New ventures that go totally in on artificial intelligence could potentially see growth and profitability within eight months, says the leader of one of Silicon Valley’s most storied startup incubators. They are “breaking the old math” when it comes to accelerating the time it takes to break into markets – or create new ones.
Budding entrepreneurs are learning to take advantage of what Garry Tan, president and CEO of Y Combinator, called “personal AGI” (artificial general intelligence), speaking at the incubator’s recent Startup School 2026 event. With personal AGI, he mused, business leaders and professionals can employ AI agents that are portable across all ventures and job roles. They run on their own infrastructure, compounding their knowledge over time, and dramatically increase their ability to act on ideas and build businesses.
Career strength is one aspect, and such capabilities also are emerging within startups being nurtured within Y Combinator. Personal AGI can just as readily help managers and professionals within established companies build new internal ventures – or strike out on their own.
This may sound like the usual over-the-top positive vibes coming out of the Silicon Valley bubble, but it’s worth looking at the inexpensive or even free resources available that now make innovation and business launches more of a reality to people across the world.
“Before you ever incorporate anything, before you have a co-founder or a logo or a deck, you can already be running an organization – an organization of one plus your agents,” Tan said. “When you sit down with an agent, you’re managing a workforce made of markdown” – or simplified text-based prompting, he stated.
During its most recent cycles, a majority of companies incubating within Y Combinator are building their structures using AI agent models. One company, Emergent, which was part of the incubator’s summer 2024 batch, “went from public launch to nine figures of revenue in eight months,” Tan related. “When they crossed $15 million in annualized revenue, they were 15 people.” Another startup, Retell, launched in the winter of 2024, recently hit $60 million annualized with about 40 people.
Such revenue per person was not possible so quickly until recently, Tan said. “Not in software, not in oil, not in railroads. And these aren’t freaks of nature. They’re the first companies built natively on the new physics, and every one of them started as one or two people. Founders are doing what used to be a person’s entire year of work.”
At least one in four of Y Combinator ventures now have codebases that were 95% AI-generated. The latest round of startups coming out of the incubator “is on track to becoming one of the fastest growing, most profitable batches in the history of YC,” Tan said.
Thanks to his own use of agents, Tan says he is personally 400 times more productive now than what he was 13 years ago when he was building his own startup. This productivity extends beyond coding to design, product management, and growth.
“You can build exactly the tool you need for the audience of one in a weekend,” Tan said. He outlines the following steps:
- Pick a harness and run an agent on your own machine. “I use OpenClaw and Hermes Agent with GBrain,” Tan said. “The intelligence is on tap, and there are many paths.”
- Start your library. It doesn’t have to be a grand archive, said Tan. “One folder of markdown files, export your notes, export your email if you can. Write one page about each project you are working on and each person you work with. And on those pages, write the things you actually know, what you’re building together, what they care about, what you owe them, what they said last time. That’s stuff no model on earth has because it only exists in your head.”
- Write your first skill file. Think about the task you do every week that you hate the most, Tan suggested. “It might be expense reports, meeting notes, weekly status updates, competitor research. That page is now an employee. Run it.”
- Wire the task up to be a recurring job. “The first time you wake up to work that finished while you slept, something shifts in your head permanently,” Tan related. “That’s the day that the day stops being the unit of work for you.”
- Never do one-off work. “Most people run one operation with one agent and then throw the context away,” said Tan. “They close the window. At the end of every task, ask the agent to ‘skillify’ what it did. Turn it into a markdown file you can use and reuse forever. The person who captures what they learn gets smarter every single day. ”
The main risk to an AI agent-built venture, especially for those in existing companies, is in who controls the skill files. “Those files may live in the company’s repo under the company’s IT policy,” Tan cautioned. “You may leave with nothing. The company keeps running your judgment without you. Forty files executing forever and her name isn’t even in the commit history.”
This has happened before in history, he related. “Craftsmen owned their tools. That’s what made them free. The factory broke that. The loom belonged to the mill. The knowledge workers assumed we were safe because our tools lived in our heads where nobody could confiscate them. Skill files end that. For the first time in history, your cognition can be extracted, stored, versioned, and owned. The only question is, by whom?”
That’s why it’s important to maintain ownership of your agentic workforce, he urged. Key is “an agent that runs on your infrastructure, reads from a memory you own, executes procedures you wrote, and compounds. Your personal AGI gets better every single day you use it because every day it knows more of your life.”
Technology and AI amplify entrepreneurial striving. “For most of history, almost all of that striving never got an audience. It died waiting for funding, waiting for headcount, waiting for permission, waiting for someone else to believe first.” AI agents, on the other hand, are “the first technology I’ve ever seen that lets the striving go straight to work.”
