back the day before we recorded. Build your product on it and the floor drops out overnight. So the model was never the moat. It’s rented, and one agent swaps for the next without much friction. The defensible thing is being the team a customer trusts enough not to rip out and replace.

Sovereignty isn’t a hard drive. Every country got spooked and started asking whether it needs its own Mythos. Ryan’s answer: you can’t out-spend the frontier. A gigawatt data center runs $50–100B, few governments are signing that cheque, and the Chinese open-weight models are six to nine months behind anyway. The moment they ship, anyone can retrain and repackage one until, in his words, “I have my own Ryan’s Fantastic model.” He stresses he’s not in government, but the observation is simple: don’t run a race you can’t fund. Figure out what your country is genuinely good at and point that at the AI stack instead of trying to clone the frontier. Mining was his example for Canada, but the principle is to play to your strengths.

Finally, we get into how “sovereignty” is slipperier than “it’s on our soil.” My example (and I tracked down the reference now that the episode’s in the can): a French company, French data, a Microsoft stack sitting in France, and it can still be reached through the front door under U.S. law, because Microsoft is an American company.

When nobody can tell you what the business model will be in two years, you’re not underwriting a company, you’re underwriting a person or team, which honestly is what it’s always been about. Ryan signs off that you can email him at ryan@shn.vc and an AI will read it first, “depending on the version we’re allowed to use that day.”

Hot takes welcome, especially if you’re building a uranium AI company.

Lise Birikundavyi gave me the numbers before I’d finished my first question. Black founders are roughly four to five percent of the entrepreneurial population in Canada and take in about 0.8 percent of venture dollars. A Black woman sits at the intersection of both discounts and takes in around 0.34 percent. That’s messed up.

The reflex is to file this under fairness, and it is, but that isn’t how she pitches it. Lise co-founded BKR Capital, which invests in Black-led startups across Canada, and to her LPs the number isn’t a grievance, it’s a mispricing. “Go look for the arbitrage,” she told me. “Go where nobody else is looking.” She was one of three investors and ecosystem builders I spent two days with at StartupFest last summer whose job, stripped down, is to say yes before there’s any proof that yes is the right answer. The word all three of them kept reaching for was conviction, which is less a trait than a process: Lise, and then Nectar Economakis and Richard Chénier, each ran a different one, on different raw material, at a different scale. None of them found their conviction lying around. They manufactured it, and how they did it is the story.

Lise’s raw material is the overlooked, and she’s literal about it. When BKR likes a company it will often write the smallest cheque in the round and lead anyway: she does the diligence, puts her name down first, “and then you’re able to bring a lot of people around to support them.” The capital isn’t the product; going first is. And the same instinct that points her at the founder nobody’s funding points her at the sector nobody’s watching, which is why her deal flow is full of AI quietly eating HVAC, construction, auto repair, remittances, hair care - everyone else’s miss is the asset. Overlooked founders in overlooked markets. That’s conviction manufactured one deal at a time, the cheapest scale there is: there’s always something underrated, and being early to it is a call you can make alone on a Tuesday. Since 2021 BKR has read more than 1,600 decks and backed fifteen companies, and just held a $20-million first close on a second fund (Black Innovation Fund II, target $50 million), doubling down on that thesis.

Of course, there’s the old story that non-US markets tell themselves over and over again. It’s best summed up by a French expression Nectar Economakis quoted to me, one I loved: “nul n’est prophète en son pays.” No one is a prophet in his own country. He meant the Canadian founder who can’t get a local fund to lead a round until an American one does, at which point the locals reappear as if they’d been in the room the entire time. His partner Fred lived the undiluted version with his last company, Nubo: Series A led locally, numbers up and to the right, and then for the B, nobody. Fred came back with a term sheet from California and there was a stampede of follow-on. Same company, same numbers, same week. The only new fact in the world was that somebody else had gone first.

Nectar is trying to make a whole fund out of refusing to do that. Amiral Ventures invests seed to Series A in enterprise AI and industrial software, or in his own framing, “how do you make real shit in the economy.” When Amiral leads, the follow-on arrives, because follow-on was never the scarce thing. And the tell that he actually believes this is that it happened to him: for months his running joke was that he did venture but not capital, because the capital hadn’t shown up yet. Then one credible anchor LP committed, and the rest stopped asking whether the fund was real and started asking how to get in. Amiral held a $40-million first close at the end of last year, on the way to a $75-million target: the joke resolving itself in public.

Nectar’s approach runs the other direction. Lise’s conviction comes from something that already exists and is underpriced; his comes from an end state that doesn’t exist yet, reasoned backward into a bet. What he’s after, he’ll say flatly, is more big companies: one 200-billion-dollar company exists here, he wants ten, and ten flagships drag a whole layer of fifties and tens up behind them. You can argue with the number, but the point is that he reasoned his way to the bet rather than waiting for a term sheet from California to place it for him.

Then there’s Richard Chénier, who is attempting this at the scale of an entire economy, which is yet another version of hard. He runs Québec Tech, a nonprofit that launched at last year’s StartupFest, and his frustration is that the talent question is basically solved (the labs, the AI researchers, the quantum people, Yoshua Bengio more or less down the street) while the commercialization question is wide open, and the missing piece is that nobody will declare what the place will be great at. His phrase for the fix is “a right to win.” AI is not a sector, he kept insisting, and neither is quantum; they’re things you point at a sector. So pick the sectors where the strength is already real in Québec (energy, life sciences, aerospace, the industrial base) and aim the innovation and investment there on purpose.

Underneath the strategy vocabulary, what Richard is manufacturing is conviction at the level of a jurisdiction: an authoritative “this is the bet,” declared before there’s a result to justify it. And the reason it’s the hard version isn’t that the raw material is missing. The talent and the labs and the real sectoral strengths are all sitting right there. What’s missing is a shared decision about where to aim them, and that decision isn’t his to make alone. He’s the first to say the sectors have to be chosen with the Québec government, not announced over its head, because a bet the size of an economy only holds if the people who’d have to get behind it helped pick it. Lise and Nectar can each hold their conviction in their own two hands; Richard’s has to be held by a crowd and still point one direction. That’s the harder version of the same craft - not that theirs is easy. (Nectar had the cleanest image for it: Russian nesting dolls all the way back, until you reach the government going, well, I suppose we’re the ones who put the first money in.)

The one input that’s changed since we spoke is the world itself. A year ago, Nectar told me, if he’d said the word “defence” to his LPs they’d have run out of the room; now it’s a category with a straight face. Richard’s founders used to reflexively look south and now look to Europe and Asia. Whatever you think of the politics that did it, the effect on conviction was specific and fast: a set of bets that were unfundable in 2024 became obvious in 2025, almost overnight. A reminder that the belief was never really about the technology. The technology and the market sat there the whole time, patient, unchanged. What moved was permission.

Strip these three conversations down and the same fact sits under each: going first means being willing to be wrong out loud, before anyone can tell you whether you are. Lise built a fund on that. Nectar built a fund on that. Richard is trying to build a province on it. That’s the whole price of conviction.

Around 2007 I was the product owner bringing Ontario’s desktop telemedicine product to market, the public-sector version of what Maple and Dialogue would later turn into actual businesses. Whoops. Good gig. Three days a week I built that, and the other two I spent building something of my own, because I’ve always been an itchy entrepreneurial type. Some old colleagues, Ken and Garry Seto, saw what I was up to and wanted in, so I brought them over. Their own side hustle, Endloop, took off first: they shipped iMockups, one of the first thirty apps on the iPad App Store, and it caught because it took Steve Jobs’ idea of the iPad as a creative device rather than a consumption one and ran with it. In 2010 they called me to be their CEO.

Who gets that call? Not necessarily the most qualified person. What did I know about sales, PR, fundraising, video games, or equity? But I could build product at scale and I’d put in years next to Ken and Garry. The call didn’t come because I was the safest hire on paper. It came because the work and the relationships had quietly made me the obvious one when the seat opened up.

I’ve come to believe in engineered serendipity - the idea that you intentionally set yourself up for luck to happen. You work with interesting and ambitious people, build and ship products and content, be out there, and trust that proximity + output + time manufactures the kind of luck that will never come find you otherwise.

But you also need to be around long enough to have opportunities come your way. As Paul Graham put it, you need to be default alive.

Looking back on last year’s StartupFest, I had three very different conversations that got me thinking about time horizons.

Moon Time

Madison Feehan runs SpaceCopy out of Alberta, and the business is 3D-printing infrastructure on the moon out of the dust already up there. Lunar regolith, what the rest of us would call moon dust, crushed and characterized and printed into housing, roadways, launch pads, beams, over 250 things you’d otherwise have to fly into space at a price per kilo that makes no economic sense. Her timeline is geological. The zero-gravity test flight is slated for late 2026, the moon itself is roughly five years out, and she’s spent about $200,000 to get this far against a $5 million raise, she tells me. Printing with regolith, she noted, is “much like working with shards of glass.” Not a fun time, and not a fast one.

So how does she stay default alive until that time comes - especially as a deep tech startup? Fixing door hinges that keep breaking in Nunavut, plus vehicle parts the manufacturer no longer makes, printed on Earth 70% cheaper and 20% faster than flying them in. She claims she’s sitting on 300 pre-orders before the moon pays a dime. This isn’t a put-AI-on-the-moon-or-go-bust-in-a-year startup. This is doing a hard thing over a long period of time, so patience and resilience matter.

Brain Time

Joshua Lyttle is at the opposite end of the dial. He’s a biomedical engineering student in his final year, and his company, Mindfully, is building a non-invasive EEG wearable that reads your prefrontal cortex (FP1 and FP2, if you want to sound smart) and flags when you’re about to relapse on a habit before you’ve decided to. The clock he cares about is the smallest one here: the few seconds between the craving and the caving, between knowing what you should do and doing what you shouldn’t anyways.

The irony is that the founder fixated on the shortest clock there is has signed up for a long, tough slog. Reading the prefrontal cortex accurately enough to flag a relapse before it happens is not a two-year project, and nothing about it is guaranteed to work. He’s measuring milliseconds and committing to a decade, and he isn’t pretending it’s anything less. The difference between him and almost everyone else pitching that day is that he can afford to be wrong slowly: he’s in his final year, his founder clock reads “after I graduate,” and a decade poured into something that doesn’t pan out still leaves him young enough to start over. He isn’t outrunning his clock; for once it’s running, to an extent, in the founder’s favour.

Borrowed Time

Then there’s Katy Yam at Real Ventures, running a clock shaped nothing like the other two. Real manages $320 million across four funds, last raised in 2017, and isn’t writing new checks into new companies at the moment - it’s realizing the portfolio, returning capital, collecting on old bets like Xanadu, the quantum computing company that was still a wager when we spoke and is public now. A fund has its own time pressure, just a different kind: you deploy while the clock is young, into things that can plausibly pay out before it runs out, then hand the money back on schedule, because those returns are what let you raise the next fund at all. Madison and Joshua are racing to exist. Katy is racing a contract, and the next one behind it.

What actually kills companies, she says, is rarely the market. It’s the people: the founder who breaks before the company does (something I subscribe to wholeheartedly). Real has pulled founders out to, in her words, stabilize them as humans then reinsert them, because a founder who quietly runs out of stamina is just a clock running out before the luck arrives. She runs the one clock here with a hard date on it, and what she’s learned watching founders is that the clock that kills you is the one you’re not even looking at.

Face Time

The three of them are running clocks that don’t resemble each other at all, but the move underneath is identical. Madison stays alive fixing door hinges in Nunavut. Joshua gets to be wrong slowly. Katy spends her days keeping founders from breaking before the bet matures. Not one of them can make the luck arrive on schedule. All any of them can do is still be in the room when it decides to.

The call to run Endloop found me because I’d spent years next to Ken and Garry, shipping, being around - default alive - and letting proximity and output do what they do. In 2011, it almost happened again. We got a call from Zynga, at the time a super hot company. They were shopping for mobile companies, so they flew us to San Francisco, showed us how the machine worked, and sat us down with their M&A team and the mobile lead doing the acquiring. Zynga ended up buying Five Mobile, a 50-person shop in Toronto run by Ameet Shah. Now Ameet’s a fancy VC at Golden Ventures, but at least I’ve still got my looks.

When I lived in New York in 2017, you could eat and get around one of the most expensive cities on earth more or less for free, courtesy of venture capital. Uber would carry me across Manhattan for the price of a coffee, the meal kit companies were mailing out a week of dinners for less than it cost them to box the dinners up, and half the apps on my phone were quietly underwritten by funds that had decided growth was the only number worth chasing (profit being a problem for a later, more boring version of the company). If you sequenced your free trials carefully, you could live in Manhattan for a month or two at roughly the price of Cleveland.

Then the bill arrived. Not all at once, and yes, a pandemic smudged the timeline, but it arrived. An Uber now costs what a cab costs, sometimes more, and the delivery apps stack a service fee on a delivery fee on a tip prompt that opens at 20%. The free decade turned out to be a loan, with repayment terms nobody read: once the competition was starved out, you and I would pay the real price, plus margin.

I bring this up because we just speedran the same cycle with AI, except Uber needed fifteen years to get from subsidy to invoice and this version did it in three (effectively). The most private capital ever raised went into subsidizing the product, doing the land grab, and leaving the economics for later, when they would be somebody else’s problem.

And then, over the last few weeks especially, the vibe changed (pun intended). While per-token prices mostly did not go up (a lot of them have actually come down), what ended was the not-counting. Sam Altman is calling cost one of the biggest themes in AI right now; case in point: Microsoft has started cancelling Claude Code licenses. There is even a word for the behaviour that got everyone here, tokenmaxxing, and the moment a behaviour gets a name, you know something’s going to happen.

The why is not complicated: these companies are heading to the public markets. Anthropic filed confidentially on June 1, fresh off a funding round at a $965 billion valuation, and OpenAI filed a week later, and public markets do not accept a subscriber chart as an answer (unless you’re Jeff Bezos). At some point a person in a suit asks when you intend to make money. The subsidy phase ends because it has to.

But the subsidy was never just money. ChatGPT trained the entire world to use these things conversationally. Ask, refine, rephrase, try again, keep talking until the answer comes out the right shape. That’s a great way to work when someone else is paying for your tokens. The subsidy was an AI product retention muscle: no price signal ever told anyone to stop, so an entire generation of users and companies learned habits that only make sense while the tool is free. The money has now stopped and the habits have not. Uber found this out when its engineers, handed AI coding tools with no spending caps, ran up bills of $500 to $2,000 a month each, and the company (yes, the same one that once paid for my rides across Manhattan) torched its entire annual AI budget in four months and went, in its own CTO’s words, back to the drawing board.

This is also where the Uber analogy stops working. When Uber’s subsidy ended, the underlying thing (a man in a black Camry driving you home as a non-employee) cost roughly what it had always cost, and prices drifted back to taxi levels. With AI the expense is welded into the technology itself, at least for now. Every answer burns compute, and the price floor is electricity plus Nvidia’s margins. So when the land grab ends, there is no taxi fare for the price to drift back to.

A senior engineer costs, say, $200,000 a year and the tokens cost $2,000 a month, and you can see why boards get ideas (AI is now a stated reason for layoffs, and occasionally the polite cover story for cuts that were coming anyway). At the early stage of a company, the substitution is genuinely happening: startups are shipping with three people what used to take ten, mostly by never hiring the other seven. But inside companies that already have engineers, the pattern is additive, the $200K engineer plus the $2,000 of tokens on top, and the return is velocity, which I do believe in, and which is also hard to put on an invoice. So these tools are cheap to experiment with and expensive at scale, and the industry spent two years in experimentation mode while talking like it had solved the scale economics.

I should say that I am an optimist and am very, very excited about all of this, and not in the contractually-obligated-newsletter-writer way. You really can build software at a speed and scale that was science fiction three years ago, solve net new things, and come up with discoveries and products that never could exist until now. But “you can do more” and “you should do all of it, constantly, at maximum settings” are different claims, and the bill is finally going to force everyone to tell them apart, maybe sooner than we all would have liked.

For one thing, we will not get rid of developers. The demos imply you just describe what you want, and the tools are far more temperamental than that. The genuinely hard skill was never the typing. It was understanding a business problem well enough to translate it into something a machine will do reliably, and that is still a skill, and it still mostly lives in the domain of developers.

And the work itself has inverted in a way I do not think we have fully grokked. The old way, you sat with a machine that did exactly what you told it and nothing else, and you tried to think through every case: what if the field is empty? what if two things happen at the same time? Miss a use case and you’ve got a bug, which was tedious but knowable. Building with AI is the opposite exercise. You are not building a machine where you thought through all the use cases, you are wrapping your arms around something that wants to do everything and you’re trying to stop it from doing anything except the thing you actually asked for. You are negotiating with a probabilistic thing and hoping the guardrails hold, which is a brand new discipline, and one that takes more judgment per problem, not less. The negotiation also runs on the meter: ask, refine, rephrase, try again was a great way to work when the tokens were free, and now every round of it costs money.

It is also why I have started saying, half as a joke, that English just became a fifth-generation programming language. We spent seventy years climbing a ladder of abstraction, machine code to assembly to languages that read like math to languages that read like instructions, each rung letting you say more while typing less. The next rung up turns out to be a paragraph of plain (or maybe caveman) English handed to a model that generates every layer underneath. Which is great, and kind of ironic given how imprecise English is, because we are about to find out what imprecision costs when every vague sentence is billed by the token.

My guess about where this settles comes from an interview I did years ago with Christian Weedbrook, founder of Xanadu, the recently IPOed quantum computing company. His pitch for quantum was never “replace your computers.” It was: run your boring workloads on boring cloud, and when you genuinely need a protein folded, call the quantum API, pay the eye-watering rate, and hang up. I suspect software built alongside AI matures into something similar. Not AI as the substrate for everything, but AI as the expensive specialist you call when it is actually the right tool, surrounded by cheap deterministic code doing the parts that never needed a genius.

The capability is real and the bill is real, and they arrived in the wrong order: we started paying grown-up money before doing the unglamorous work of figuring out what the thing is actually for. So the interesting question for the next couple of years is not whether AI makes you faster, because it does. It is whether we can develop the taste to know when the expensive tool earns its keep and when it stays in the drawer, before the invoice figures it out for us.

If you have already figured it all out, hit reply. Unlike everything else in this piece, replies are still free.

Last week, at the end of the Origination and Acceleration piece, I promised you a Toronto Tech Week write-up. The question I left dangling was whether a week with no center, just hundreds of independent events scattered across a city, produces real serendipity or a pile of disconnected calendar invites.

Here’s what happened instead. I started doing the analysis and the analysis became the story.

The thing about a decentralized week is that nobody programs the whole thing. There’s no committee deciding the shape of it. Six hundred and ten different people and organizations each independently decided what was worth getting a room for, in the same city, in the same week, and that turns the calendar into something more interesting than a schedule. It’s an accidental census, a bottom-up signal of what an ecosystem is actually thinking about right now, uncoordinated and therefore honest. Which is exactly why I had my intern… let’s call him Clod…. tag all 610 events by format, topic, and function. Here’s the spreadsheet if you want to poke at it yourself, though I’d treat it as a curio rather than a primary source since keyword-tagging 610 event titles is an imperfect science and some of these calls are genuinely judgment calls.

What came back was not the AI story I expected.

Some interesting insights:

• Almost half the week, 49%, was talks, panels, fireside chats, and sessions.

• Only 7% was hands-on building: hackathons, workshops, build labs.

• Another 24% was meals, parties, and networking… Proximity basically.

In the origination versus acceleration frame I wrote about last week, this week was almost entirely origination, the messy, uncoordinated, bottom-up kind. AI appeared in 151 event titles, the costume of the year, the thing you put in the title to get registrations, but strip it out and the skeleton is surprisingly old-fashioned. People gathering, listening, eating, talking, being in rooms - the most un-AI thing possible. For all the founder mythology about building and shipping and moving fast, the dominant activity of a builder’s week was not building… It was showing up.

The underlying point worth naming is that builder culture runs almost entirely on social infrastructure, and there’s nothing wrong with that. It’s just not what anyone says out loud because it seems obvious.

Which is where Toronto gets interesting, and it's because of the genericness, not in spite of it. New York, SF, London, and Portugal all run a version of the same week. The format is a standard container. So the question isn't whether Toronto invented it - it didn't - it's what pours into a standard container when Toronto is the one filling it. A borrowed format is almost a blank test. Whatever shows up is the part that's actually local.

What I noticed, and I'll flag this as a feeling more than a finding, is how much of the week carried some kind of identity or global lens. Muslim founders, Persian founders, Africa-Canada, Mexico, Czech, Swedish, Asian founders, women-led communities. Around 9.5% of events by Clod's count, though I won't pretend I know whether that's higher than New York or London, or whether we just put it in the title more. What I can say is that it didn't read as a side track. It was on the main calendar, unremarkably, next to the AI panels and the investor breakfasts and the pickleball tournaments.

Adding to the heterogeneity, you had ALL IN Talks on Thursday (I should note I’m an event partner and have been remunerated by them in the past, make of that what you will), with a room full of enterprises trying to wrap their arms and brains around AI and where it fits in their business. That’s a completely different register than the scrappy founder energy everywhere else that week. At the same time, a friend of mine got acquihired to cofound an AI vibrator startup with US cofounders, which is either the most 2026 sentence I’ve written or the most Toronto one, I’m genuinely not sure. The week was messy, multilingual, uneven, and real in a way a programmed conference can’t manufacture.

Big, organized conferences say: look who came here. Toronto Tech Week says: look who was already here.

Toronto Tech Week isn't interesting because it invented something. It's interesting because Toronto is finally dense enough that a borrowed format, run from the bottom up, shows you something true about the place. The ecosystem is becoming visible to itself, and a census nobody planned is one of the better ways to see it.

What’s your take?

Last year, after Web Summit’s first Vancouver edition, I wrote that the conference still felt Canadian. That for a global event’s North American outpost, it had not quite grown into its stature. My advice, stated plainly, was that its north star for 2026 should be to feel more like the centre of the universe.

I went back this year. I still like the conference a great deal. But I think I gave it the wrong advice, and the reason why is more interesting than the advice itself.

First, credit where it is due

Web Summit Vancouver is, by every number it publishes, working. North of 20,000 attendees this year, up roughly 29%, with its largest investor turnout yet and well over a thousand startups. The team runs a genuinely well-oiled machine.

And I want to say the real positive thing clearly, because I mean it. Web Summit thinks big. It shows up in a city, plants a flag, and behaves as if that city is, for four days, the most important place in tech. In Canada especially, and honestly in a lot of places that are not San Francisco, the default setting is small thinking. Modest ambitions, modest framing, a quiet apology built into the pitch. Web Summit does not do that. A tech ecosystem that gets a regular dose of “act like you matter” is better for it, and I left genuinely energized. I even threw my own event during the week, an attempt to get founders, investors, and ecosystem people into a room to make something happen without being sold to every ninety seconds.

So this is not a piece about a conference that disappointed me. It is a piece about a tension I have been chewing on for a year, and Web Summit is simply the clearest example of one side of it.

The thing people do not think about: who funds the gathering

Here is something most attendees never consider, and I think it is worth thinking about.

A conference like Web Summit is not primarily funded by founders buying tickets. A major part of the business model is cities, provinces, countries, and corporates, all paying for space, pavilions, presence, and proximity. That is the engine underneath the event.

I do not mean that as a knock. It is just the mechanism, and once you see it, the shape of the whole conference makes sense. If your customers are governments and corporates buying presence, you build the thing they are buying: big stages, national pavilions, regional investment showcases, a marquee moment worth being photographed next to. The event optimizes for what funds it. Every event does. The regional bootcamps, the investment tours, the pavilions are not incidental. They are part of the value proposition.

This is what I would call a top-down model. The gathering is convened, and substantially paid for, from the top. And top-down is genuinely good at certain things. It creates scale fast. It manufactures ambition and gravity. It can put a city on the global map in a way no grassroots effort can match in the same timeframe. That is a real capability and Web Summit is excellent at it.

But it is one of two ways to gather an ecosystem, and the other one works completely differently.

The other shape

Last year at Startupfest in Montréal, I recorded a couple of relevant conversations that have stuck with me. I am publishing them alongside this piece because they describe the other model better than I can.

The first is with Ilias Benjelloun, a three-time founder and longtime community builder in the Montréal ecosystem. Ilias’s view is that the real energy in a tech ecosystem is bottom-up: the grassroots groups, the underground networks of builders, the people self-organizing without waiting for permission. He is not dismissing the organizations that support founders, he has helped build some of them. His point is narrower and it is about events: the gatherings that matter most are the ones that find those grassroots groups and back them, rather than staging something over the top of them.

The second is with Simran Kanda, who runs Elantech in Montréal, so she sees this from inside a small institution. Her observation is that as an ecosystem matures, it gets more structured and more professionalized, which helps the external image but quietly starves the human layer, the part where founders are actually nurtured rather than just networked. Her response was to build deliberately small, unstructured rooms: no cameras, no stakeholders, no service providers, sometimes literally a picnic or a sports afternoon. Her attendance rate is around 90%, because people show up for things that feel human.

Put their two views together and you get the bottom-up model. Not convened from the top and paid for by sponsors, but emerging from the people doing the work, distributed, human, a little messy, harder to photograph.

The tension: origination and acceleration

Here is the thing I actually want to name, and it is not “which model is better.” Both models are generative. They just generate different things.

Bottom-up is origination. It is where the actual material of an ecosystem gets made: the builders, the relationships, the trust, the companies themselves. It is slow, human, a little messy, and it does not photograph well. Ilias and Simran are describing origination. You cannot fake it and you cannot rush it.

Top-down is acceleration. It takes what an ecosystem has already originated and adds velocity to it: scale, capital, international attention, a centre of gravity, a stage. Web Summit is very good at acceleration. The 20,000 people, the 768 investors, the billions in tracked follow-on funding, that is real acceleration of real companies.

And here is the part worth sitting with. There is a reason the acceleration model is the one that attracts big money, and it is not glamour. It is legibility. A large corporate or a government can easily fund a top-down conference, because a conference has sponsorship tiers, pavilions, invoiceable line items, a procurement-shaped surface. Almost nobody can write that cheque to a grassroots picnic. There is no purchase order for origination. So acceleration events grow, because they can absorb institutional money, and origination events stay small, because they cannot. That is structural, not a judgement.

So the tension is not top-down versus bottom-up, and it is not which one is better. It is sequence. Origination tends to come first, and most of the money flows to acceleration. The interesting question for any gathering is which job it is actually doing, and whether it is honest with itself about which one that is.

Toronto Tech Week 2026

Which is what makes this week interesting, because Toronto Tech Week is happening right now, and it is a real world test of the bottom-up model.

Toronto Tech Week is mostly decentralized. It has one marquee event, called Homecoming, and then essentially nothing else is centralized. The rest is a sprawl of independently organized events across the city, closer to a startup open house than a conference. One anchor, everything else bottom-up.

And the shape of it is the interesting part. Toronto Tech Week is almost pure origination: three hundred-odd events, run by the city’s own people, scattered across the city, with one piece of acceleration, Homecoming, placed in the middle. It is the bottom-up model at full scale.

Here is the question I am actually focusing on into the week. Web Summit’s core asset is a building. The convention centre is the product as much as the programming, because proximity is what creates the accidental collisions (not ironically the original name of the conference itself: Collision), the hallway conversation, the person you did not plan to meet. Toronto Tech Week, by design, has no building. No central hub, no floor, no single meeting point. Three hundred events and no central location… creating a different kind of serendipity.

So the open question is whether origination at that scale holds together without a centre. Does a week with no hallway still produce sparks, or do you only ever meet the people you already planned to meet? This is not year one, it ran last year and it is back, so it clearly works well enough to recur. The real test is what happens as it grows. A no-hub model that is charming at small scale either scales gracefully because it was never dependent on a room, or it slowly thins out into three hundred disconnected calendar invites.

I have thoughts on that already, having spent the week in it. I will put them in next Wednesday’s piece.

We focused on the hot topics du jour. The investor panel with Green Sky Ventures, InterGen Capital, and Imbue Capital focused on the changing shape of capital markets. What stood out for me was the signal-to-noise problem created by the sheer volume of new startups, angels overpricing rounds negatively affecting their future returns, and the decision point around stalling at $3-7M ARR (or just revenue if it’s not recurring) and whether it’s worth seeking an exit or not.

The operator panel with #paid and Solink - both mature, venture backed companies - covered the other hot topics: AI eats features, price the outcome not the token, trust matters, and cleverness is not a moat. It's also worth noting I did poke them a bit because at this point decade-old startups are… incumbents? Disruptees? We don't have a word for the company that was scrappy six years ago and is now the one being undercut by AI-native competitors on weekends. We should. I nominate “mature startups”.

The one moment that made me laugh was when the investor panel converged, to my surprise, on the idea that services revenue is fine now, actually, as it gets you in to deliver outcomes and builds a relationship pure SaaS businesses can’t replicate. So we have come full circle. Angels should be investing in services companies. You heard it here first, and also in 2003.

Looping back to “what happens after you accept that not every company is venture-tracked and decide to go the other way”, at Startupfest I sat down with Mishel Wong, founder of BoPaq, a Montréal company replacing single-use takeout containers with reusable ones. Good business, real traction, doesn’t fit a VC bucket given reverse logistics, physical infrastructure, and behaviour change. Exactly the kind of company the ecosystem keeps quietly calling a failure for not unicorning. And she was super open and brutally honest - worth a listen since entrepreneurs don’t often share such raw details, especially mid-decision-making.

Mishel went the strategic acquisition route. The first deal fell apart at the altar. She described it like getting left at the wedding by someone who suddenly realized they didn’t actually want kids, even though kids had been the plan the whole time. The acquirer hadn’t fully reckoned with what taking on reverse logistics actually meant, and walked once reality set in. She moved into due diligence with a second partner, going in with a sharper rule: surface the ugliest operational realities first, on purpose, before anyone gets emotionally committed. They've since closed the deal.

That’s the part worth sitting with. The alternative paths get pitched as the calmer option. They’re not. The hard part just moves. It moves from “can I raise the next round” to “does the operational reality of my business survive contact with a partner’s spreadsheet.” Most founders aren’t trained for that conversation. Most acquirers aren’t either.

First up: Kare Chemical Technologies.

Kare makes pharmaceutical-grade cannabinoids out of orange peels. Orange peels. It’s a patented catalytic process already being licensed to pharma manufacturers. The applications they’re most excited about aren’t recreational anything. They’re non-addictive alternatives to opioids and treatments for pediatric epilepsy. They recently closed a $750K pre-seed round with a very small team.

This is the kind of company I think gets undercounted right now. Not a vibes-based AI wrapper. Not a “we’re disrupting [established industry] with [LLM]” deck. Just deep, weird, hard chemistry being done by people who’ve been at it for years and have something real to show for it.

Which is also kind of why I’m at NACO. I’m less interested in what founders are pitching - that’s a known quantity - and more interested in what investors are actually thinking about right now. Not just the sectors they’re chasing (hard tech? health? climate?) but how they’re thinking about the job itself. What’s keeping them up. What they got wrong in the last cycle. How much of their thesis is conviction versus what the LPs will tolerate. And underneath all of that, a question I find genuinely interesting: where does Canadian capital think it’s going? There’s a real conversation happening up here about decoupling from US dependence… Sovereign wealth funds, domestic angel networks, less embarrassment about backing things on home soil like defence, which until recently was a negative signal and now everyone is “in defence”… and I want to know if the people writing cheques believe it or are just nodding politely on panels.

In the meantime: orange peels. Enjoy.

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I’ve been a SXSW Pitch judge for two years now, and this year I noticed something running underneath almost every conversation I had - about AI, about music, about self-driving cars - worth naming.

Everybody on every panel and stage was talking about trust. Trust is the new moat. Trust is the new differentiator. Trust trust trust. Fine. But “trust” is doing so much work right now that it’s starting to mean nothing, which I think is a bit of a problem when you’re trying to build something. So let me try a more useful word: receipts.

When everyone has the same tools and the output is cheap to produce, what’s left is the trail behind the output. The reasoning, the track record, the proof, the why. The stuff that’s actually hard to fake.

Let me show you what I mean with a three act vignette.

The Kids Are Buying CDs

I was having fried chicken at Gus’s, and, over the inability to make eye contact with our server, started chatting with a chap who does strategy at Universal Music and negotiates the deals with the streaming companies. He told me that kids these days (👴🏻) are now buying… CDs and CD players. They’re cheap, you have ownership over the media (inasmuch as one can), they’re tangible, and… no screens, no algorithm deciding what’s next.

This stuck with me because it’s not really about CDs. It’s about the fact that the streaming model asks you to take everything on faith: that the song will still be there next week, that your subscription will still exist, that Amazon won’t take the book away, that the playlist hasn’t been quietly reordered for reasons the algorithm doesn’t owe you. A CD is a receipt. You can hold it. It’s evidence that a transaction happened and that a thing exists and will continue to exist whether or not a Series C startup decides to pivot.

That’s a weirdly old-school thing for a kid to want, but I get it.

The Fart App Era Grows Up

Last year at SXSW, my take was that AI felt like the early iPhone App Store: experimentation, novelty, fart apps, nobody quite sure what the platform could really do. This year the panels and the parties had moved on. The question now is: now that everyone can build with AI, what actually lasts?

The creator economy tracks were saturated with this anxiety. Everyone is talking about authenticity. And I’ll be honest. I’m sick of the word. It’s started to sound… inauthentic. (How fitting). But underneath the buzzword is a real thing, which is that when AI commoditizes the tools and increasingly the content itself, what differentiates a creator is not what they made this week but the trail behind them. The point of view they’ve held over time. The takes they got right. The takes they got wrong and admitted to. The reps. The receipts.

Your audience isn’t buying the post. They’re buying you, and the only way they can do that is by looking at the trail.

WayMo Or Less

I took my first Waymo. Genuinely impressive. Quick tip: sit in the front. No awkward passenger energy, and you control the radio and the temperature.

The car won’t make u-turns. It won’t do 31 in a 30. It won’t cut through an alley even if it would obviously be faster. Which makes sense… you can’t program in “just do whatever makes sense” if you ever want any of these decisions to hold up in court. So maybe the machines are safer but not faster. Or maybe I lived in NYC for too long.

What was harder to accept were the unexplained moments. It dropped me off on the wrong side of a highway - twice - without saying a word. My hunch is that the car won’t drop you off next to your destination if there’s any hint of an illegal stop or blocking right-of-way, so it just… didn’t. It backed up at a red light to make room for a truck behind it, which is polite but genuinely alarming when you don’t see it coming and your stomach tells you the car is misbehaving.

The fix isn’t complicated, and it’s the same thing the CDs and the creator economy stuff is about: tell me what you’re doing and why. Give me the receipt in real time. The technology earned my respect on the first ride. It hasn’t quite earned my trust yet, and the gap between those two things is exactly the thing I’m trying to name. Waymo has the capability. What it’s not giving me is the receipt.

Trust, Built From Receipts

So that’s the thing I keep coming back to. Trust is real, but it’s the conclusion. Receipts are the mechanism. When the tools are cheap and everyone can produce the output, the differentiator is the evidence behind the output. The reasoning behind the take, the track record behind the brand, the explanation behind the decision the robot just made.

I think this is a useful frame for anyone building right now, because it tells you where to invest. Not in more capability - that’s a commodity - but in the trail. The receipts. The stuff that takes time and can’t be faked, which is, conveniently, the stuff AI is worst at.

What’s your take?

In the meantime, here’s what a Waymo’s like from the driver’s POV.

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🎙 New Episode: How Donal Greene Beat $100M Startups (and Got Acquired on His Terms)

Most identity verification startups in 2022 were flush with VC cash... $200M raises weren’t uncommon. The standard playbook: raise big, spend fast, pray you don’t get hacked.

Donal Greene? He skipped all that.

Instead, he bootstrapped a tiny team, built a better product, got to $10K MRR, and then forced one of his competitor’s customers to acquire him.

This is not a case study in fundraising. It’s a playbook for building something better, faster and getting paid for it.

What stood out to me:

• MLP > MVP: Donal focused on building a “Minimum Lovable Product,” not just something that functioned. It worked: ID verification in 20 seconds, zero clicks, better fraud detection than the $100M giants.

• Domain expertise wins: What I thought was cool was that he constructed a team with 10+ years of biometric security experience. That edge made the product defensible and differentiated.

• He bootstrapped smarter: He focused on being fast, efficient, and good enough to close paying customers. That made it viable and visible to acquirers.

• Prospect your buyer: The wildest move? He identified a flaw in a competitor’s system, filmed a screen recording, and cold-DM’d a customer CEO. That CEO replied… with a Google Meet link. Weeks later, deal done, selling to Canada's Certn.

There’s a ton here for founders who don’t want to chase hype, and want to build on their own terms.

Donal doesn’t just tell the story of his exit; he demonstrates how to engineer your own.

🔊

Watch or listen: YouTube | Apple Podcasts | Spotify

Toronto Tech Week 2025: Recap & Thoughts

This past week marked the inaugural Toronto Tech Week, a grassroots response to years of fragmented ecosystem events and, notably, the recent loss of Collision to Vancouver. Modeled after other tech weeks around the world, it aimed to unify and energize the city’s tech scene.

So, how was it? I think the team did an admirable job.

Here’s the thing about most conferences: content quality varies, but the real action happens at the side events. Toronto Tech Week leaned into that insight. It was the side events, minus a central tentpole. The organizers told me on my livestream that they aimed for 10,000 attendees. If they hit that, they’re in the same ballpark as Web Summit Vancouver, which reported 15,727 this year. Not bad for a first outing.

And without a formal main event, there was still a ton of substance. We saw everything from packed mixers to conversations with some of Canadian tech’s sharpest minds. Brad Feld came to talk mentorship. Evan Solomon, now Canada’s new Minister of AI and Digital Innovation, came to listen. Netflix CTO Elizabeth Stone shared how they’re scaling and evolving (hot take: they want to be the next YouTube). A cohort of scaling entrepreneurs from Northern Ireland came to MaRS to explore North American markets. I even joined a panel with Dwayne Forde of Mantle at a founder matchmaking event hosted by YSpace and the Black Entrepreneurship Alliance.

In total? Over 300 events. Too many to name, but plenty to move the needle.

I’ve come to believe that culture drives everything in an innovation ecosystem. Government policy is downstream of culture. Risk-taking and entrepreneurship are, too. So is the instinct to rest on your laurels. And culture, as we all know, is the hardest thing to change.

By definition, events like this start by preaching to the choir. But this one had a glimmer of something more. A sense it might just be crossing the chasm into the broader fabric of Toronto.

Good thing crossing chasms is what tech entrepreneurs do best.

Upcoming Events

July 9-11: Startupfest in Montréal. We'll be doing a pop-up show on the event floor. Come by, say hi!

September 24-25: ALL IN, Canada's largest AI conference in Montréal, where I'll be hosting the All In Talks stage again.

🔊

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• How Donal built a “Minimum Lovable Product” instead of chasing MVP hype

• Why deep domain knowledge beat VC-funded noise

• What he learned replacing his founding team mid-build

• How a cold outreach turned into a full acquisition

• And what he’d do differently the next time around

This one’s for the builders who’d rather out-execute than out-raise.

📬 Tech entrepreneurship is changing fast. Join the conversation: https://decelerator.link/updates?ref=youtube

#podcast #interview #ai #startups #entrepreneur #entrepreneurship #technology #technews #artificialintelligence #innovation

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🎙 New Episode: Why Most Startup Ecosystems Aren't Ready for the AI Boom

At the inaugural Web Summit Vancouver 2025, I sat down with JF Gauthier, founder of Startup Genome, to unpack why ecosystems like those in Canada, Europe, and beyond are falling behind, and what cities like Philadelphia are getting right. They also just released their 2025 report.

So many things stuck out for me in our conversation including (and no, this is not a ChatGPT bullet list):

• the fact that startup ecosystem value has dropped 23% globally, its biggest drop ever, but ultimately still grows 4x faster than the rest of the economy

• In ecosystem land, Toronto fell from #13 to #20 and Vancouver from #15 to #36. OTOH, Tel Aviv, Singapore, Seoul all had government-seeded private scaling. And Philadelphia galvanized its ecosystem with no government help at all.

• JF also cited the example of DeepSeek and how the Valley-based companies acted on this innovation. They tested the new models with in days and shared their learning rapidly. He noted innovation velocity isn't just about capital - it's about ecosystem learning loops.

Just so much meat on the bone here...

Whether you're a founder, policymaker, or investor, this is your roadmap to staying relevant in the AI era.

🔊

Watch or listen: YouTube | Apple Podcasts | Spotify

Toronto Tech Week 2025: The Livestream Prep Tour

Watch the livestream, but not live!

Toronto Tech Week is coming up this week and one of the primary complaints I heard from friends and a few enemies is that the number of events was overwhelming and just tough to choose from and navigate. So I reached out to the organizers of the event and hosted a livestream this past week (our first 🙌🏻) to hear their perspectives on the event. If you're thinking of attending, have a listen!

Upcoming Events

June 23-27: Toronto Tech Week, we'll be out and about for its inaugural incarnation.

July 9-11: Startupfest in Montréal.

September 24-25: ALL IN, Canada's largest AI conference in Montréal, where I'll be hosting the All In Talks stage again.

🔊

Subscribe: YouTube | Apple Podcasts | Spotify

At the inaugural Web Summit Vancouver 2025, I sit down with JF Gauthier, founder of Startup Genome to unpack why ecosystems like those in Canada, Europe, and beyond are falling behind and what the top-performing cities are doing differently (like Philadelphia).

We dive deep into:

• Why AI is killing traditional SaaS

• How governments can seed ecosystems then get out of the way

• The real reason Canada's commercialization gap persists

• What investors should be doing in the AI-native era

• The new rules for building and scaling in 2025

Whether you're an entrepreneur, policymaker, or investor, this is your roadmap to staying relevant in the next wave of innovation.

🔗 Full Startup Genome report

📬 Tech entrepreneurship is changing fast. Join the conversation.

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New Episode: Ryan Henry on YC Spring 2025, Agents & Vibe Coding

Once again, I sat down with Ryan Henry of Sand Hill North, the sole VC at a family office to get his hot takes on the cutting edge startups he invests in. Why focus on the YCX25 batch for a show about building tech companies differently? Well, one is he does invest in the latest companies out of YC, and I'm fascinated by what shiny new AI tech shows up. And two, as a non-traditional investor, he doesn't have to deploy capital. He can do whatever makes sense for the fund whenever it makes sense.

So why check it out? This one gets into the weird tension of where we are right now: in between building tools and building coworkers. We cover:

• What “vibe coding” actually is (and why Ryan thinks I got it wrong)

• The early signals of agentic workflows taking over creative tasks

• What a good founder looks like in the age of AI

• Which traditional startup structures are breaking - and when those patterns don’t work, especially in enterprise or high-stakes domains

Check out the full episode - does this match what you're seeing and hearing?👇🏻

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Latest Episode: YouTube | Apple Podcasts | Spotify

Web Summit Vancouver 2025

After Vegas, New Orleans, and Toronto, Web Summit's newest North American destination is now Vancouver. I do enjoy these conferences and this one was no exception. It was significantly smaller than the previous iterations (15k people vs 40k), but Vancouver is a smaller city and there were no shortage of things going on. Aside from hosting an event, I moderated a panel on Canada's innovation opportunity within the Vancity Innovation house (a side event that hoped to increase BC's impact in tech writ large), and even recorded a pod with the founder of the Startup Genome project.

For its freshman year, it was a good start. It certainly had a BC vibe and clearly rallied their tech ecosystem. The Web Summit team have clearly built a well oiled machine as well. What I'm looking forward to at future iterations - and I know this is tricky - is a more "global" feel. Yes there were countries and companies from around the world, but - and maybe it's just that I wasn't invited to the cool kids parties and stages - it felt Canadian. It's a global conference's North American edition, and I think it still has to grow back into that global stature. I know this is hard work and doesn't happen quickly, but IMHO that should be their north star for 2026 - feel more centre of the universe.

I'll be going back, excited to see the next iteration, and hope to see you there too.

Upcoming Events

June 23-27: Toronto Tech Week, we'll be out and about for its inaugural incarnation.

July 9-11: Startupfest in Montréal.

September 24-25: ALL IN, Canada's largest AI conference in Montréal, where I'll be hosting the All In Talks stage again.

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AI startups in 2025 are throwing out the roadmap. In this episode, investor Ryan Henry shares what he’s seeing at the frontier: agentic workflows, founder-led experimentation, and why traditional product roles are fading fast. We also revisit a debate about “vibe coding” - intuition-led building in a world of moving targets.

📍 Key Moments

• 00:00 - Introduction to Ryan Henry and his family office VC approach

• 02:40 - Ryan's fund structure: investing in other funds for deal flow

• 07:12 - Different return expectations compared to traditional VCs

• 18:30 - Debating "vibe coding": what it is and its implications

• 21:32 - The evolution of AI-assisted development capabilities

• 27:10 - Concerns about rapid prototyping vs. proper customer discovery

• 33:30 - Current YC trends: AI agents, robotics, and advanced manufacturing

• 41:55 - The state of AI agents today and what they can reliably do

• 47:38 - Building companies with anticipation of improving AI capabilities

⁠Subscribe to my newsletter here to stay up to date on the new startup world⁠!

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New Episode: Enron

At the Consensus 2025 conference in Toronto, I discovered something unexpected: Enron - yes that Enron - the infamous energy company that collapsed in 2001 is being revitalized with a mission to solve America's energy crisis.

Connor Gaydos, best known for creating the viral "Birds Aren't Real" movement, shares his vision for transforming the disgraced Enron brand into a trusted energy provider focused on transparency, community, and innovative solutions to fix the electrical grid.

Some highlights for me:

• Rebranding disaster into opportunity: Connor bought the Enron brand post-bankruptcy and is reviving it as a transparent, trustworthy energy company in Texas.

• Memes meet megawatts: Connor’s past with the viral “Birds Aren’t Real” meme taught him the power of community and storytelling. Now he’s using that same memetic savvy to build a loyal following around Enron’s mission.

• Solving the energy crisis with grit and tech: The plan? Start as a retail energy provider in Texas with a focus on cleantech - batteries that store excess solar and wind power for peak hours - and scale from there. There’s even a beta micro nuclear reactor (“The Egg”) (!) in the pipeline.

• Crypto complications, but not just for cash: Enron tried a token offering to get the community involved, but ran into shady liquidity providers manipulating the market. The lesson? Trust and transparency are the only currencies that matter for long-term success - something that resonates with me.

• Fighting monopolies with attention and authenticity: Texas’s deregulated energy market is ripe for disruption, but entrenched players don’t make it easy. Connor’s strategy? Use the Enron brand legacy to get people talking, demand better service, and force regulators to sit up and take notice.

Check out the full episode - I'd love to hear your take on this.👇🏻

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Latest Episode: YouTube | Apple Podcasts | Spotify

Upcoming Events

Here's what's coming up, and do subscribe to our events calendar here.

May 27-30: Web Summit Vancouver, its inaugural conference in a new location. We'll be hosting a soirée - limited spots, check it out here.

June 23-27: Toronto Tech Week, where we'll have some announcements coming up soon.

July 9-11: Startupfest in Montréal.

September 24-25: ALL IN, Canada's largest AI conference in Montréal, where I'll be hosting the All In Talks stage again.

🔊

Subscribe: YouTube | Apple Podcasts | Spotify

Connor Gaydos, best known for creating the viral "Birds Aren't Real" movement, shares his vision for transforming the disgraced Enron brand into a trusted energy provider focused on transparency, community, and innovative solutions to fix the electrical grid.

With energy and Web3 investors, he shares his vision and journey to date, with a little bit of token malfeasance he discovered along the way.

0:00 - Consensus 2025 recap

3:01 - Meet Connor Gaydos, the new CEO of Enron

5:47 - Lessons learned from "Birds Aren't Real" and memetic marketing

8:46 - Enron's mission to fix America's energy crisis

11:12 - Innovative battery solutions to address peak energy demands

14:00 - How Web3 and community tokens fit into Enron's strategy

17:15 - Building trust with a historically distrusted brand

21:22 - The "Egg" - Enron's micro-nuclear reactor concept

24:28 - Taking on entrenched energy monopolies

29:46 - Building community through internship programs

31:31 - Lessons from cryptocurrency setbacks

33:34 - Enron's six-month roadmap to enter the Texas energy market

Connor explains how he's using memetic marketing to raise awareness about energy issues while building a legitimate business focused on battery storage, retail energy provision, and eventually micro-nuclear technology.

By attracting attention through the infamous Enron brand, he hopes to challenge the status quo in an industry that has lacked innovation and customer focus.

#startup #founder #entrepreneur #entrepreneurship #web3 #podcast

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New Episode: Austria!

This week, I had the pleasure of talking with Markus Raunig from AustrianStartups about all things European tech, and Austria in particular.

Here’s what Markus shared about the European and Austrian startup scene, and why you may want to take a closer watch / listen:

• Europe’s tech narrative is changing. For years, the meme was: America innovates, China duplicates, Europe regulates. But with fresh EU initiatives like the "one company" legal framework—essentially creating a virtual 28th state to simplify cross-border startups—Europe is pushing to attract top talent and compete on a global scale.

• Austrian startups thrive on stability and quality of life. Vienna has been named the most livable city in the world multiple times, combining affordable living with excellent infrastructure and access to talent from both Western and Eastern Europe. This unique geographic and cultural crossroads gives startups one of the best bases for European scaling.

• Entrepreneurship needs to be a mindset cultivated early. Markus draws a parallel to how Austria created a ski culture by teaching every child to ski. Now the focus is on early entrepreneurial education — giving young people the tools and mindset to take risks confidently, supported by a robust social safety net that empowers rather than encourages complacency.

• Austria balances social safety with economic dynamism. There’s a strong social safety net that allows risk-taking without the fear of losing everything. However, this can also breed complacency. The real work is in activating people to use that safety net as a launchpad to pilot their own ventures rather than stay passengers in life.

Check out the full episode for a deeper dive into Austria’s ecosystem, Europe’s startup ambitions, and the tradeoffs that are made. 👇🏻

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Latest Episode: YouTube | Apple Podcasts | Spotify

NACO Summit 2025

Last week I moderated a couple of panels at the NACO (National Angel Capital Organization) Summit in Ottawa, Canada the day after the election. The energy was palpable as it's obvious Canada itself is at an inflection point where Canadians have to the opportunity to choose their destiny and have unprecedented power to do so. Whether this time's the charm remains to be seen, but the innovation ecosystem is clearly ready to step up and make that change. How remains the billion dollar question.

Upcoming Events

Here's what's coming up, and do subscribe to our events calendar here.

May 15-16: The OOO Summit in NYC, created by events magnate Andrew Yeung.

May 27-30: Web Summit Vancouver, its inaugural conference in a new location. We'll be hosting a soirée - limited spots, check it out here.

June 23-27: Toronto Tech Week, where we'll have some announcements coming up soon.

July 9-11: Startupfest in Montréal.

September 24-25: ALL IN, Canada's largest AI conference in Montréal, where I'll be hosting the All In Talks stage again.

🔊

Subscribe: YouTube | Apple Podcasts | Spotify