Y Combinator

Eric Ries, author of 'The Lean Startup,' discusses his new book 'Incorruptible,' arguing that shareholder primacy is a recent and destructive legal norm that causes good companies to lose their missions. He presents structural alternatives like Public Benefit Corporations, dual-class shares, and industrial foundation models to help founders protect their companies long-term. Case studies from Costco, Novo Nordisk, and Anthropic illustrate how mission-first governance structures outperform standard Delaware CC Corp practices.

OpenAI is offering $2 million in API tokens to every YC company in the spring and summer batches, invested via an uncapped SAFE at the Series A valuation. The deal is aimed at founders who are heavily consuming tokens to build AI-powered products rapidly. Applications must be submitted by May 25th, with decisions communicated by June 5th.

The speaker argues that AI enables companies to move beyond traditional hierarchical structures toward self-improving recursive AI loops. Rather than using AI as a productivity tool bolted onto existing workflows, companies should redesign themselves around AI-native systems that learn and improve autonomously. The talk uses YC's own internal AI systems as live examples of this paradigm shift.

Aadit Palicha, co-founder of Indian quick-commerce grocery startup Zepto, discusses how he turned down Stanford at 17 to build a 10-minute grocery delivery company during COVID-19, starting from a WhatsApp group in Mumbai. He explains how relentless customer focus, a pivot to dark stores, and obsessive supply chain optimization turned a neighborhood delivery experiment into a billion-dollar platform employing over 200,000 people.

A brief celebratory event in India drew an unexpectedly massive turnout, with over 25,000 applications received. Speakers expressed excitement about the energy in the room and optimism about India's AI future being shaped by the current generation of participants.

Paul Graham argues that ambitious founders should move to Silicon Valley, at least temporarily, to access superior talent networks, serendipitous meetings, and a unique pay-it-forward culture. He also contends that Swedish founders returning home after this experience—ideally through Y Combinator—are one of the best mechanisms for building Stockholm into the Silicon Valley of Europe.

Gary Tan, CEO of Y Combinator, describes how he returned to coding after a 13-year hiatus using Claude Code and AI-assisted development tools, shipping hundreds of thousands of lines of code while running YC full-time. He built Gary's List (a politically-focused blogging and research platform) and GStack (a collection of AI prompting skills), achieving what he estimates is 400x his previous coding productivity. He argues we are entering a 'personal AI' revolution analogous to the personal computer era, where individuals must choose between controlling their own AI tools or ceding that control to corporations.

Y Combinator is hosting Startup School Paris on June 29th, a one-day event bringing together builders and hackers from France and Europe. The event will feature founders from notable tech companies and provide direct access to YC partners and alumni. It is positioned as a celebration and cultivation of the next generation of European entrepreneurs.

Harshil Mathur, co-founder of Razorpay, discusses the company's journey from a side project to India's largest payments platform. He covers early struggles including a near-death experience when their bank partner pulled out, the strategic bets that drove explosive growth, and lessons on founder mode, capital efficiency, and adapting to AI.

Current GPUs are poorly optimized for agentic AI workloads, achieving only 30-40% peak utilization due to the bursty, multi-modal nature of agent execution loops. Purpose-built inference silicon designed around the agent loop itself represents a significant hardware opportunity. The speaker argues that compiler design, not just chip architecture, will be the critical differentiator for whoever builds this next.

The transcript argues that AI is transforming scientific discovery by enabling closed-loop autonomous research systems. Frontier AI models have reached PhD-level performance on scientific benchmarks and are beginning to run full design-make-test-analyze cycles in fields like drug discovery and materials science. The speaker predicts that the most impactful companies will build 'AI-native discovery engines' rather than simple research co-pilots.

The transcript argues that AI-native companies succeed by making their entire organization 'queryable' — capturing all meetings, tickets, and interactions into a unified AI layer. This transforms companies from open-loop to closed-loop systems, enabling continuous monitoring and adjustment. The speaker sees a major opportunity to build the connective infrastructure that makes this possible by default.

The transcript argues that AI has dramatically reduced software development costs, making legacy SaaS companies vulnerable to disruption. Startups are encouraged to build AI-native challengers targeting even the most entrenched enterprise software markets. The speaker frames this moment as analogous to the cloud transition that created the last generation of great software companies.

Adi Oltean, co-founder of Star Cloud, advocates for developing industrial capabilities in space, focusing on extracting raw materials and 3D printing structures on the moon. He highlights the efficiency advantages of lunar manufacturing and encourages related startups to apply to Y Combinator.

The transcript argues that AI agents represent the next trillion users of the internet and require purpose-built software infrastructure. Unlike humans, agents need machine-readable interfaces such as APIs, MCPs, and CLIs rather than visual UIs. The biggest startup opportunity lies not in building agents, but in building the software agents depend on.

The transcript discusses the significant gap in hardware iteration speed between the US and China, particularly Shenzhen's ecosystem. A few US startups are beginning to address this, but the overall infrastructure stack remains incomplete. The speaker signals strong investment interest in startups that can dramatically accelerate hardware development cycles.

YC visiting partner Francois Shaard discusses two 2025 AI papers—Hierarchical Reasoning Models (HRM) and Tiny Recursive Models (TRM)—that demonstrate recursion at inference time as a powerful alternative to simply scaling model size. A 7-million parameter TRM outperforms much larger LLMs on reasoning benchmarks like ARC Prize by leveraging recursive hidden states instead of chain-of-thought token generation. The conversation contrasts these approaches with traditional LLMs and RNNs, exploring why recursion addresses fundamental limitations in transformer reasoning.