Why I Stopped Asking Founders How Long Their MVP Took
AI did not just change the tools. It changed the timeline, the team size, and the economics of building.
👋 Merhaba, I’m Burak. Each week, I share lessons from 26+ years of building, investing in, and mentoring startups across emerging markets, from the early internet days to today’s AI revolution. 🧿
Lately, in my calls and meetings with founders through the fund, I keep seeing the same shift.
It is no longer taking the same people, the same time, or the same money to build and test a product.
What also makes me confident about this is that I keep hearing the same thing from smart people in the ecosystem. Not just founders, but operators and podcasters who are close to the work every day.
Two podcast episodes made this very clear to me recently.
One was Marily Nika on Lenny’s Podcast, where she explained how she moves from idea to user research to PRD to prototype in a very short time by chaining AI tools together. The other was Greg Isenberg on Startup Ideas, where he talked through the collapse in build costs and the new startup patterns emerging because of it. Different people, same signal.
The old product-building playbook is breaking.
Here is what founders should understand now.
1. The timeline has collapsed
The old sequence was simple.
Have an idea.
Hire developers.
Build an MVP over a few months.
Launch.
Hope people care.
That sequence is getting weaker by the month.
Isenberg described it as the “one-hour company stack.” Idea in the morning, something built minutes later, a working version shortly after, first users the same day. That sounds exaggerated until you look at what founders are already doing with tools like Claude Code, Replit, and v0.
Marily Nika showed the same shift from a different angle. Her workflow is not “think for weeks, then start.” It is tool hopping: Perplexity for research, a custom GPT for PRD generation, v0 for prototyping, and other tools to turn the work into something presentable fast. The whole flow is compressed.
This does not mean every serious product can be built in a day.
It does mean founders no longer have a good excuse for waiting three or four months before testing whether anyone cares.
Bad: Spending months building an MVP in stealth.
Good: Shipping a working version quickly, testing it with real users, and deciding fast whether it deserves more time.
The founders still working on old startup timelines will lose to founders who treat product building like rapid testing.
2. One person can now do what a small team used to do
This is the second big shift.
A founder or product person can now do work that previously required a team: research, writing specs, building prototypes, iterating, and even preparing stakeholder-ready material.
That changes the early-stage equation.
You do not need to raise money just to find out if the problem is real.
You do not need a full team before you know if users care.
The bottleneck moved from resources to judgment: choosing the right problem, reading user signals correctly, and deciding what to build next.
Bad: “We need $500K to build the MVP and validate the market.”
Good: “I tested three versions this week. Version two got traction. I am doubling down there.”
I am already seeing this in founder meetings. The stronger founders are shipping before they start fundraising.
3. The business model is shifting too
This is where the story gets more interesting.
AI is not only changing how products are built. It is changing how they are sold and priced.
One of Isenberg’s strongest points was that vertical AI does not tap into software budgets the same way vertical SaaS did. It taps into labor budgets. In other words, if your product replaces work a person used to do, the pricing logic changes.
That is why outcome-based pricing matters more now.
Not per seat.
Not per user.
But per result.
Per resolved ticket.
Per completed workflow.
Per qualified lead.
Per task done successfully.
Gartner expects 40% of enterprise SaaS to shift toward outcome-based pricing by 2030, while seat-based pricing is expected to decline from 21% to 15%. Those are not small changes. They point to a different economic model.
This changes the product question too.
The old question was: will customers subscribe?
The new question is: does this agent or workflow actually do the job well enough to replace cost, time, or headcount?
If it does, the value is obvious.
If it does not, clever pricing will not save it.
4. When building gets cheaper, distribution matters more
This is the part many AI-excited founders still underestimate.
If everyone can build faster, then building itself becomes less defensible. The advantage moves to distribution, trust, access, and existing audience.
You can build something impressive in a weekend.
That does not mean anyone will see it.
This is why I think distribution matters more than ever right now. The founder with the better channel, customer base, email list, community, or trust edge is often in a stronger position than the founder with the slightly better AI product.
That does not make product irrelevant.
It just means the moat is shifting.
The tools are becoming easier.
The models are becoming accessible.
The build cost is falling.
What remains hard is choosing well, reaching the right people, and earning trust fast enough to matter.
That is what I am paying more attention to in founder conversations now.
What part of your product process has AI changed the most for you — and where do you still feel the old bottlenecks?
🎧 Sources I referenced in this post:
Marily Nika — “PMs who use AI will replace those who don’t” on How I AI (Lenny’s Podcast)
Greg Isenberg — “23 AI Trends Keeping Me Up at Night” on Startup Ideas Podcast
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