Y Combinator

Ask These Questions Before Starting An AI Startup

Jordan Fisher

Founder and alignment researcher Sam Altman warns that the imminent arrival of AGI within two to three years forces startups to radically rethink hiring, product design, and long-term strategy beyond traditional focus models. He argues that enterprises will soon bypass external SaaS providers by building internal software with AI, while consumer markets may shift from static apps to on-demand, AI-generated solutions that require new trust mechanisms like automated auditing. Ultimately, Altman urges founders to prioritize solving hard infrastructure problems and societal impact over immediate monetization, as the window to build defensible moats against commoditization and centralized control narrows rapidly.

The 7 Most Powerful Moats For AI Startups

Jared, Diana, Gary, Tiana, Harjit

Founders now treat defensive moats as existential necessities to combat margin erosion, prioritizing execution speed and specialized engineering over traditional growth hacks. Key strategies include securing non-arbitrageable assets like regulatory approvals, leveraging deep workflow integration to create high switching costs, and adopting "work completed" pricing models to bypass incumbents' automation cannibalization traps. Ultimately, these tactics focus on emerging as sustainable advantages only after validating solutions to critical customer pain points, rather than relying on long-term strategic forecasting.

Early Decision for Students

Y Combinator is launching an "Early Decision" track specifically for graduating seniors to apply during their final year of study, securing guaranteed funding and a spot in the Summer 2026 batch. This program eliminates the immediate pressure to interview for traditional employment by providing financial support and a committed place in a future cohort before graduation. By allowing founders to receive capital and enrollment immediately, the initiative enables students to focus entirely on building their startups while completing their degrees.

Why Now Is The Best Time To Build In Crypto

Harj Taggar, Jesse Pollak

Led by Base founder Jesse Pollock, industry leaders declare a new golden age for crypto building driven by mature infrastructure that has reduced transaction costs to near zero and achieved regulatory clarity through legislation like the Genius Act. This environment enables a shift from legacy financial systems to programmable, censorship-resistant networks where stablecoins facilitate global access and tokenization allows creators to retain ownership of their capital. As a result, Coinbase and Y Combinator are prioritizing technical founders who apply these scalable Layer 2 architectures to solve real-world problems, signaling a surge in high-quality engineering teams ready to integrate AI and financial services over the next 18 months.

Don’t Be Afraid to Talk About Price

This analysis challenges the common founder hesitation regarding willingness-to-pay discussions, arguing that such dialogues are essential for validation rather than customer deterrence. Vendors are advised to explicitly link specific problem-solving capabilities and agreed metrics to customer valuation to effectively frame these inquiries. The primary strategic outcome of this approach is the early disqualification of prospects who lack financial readiness or the willingness to purchase.

"Startups only exist to find product-market fit."

The presentation argues that early-stage startups must prioritize discovering Product-Market Fit over mimicking the operational structures of established enterprises. It warns that founders who prematurely adopt enterprise-level functions, large offices, or redundant departments incur unnecessary costs that distract from core execution. Consequently, the most effective pre-funding strategy involves maintaining a lean team of two to three founders and a single engineer dedicated solely to validating market demand.

The Future of Software Creation with Replit CEO Amjad Masad

Amjad Masad, Chinat, Shivam, Sophia, Emma

Replit outlines a strategic pivot toward making software engineering obsolete by developing autonomous agents that operate within a robust, sandboxed cloud infrastructure capable of end-to-end testing and self-healing. This transition aims to shift software value from expensive SaaS applications to near-zero-cost, prompt-driven creation, enabling individuals to act as sovereign entities that assemble teams and deploy full-stack solutions instantly. By achieving near-full autonomy in the next agent generation, the platform intends to dismantle traditional corporate hierarchies in favor of on-demand, mission-based networks where human creativity complements agent-driven execution.

Agency and Independence

As AI systems surpass humans in executing instructions, the traditional higher education focus on attendance and procedural compliance is becoming obsolete. Future academic value must instead prioritize the cultivation of independent judgment and self-directed action. Developing personal agency is now the critical differentiator required for success in a post-AI workforce.

The FDE Playbook for AI Startups with Bob McGrew

Bob McGrew, Jared

Originating at Palantir to solve intelligence agencies' workflow opacity, the Forward Deployed Engineer model embeds analysts and prototypers at customer sites to drive product discovery through high-touch, outcome-based engagements. This strategy has rapidly spread to the AI sector, where over 100 startups now hire FDEs to bridge the gap between generic large-scale models and specific enterprise needs while securing contracts tied to delivered value rather than usage. As OpenAI’s Bob McGrew observes, these on-site teams function as essential execution layers that extract practical utility from rapidly advancing technology, positioning human ingenuity and adaptive implementation as the primary drivers of market adoption.

Michael Truell: Building Cursor At 23, Taking On GitHub Copilot & Advice To Engineering Students

Michael Truell, Diana Hu

Founded by MIT graduates led by Michael Truel, Cursor pivoted from failed ventures in CAD and encrypted messaging to launch a custom AI-driven code editor in late 2022 with an aggressive vision to automate the future of software development. Leveraging a strategic shift to API-based models and a product-led growth approach, the team scaled rapidly from one million users in 2023 to over 100 million in 2024, capturing approximately 80% of YC batches. This rapid adoption was driven by features emphasizing codebase awareness and speed, reinforcing the founders' long-term outlook that AI will transform the industry into a collaborative ecosystem where programming fundamentals remain critical for reviewing and editing AI-generated logic.

OpenAI vs. Deepseek vs. Qwen: Comparing Open Source LLM Architectures

Ankit Gupta

OpenAI, Alibaba Cloud, and DeepSeek have each launched significant open-weight language models featuring distinct Mixture of Experts architectures and advanced long-context capabilities. While OpenAI's GPT-OSS prioritizes inference efficiency on consumer hardware, Alibaba's Qwen 3 introduces flexible dense and sparse variants with dual reasoning modes, and DeepSeek's V3.1 achieves superior memory efficiency through Multi-Head Latent Attention. Despite differing engineering strategies for scaling and alignment, all three families demonstrate comparable performance benchmarks derived from trillions of tokens and complex post-training pipelines.

AI won’t make coding obsolete. It will make it universal.

The speaker challenges the narrative that AI automation makes learning coding obsolete by citing historical precedents where easier tooling, such as the shift from punch cards to high-level languages, ultimately expanded the number of programmers. Arguing that accessibility drives adoption rather than replacement, the presentation advocates for cross-functional upskilling among leaders like CFOs and recruiters to enhance their specific job functions. This approach anticipates a future where broad coding literacy empowers everyone to code, resulting in significant productivity gains across all organizational roles.

How This 25-Year-Old Built A $675M Legal AI Startup (With No Legal Experience)

Gustaf Alströmer, Max Junestrand, Mark Mandelmann, Martin Splitt

Founded in 2024 by Max Giunestrand, Legora is an AI-powered workspace for legal professionals that recently secured an $80 million Series B funding round led by Iconic and General Catalyst. The company differentiates itself through a "software + service" hybrid model and a data-centric architecture that ensures GDPR compliance by hosting all European client data within the EU. With a flat organizational structure that scaled from ten to 100 employees in less than a year, Legora is aggressively expanding its operations to hubs in New York, London, and Stockholm to support law firms in navigating the AI transition.

Technical Expertise is Now the Missing Piece

A growing gap between AI's theoretical potential and practical deployment has established technical expertise as the primary constraint in the current landscape. Y Combinator observes that college students now outperform experienced PhDs and industry veterans in model proficiency, driven by their mastery of engineering practice over theoretical knowledge. These students demonstrate a unique ability to consistently extract maximum performance from AI models, a skill that often eludes senior experts.

Intellectual Fearlessness

Dr. Fei-Fei Li

World Labs CEO defines the company's hiring philosophy around "intellectual fearlessness," prioritizing candidates who demonstrate the courage to fully embrace difficult problems and pursue autonomous solutions with complete commitment. This approach draws from the CEO's past observations of high-performing peers, identifying the trait as the primary differentiator for success rather than traditional background metrics. By focusing exclusively on this core characteristic, the organization aims to cultivate a team capable of tackling complex challenges without hesitation.