Why Even Y Combinator Can't Crack the New Software Paradigm
What I am writing here will be a "Told you so" article in ten years.
Here's a number that should terrify every investor in Silicon Valley: 0.1%.
That's the unicorn rate for Y Combinator companies from 2020 to 2025.
Not their rejection rate.
Not their failure rate.
Their unicorn rate.
The most successful incubator in history - the one that birthed Airbnb, Stripe, and Dropbox - has produced exactly three billion-dollar companies from roughly 3,000 bets over the last five years.
Ramp, Whatnot, and Zepto.
Now before you say "unicorns take time" - I know.
BUT when you look at the heavy hitters out of YC.
Airbnb took 2.5 years. Stripe took 5. Coinbase took 5. The average YC unicorn historically takes about 3 years to hit that billion-dollar mark, with some lightning strikes like Brex getting there in 18 months.
But here's the thing: we're now 5 years out from 2020(that was fast). The 2020 and 2021 cohorts have had their full historic window. The pandemic cohorts - when everyone said digital transformation would accelerate everything - have had more time than DoorDash or Dropbox needed.
Compare that 0.1% to their historical 4-5% unicorn rate and you start to see the outline of something nobody wants to talk about.
This isn't about needing more time. The old playbook is dead.
Y Combinator's performance here isn't a fluke or a pandemic blip. It's what happens when the world's best incubator, with the world's best network, using the world's best playbook, hits a paradigm shift most of the world still doesn't fully understand.
The irony? YC knows this.
Sam Altman literally runs OpenAI. Paul Graham writes essays about AI transformation. But institutional knowledge is harder to change than code.
MIT just released a study (that everyone and their mother is quoting) showing 95% of corporate AI initiatives are failing.
Everyone's pointing fingers at implementation, at change management, at "resistance to adoption."
Honestly though, they're missing the real story. It's not that companies can't implement AI. It's that they're trying to buy half-baked AI solutions when their employees could build better ones themselves.
Think about what Y Combinator teaches. Move fast. Find product-market fit. Scale aggressively. Hire engineers. Build moats.
It's gospel in Silicon Valley, refined over decades of pattern matching. Paul Graham could probably recite the formula in his sleep. And it worked brilliantly... when software required engineers to build it.
But AI (when used correctly) isn't just another programming language. It's not Python 2.0. It's a compiler for human intent.
If you want to dive deeper into what I mean, I recorded a quick video the other day you can see here:
But if you didn’t watch the video, let me explain this the way I explained it to some Directors I am working with at the European Union last month.
When you write traditional code, you're telling a machine exactly what to do, step by step. If persona equals "conservative" and question equals "taxes," then return this specific output. Every edge case needs its own logic. Every possibility needs to be anticipated.
With AI, you're doing something fundamentally different. You're giving it context and letting it compile the solution. "Here's a conservative persona and a tax question - use context to generate the appropriate response." One instruction replaces hundreds of conditional statements.
This isn't just more efficient. It's a complete shift of how we can build software.
Y Combinator's startups are still hiring armies of engineers to write code that an AI could generate in seconds. They're still building features that should be prompts. They're still thinking software is a product when software is now disposable.
Here's what I mean: When I teach multinational enterprise teams how to use AI, I can show a non-technical person - someone who's never written a line of code - how to build their own agents with Copilot. While I am doing this, half the time I am busy teaching them what I learned in the two Accelerators I went through my self but instead on how to launch the product internally.
I am literally watching in real time huge cooperate teams launch a software product like a software company; non-technical teams taking their first major a course with me and less than two months later they have 200 other people piloting it in a company.
The crazy part is the software never leaves the company; they drop four vendors and move on.
In six weeks, they're creating what 20 YC startups are trying to sell them.
The expense tracking app? Built it in an afternoon. The workflow automation tool? Created over lunch.
The customer service bot? Karen from HR made three versions before picking her favorite.
Software isn't a moat anymore. It's a commodity you generate on demand.
Microsoft seems to get this better than anyone else right now. They're not selling simply selling software - they're selling the ability for every employee to create software. Copilot isn't a product; it's a software factory that fits in your Teams sidebar.
They understand that every business is held together with duct tape and spreadsheets, and instead of building better products to replace them, they're giving employees the power to orchestrate AI across that beautiful mess themselves. In real-time. Without IT's permission.
This is why some of those YC startups are dead on arrival. They're raising millions to build what Janet in accounting can prompt into existence during her coffee break.
And its only going to get easier for Janet to do that every month that goes by.
Now you may be asking, what about the three unicorns that did emerge from recent YC batches?
Look closer. Ramp isn't selling expense software - they're selling the financial intelligence layer that no employee could replicate. Whatnot didn't build a marketplace that anyone could prompt into existence - they built network effects. Zepto's 10-minute delivery isn't software - it's physical infrastructure that can't be wished into being with Copilot.
They succeeded because they understood what Microsoft and every enterprise is about to figure out: if an employee can build it in an afternoon, it's not a business. It's a prompt.
Let me give you a perfect example from MY own work.
(put my money where my mouth is so to speak)
In my research at Edinburgh, I built a pipeline that administered 10,000 psychometric tests to AI models. Complex stuff, right?
Download that notebook file and give it to Claude Code and I bet you it can make three versions of it for 10 different business cases and it would run fine.
That's not efficiency. That's obsolescence. Every YC startup building "AI-powered tools" is competing against their own customers' ability to build those exact tools themselves.
Everyone is building hotter fire, instead of building the stoves to control that fire.
This is why the MIT study shows 95% failure. Companies are trying to "implement AI" like it's Salesforce. They're hiring AI engineers like they're Java developers. They're building AI strategies like it's 2015 and they're choosing between Angular and React.
The successful 5%? They're not implementing AI. They're rebuilding their entire conception of what software is.
Stop creating solutions. Create solution-generators.
Stop thinking about B2B SaaS.
Think about B2E - business to employee - where every worker becomes their own developer.
The real opportunity isn't in what you build. It's in enabling others to build. The consultants who win aren't the ones who implement systems - they're the ones who spend six weeks teaching employees how to replace everything they were about to buy.
The value isn't in the software; it's in the orchestration of knowledge.
Most importantly, stop thinking traditional software is a product. Traditional Software as we know it is now a conversation. A prompt. A Thursday afternoon experiment by someone who's never coded before. This is not to say a new level of complex software will not exist but that’s a longer conversation.
The companies that understand this aren't pitching to CTOs. They're teaching employees to bypass IT entirely until its time to hand off what they built so IT can scale it.
Why raise $2M to build an expense tracking app when any employee with Copilot can build five versions and pick their favorite?
The 0.1% unicorn rate isn't a failure of Y Combinator's model.
It's proof that the entire concept of a traditonal software startup is becoming obsolete.
This is not disruption. It’s extinction. And it's happening inside every enterprise, one update at a time.
I keep using the term "traditional software" on purpose.
Because we're witnessing the same evolution that took us from photograph to film to video game - each layer didn't replace the previous one, it abstracted it into something unrecognizable.
A photograph captures a moment. Film sequences those moments into narrative. Games make those narratives responsive to intent. Each jump changes not just the medium but what's possible.
Traditional software - the kind you write line by line, deploy, and sell - is the photograph.
We're already in the film era where AI orchestrates those lines into dynamic flows.
But we're speeding toward the game era: software that doesn't exist until you need it, that builds itself in response to your intent, that's as unique as the conversation that creates it.
Most are still teaching photography in a world that's about to demand interactive experiences. The companies that survive won't be the ones building better software.
They'll be the ones who understand that software itself is becoming a new kind of medium entirely.