Y Combinator

Patrick Collison discusses Stripe's founding story, the importance of concrete customer problems, and shares data suggesting it's the best time ever to start a business. He argues that despite AI advancement, there will be many winners rather than centralization, and emphasizes the value of deep learning alongside AI tools.

This YC Paper Club event focused on chip and kernel specialization in AI systems, featuring discussions on multi-GPU kernel optimization, energy-efficient inference, AI-generated kernel code, heterogeneous inference hardware, and GPU-accelerated game engine simulation. Speakers explored how specialization across hardware, software, and algorithms can dramatically improve efficiency and performance across different AI workloads.

Blake Scholl, founder of Boom Aerospace, discusses building the first independently developed supersonic jet by applying software development principles to hardware manufacturing. He argues that startups can compete in regulated industries by building solutions that solve regulatory concerns, and emphasizes that passion, iteration, and vertical integration are key to breakthrough innovation in deep tech.

Boris Cherny, creator of Claude Code, discusses how Anthropic's Opus 5 model represents a major leap in AI capabilities, requiring a fundamental rethinking of how to build AI products. Rather than accumulating complexity, successful builders must regularly delete system prompts and code to "unhobble" the model, allowing it to tackle increasingly complex tasks like rewriting entire codebases and maintaining software automatically.

The speaker argues that API communication is fundamentally broken across the industry, with breaking changes and new features going unnoticed. Since agentic coding tools have proven viable and developers accept external tool access to codebases, API providers should automatically apply changes to customer code rather than just announcing them—similar to how Dependabot works for dependencies.

YC partners discuss what makes startups durable in the AI era, emphasizing that while AI reduces software development costs, founders must focus on harder problems with defensible moats, maintain direct customer contact, and prioritize co-founder relationships for emotional and strategic support. They argue that pure software businesses are no longer durable and that the pace of AI improvements means cost concerns will self-resolve within 6-12 months.

Deepfakes and AI-generated voice clones have made digital fraud increasingly sophisticated and harder to detect, with a recent $25 million wire fraud involving deepfake video call participants exemplifying the problem. The traditional trust signals of seeing faces and hearing voices are no longer reliable, necessitating a fundamental rebuild of the internet's trust layer to verify that humans—not AI—are on the other end of communications.

Alex Lebrun, CEO of Amilabs, discusses his journey building multiple AI startups and explains why world models—AI trained directly on sensory data rather than text—represent the next frontier beyond large language models. He argues that being early in technology requires specific founder strengths, and shares lessons on ambition, fundraising, and the challenge of managing a $1.2 billion seed round.

Eric Landau, co-founder of Encord, discusses his career trajectory from particle physics to quantitative trading to founding a data infrastructure company for AI. He explains how Encord pivoted from general vision AI to focus on Physical AI, which he believes will be a massive market as robotics proliferates across manufacturing, logistics, and autonomous vehicles.

Traditional software for physical-world industries like construction and fleet operations hasn't evolved in 20 years, but AI agents, robots, and wearable-equipped humans now create a new operating system opportunity. These new systems will manage human and robot labor together, capturing end-to-end work data that incumbents lack, while operating in industries that spend 10-100x more on labor than software.

Jay Vineet, CEO of OpenCode, discusses how his open-source coding agent reached 13 million monthly active users and $40M annualized revenue in just 8 months by offering free access to coding agents globally and a cheap subscription tier for real work. He shares how being blocked by Anthropic's Claude Code actually accelerated growth, the company's unique insights into model usage patterns, and his 16-year journey building the same legal entity through multiple failed startups before finding product-market fit.

PhotoRoom founders discuss how YC transformed their ambition from a vague dream to concrete billion-dollar thinking, and share tactical strategies for European founders to overcome cultural barriers to ambitious goal-setting. They emphasize that depth in focus and hiring ambitious people are keys to achieving exponential growth.

Y Combinator is increasingly bullish on crypto despite current market downturns, expecting more startups to integrate crypto infrastructure for capital raising and payments. The firm argues that bear markets attract serious builders focused on real innovation rather than speculative gains, and highlights emerging opportunities in stablecoins, trading infrastructure, and financial rails.

By 2030, one in five Americans will be over 65, creating a massive caregiver shortage with millions of unfilled jobs. AI-powered technologies like conversational voice interfaces, monitoring systems, robotics, and care coordination software present new opportunities to support aging populations and family caregivers.

Stan Houlé, CEO of Dust, discusses building a model-agnostic AI platform for enterprise work in competition with frontier labs like OpenAI and Anthropic. He shares insights on company building, fundraising strategy, pricing models, and maintaining defensibility in a rapidly evolving AI landscape.

AI represents the biggest platform shift since mobile and web, with intelligence now becoming capable and affordable enough to power consumer products at scale. The speaker argues that the optimal time to build AI-powered consumer applications is now, as costs are falling 10x annually and whoever builds first will establish market dominance across all major consumer categories.

The speaker advocates for a new cloud platform designed specifically for small software—purpose-built tools for individuals and small teams. Current cloud providers like AWS and Azure are overly complex for these use cases, and a simpler alternative could unlock new possibilities, particularly with AI agents, while addressing security and sharing challenges.

Secretary of the Army Dan Driskill announces a major overhaul of Army acquisition processes, calling for innovative startups to develop modular, commercially-based defense solutions including low-cost interceptors, advanced sensors, drones, and logistics systems capable of operating in extreme global environments.

James Hawkins, CEO of PostHog, discusses how the company pivoted from product analytics to building AI-native self-driving software that autonomously identifies and fixes product issues. He argues that ambitious startup ideas are actually easier to sell and fund than narrow solutions, emphasizing the importance of shipping quickly, maintaining strong co-founder partnerships, and targeting remarkable rather than unremarkable products.

The video explains how world models—neural networks that predict future states of an environment given actions—could solve AI's sample efficiency problem and potentially unlock AGI. By learning to simulate environments like humans do, AI systems could train policies on synthetic data rather than requiring millions of real-world examples, as demonstrated in recent robotics and gaming applications.