I had an introductory meeting the other day with a California-based founder - thank you Boardy. As the founder was telling me about his startup and his MVP—which sounded genuinely interesting—I casually asked if he was raising capital. He stopped, shook his head, and said no, because that would be a waste of time until he had paying customers.
I had to chuckle and told him, “Nice to hear that California investors are catching up to Boston.” <ducking as I say that…>
The New Venture Reality
The current venture market is experiencing extreme concentration, with massive capital flowing into mega-rounds for frontier AI labs and data center infrastructure, while tens of thousands of ventures are struggling to survive. Both Mike Troiano and John Landry have recently written relevant pieces about this structural market shift, suggesting that the traditional venture playbook no longer works like it used to for many. Probably most.
The shift isn’t just about risk tolerance or market cycles—it’s driven by a fundamental rewrite of venture economics.
The New Reality: Validation Before Capital
The old playbook was to formulate an idea, raise a (pre)seed round from investors who you convinced to believe in it, use that capital to hire engineers to build a minimum viable product (MVP), and then hit the market to find out if anyone actually wanted to buy it.
Generative AI has shattered that model. These days, vibe coding platforms and intelligent agents have collapsed the cost and time required to build a working prototype down to, effectively, $0. What used to take six months and six figure engineering salaries can now be spun up over a weekend for the cost of some Claude Code tokens.
Since the cost of building has plummeted, the sequencing has inverted. Market validation now comes before capital, not after it. Code is no longer the bottleneck, rather the scarce resource is proof that customers are willing to pay for what you built. In other words, early-stage capital no longer buys existence; it buys speed, distribution, and scale. Putting capital into a business before verifying market demand is akin to pouring gasoline onto an unlit stove. You aren’t accelerating growth; you’re wasting resources - and risking an explosion.
Redefining Traction in an AI-First World
This forces a redefinition of what “traction” actually means at the seed stage. Traction is no longer a shiny functional app, a waitlist full of personal connections, or vanity metrics like app downloads and free tier signups. Traction today means real prospective customers saying, “This solves a problem I care about, and I will pay you to solve it”—and the ability to show transactions flowing through Stripe to prove it.
Startup creation becomes a rigorous customer discovery problem rather than an engineering challenge. Many founders still stumble here, because they are often builders. Building feels safe—it’s controllable, logical, and gratifying. Customer validation, by contrast, is uncomfortable. It requires stepping out from behind the screen, talking to complete strangers, designing unbiased tests, and avoiding the trap of polite, friendly feedback from people who don’t want to hurt your feelings.
Unfortunately more money won’t fix a founder who can’t clear this bar. It’ll just help them build the wrong thing faster.
The Shift in the Classroom
We are seeing this same trend playing out across top academic institutions nationwide. UC Berkeley’s Haas School of Business recently launched its AI Entrepreneurship course, designed as a hands-on accelerator for MBA founders leveraging AI to accelerate build cycles so they can focus heavily on commercial viability, market research, and customer adoption.
Entrepreneurship education must pivot toward teaching structured customer discovery, interview methodology, and quantitative validation techniques. When AI outsources the build step, teaching founders how to validate becomes the main curriculum.
Practical Takeaways for Founders
Those building a venture or preparing to pitch investors need to adjust their execution playbook:
Don’t raise to build — raise to scale. Treat fundraising as a catalyst for scaling a customer acquisition loop that you have already proven, not as a source of capital to fund R&D.
Treat your first 90 days as a validation sprint. Resist the urge to dive straight into IDEs or low-code builders during your initial quarter. Spend those 90 days conducting interviews, testing positioning, and getting clear signals on willingness-to-pay before writing code. Step back from the AI harness and go talk to some potential buyers.
Apply the “10 Strangers” rule. Before you consider reaching out to investors, force yourself to get 10 complete strangers—people outside your network, alumni group, or friend circle—to commit time or money to your solution. If you can’t convince 10 strangers, funding isn’t your blocker; your value proposition is.
Knowing What to Build Was Always the Hard Part
Returning to that founder I met with: his decision to forego fundraising until he had customers isn’t a sign of weakness, but a sign of modern founder maturity.
Building an MVP was never the true hurdle in entrepreneurship; it was simply the most visible and expensive one. Knowing what to build, and verifying that the world actually wants it, was always the real challenge. AI didn’t change that fundamental truth—it just stripped away the last remaining excuses to ignore it.
On that note, I’m back to the classroom myself this week. Fittingly, one of the courses I’m teaching this fall is oriented around Design Thinking, which preaches this discipline. You don’t start by writing code or polishing a finished product in a vacuum; you start with radical empathy for the prospective user, uncover their genuine pain points, and validate that someone actually cares before committing real resources. Looked at through that lens, maybe the venture machine isn’t "broken" after all. Perhaps the era of raising funding for an unvalidated prototype was the historical anomaly, and the market is simply correcting to how things should have worked in the first place.
I intend to keep writing here during the semester, but my teaching load has increased, so posting may be more sporadic. Either way I’m excited to be back, and confident that the insight and motivation I get from working with the next generation of leaders will help sharpen the sword here as well.