Y Combinator

Venture Capital

109

Mentions

Podcasts

Episodes

Podcast consensus

Points of consensus

▶Y Combinator is aggressively integrating AI into its own operations, using a centralized database and hundreds of internal tools to power AI agents that improve processes, write code, and even autonomously deploy fixes overnight.May 2026

▶A significant majority of YC's portfolio companies are now AI-focused, with 80-90% of recent batch startups centered on AI and 95% using AI-powered developer tools to build their products.

▶Y Combinator has a clear investment thesis focused on "AI-native service companies" in sectors like law, insurance, and healthcare, believing they can achieve software-like margins and will constitute many of the largest companies founded in the next decade.

▶The firm's extensive data, particularly its single Postgres database and thousands of hours of recorded office hour sessions, is a critical asset that enables the effective training and operation of its internal AI systems.May 2026

Points of debate

▶While many claims highlight the success of YC-backed companies like Solugen and Billion to One, a quote from the founder of Lovable reveals they rejected a YC offer, viewing it as a "distraction and cause too much dilution," suggesting the program is not the optimal path for every startup.

▶There is a contrast between the historical view of AI as a productivity tool (e.g., making engineers 20% more productive) and YC's current philosophy, which posits AI as a revolutionary force that fundamentally reshapes company structures, makes software a commodity, and renders middle management obsolete.

▶The dominant LLM provider for YC applicants is in flux. While OpenAI's tools are mentioned as key infrastructure, recent data for the Winter 2026 batch shows Anthropic's API usage has surged to over 52%, surpassing OpenAI as the most used API among applicants.

▶Y Combinator warns startups against using generic AI-generated website designs that lack originality, yet its own design team heavily utilized AI coding assistants and AI video generation tools for its recent website redesign, indicating a nuanced view where AI is a powerful tool but requires strong human editorial direction.Apr 2026

Key themes

▶The Self-Improving Company: Internal AI TransformationMay 2026

Y Combinator is actively transforming its internal operations by building a sophisticated AI infrastructure. This system, built on a centralized Postgres database, includes a registry of over 350 tools and AI agents that review conversations, improve company descriptions, and even autonomously identify, fix, and deploy code.

Y Combinator is not just an investor in AI but a primary user, using its own operations as a testbed for the AI-native company structure it advocates for, giving it a unique advantage in vetting and advising its portfolio.

▶The AI-Native Service Thesis

Y Combinator is championing a new category of business: the AI-native service company. It predicts that AI will enable service businesses in massive markets like law, insurance, and logistics to achieve software-like gross margins (50%+) and that these companies, not traditional SaaS, will be among the largest founded in the next decade.

This investment thesis signals a strategic shift away from pure software plays towards tech-enabled services where the primary competitor is the cost of human labor, representing a multi-trillion dollar addressable market.

▶The AI-Driven Portfolio

The composition of YC's portfolio has dramatically shifted, with 80-90% of recent startups being AI-focused. The claims highlight a diverse range of AI applications, from biotech (Billion to One) and chemical manufacturing (Solugen) to developer tools (AgentMail, Scrappybara) and robotics (Physical Intelligence).

The sheer concentration of AI companies in YC's batches creates a powerful ecosystem and feedback loop, accelerating innovation and revealing market trends, such as the rapid shift in LLM API preference from OpenAI to Anthropic among new applicants.

▶Redefining the Future of Work and Corporate Structure

Y Combinator's leadership articulates a vision where AI fundamentally breaks the traditional hierarchical organization. They predict companies will become constrained by AI token usage rather than employee headcount, middle management will become obsolete, and the primary corporate asset will be accumulated business context, not the software itself, which is becoming a disposable commodity.

This forward-looking perspective suggests that the metrics for evaluating company efficiency and value are changing, with revenue per employee increasing dramatically and long-term defensibility shifting from proprietary code to proprietary data and processes.

Source episodes

Timeline

Since 2012

A quote claims that since 2012, 20% of 'super unicorns' were funded by Y Combinator, establishing its long-term track record in backing highly successful companies.

Approx. 18 months ago

This period serves as a benchmark for company efficiency. Since this time, YC has observed that companies reaching Demo Day generate approximately 5 times more revenue per employee, indicating a massive productivity leap driven by AI.

Approx. 1 year ago

Y Combinator began building its own internal harness for YC-specific AI agents, marking a significant step in operationalizing AI within the organization itself.

Early 2025

Anthropic's API had a 20-25% usage share among YC applicants, indicating it was a significant but secondary player to OpenAI at the time.

Late 2025

Discourse indicates a major shift in the AI development landscape, as Anthropic's API usage among YC applicants surged to over 52%, surpassing OpenAI for the upcoming Winter 2026 batch.

Winter 2026

This batch is characterized by an overwhelming focus on AI, with Anthropic as the dominant LLM API provider for applicants and portfolio companies like Confluence Lab achieving state-of-the-art benchmark scores.

Suggested prompts

How does Y Combinator's internal adoption of AI agents and a 'self-improving' operational model influence its investment thesis and the specific advice it provides to portfolio companies? &nearr;What are the primary risks associated with YC's 'AI-native service company' thesis, particularly regarding long-term defensibility against competitors if the underlying AI models are commoditized? &nearr;Given the rapid shift in LLM API usage among applicants from OpenAI to Anthropic, what does this signal about the evolving technical and product needs of early-stage AI startups? &nearr;How does YC's philosophy of treating software as a 'disposable commodity' impact the way its portfolio companies should approach building moats, intellectual property, and long-term enterprise value? &nearr;

Key concepts

AI-Native Services 1 ep Internal AI Agents 2 ep Portfolio Company Strategy 3 ep Future of Work & Org Structure 1 ep LLM API Usage Trends 1 ep Website Design & AI Tools 2 ep Investment Thesis 1 ep Corporate Governance 1 ep Founder Experience 4 ep Robotics & Physical AI 1 ep

Notable quotes

“Y Combinator is observing that companies reaching its Demo Day now generate approximately 5 times more revenue per employee compared to 18 months ago.”

Y Combinator · How to Build a Self-Improving Company with AI

“The primary value in a modern company lies in its accumulated business context and skills, not in the software itself, which is becoming a disposable commodity.”

Y Combinator · How to Build a Self-Improving Company with AI

“Anthropic has become the most used LLM API among applicants for the Y Combinator Winter 2026 batch, surpassing OpenAI.”

Diana · The Truth About The AI Bubble

“Lovable rejected an offer from Y Combinator because the founders felt it would be a distraction and cause too much dilution.”

Anton Osaika · Anton Osika, Co-Founder and CEO @ Lovable: Hitting 85% Day 30 Retention - Better than ChatGPT

Report last updated: Jun 10, 2026

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