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Max Hodak: What Really Kills Deep Tech Startups?
Y Combinator· 2026-08-07 21:30
Infrastructure and Operational Efficiency - Startups outside of pure software must continuously purchase thousands of items, such as computers, microscopes, 3D printers, and printed circuit boards (PCBs)[11] - Hardware and deep tech iteration cycles generate substantial costs, such as **40,000 dollars** per wafer iteration and a **3 million dollar** annual research budget for a small team[26][27] - Internal software systems like Helix are developed to streamline workflows, purchasing, and manufacturing tracking, replacing commercial enterprise software to maintain execution speed[21][25][104] Talent Acquisition and Performance Review - Recruitment processes involve multi-step evaluations, starting with initial application reviews where **17%** of top-of-funnel applications advance to phone screens[40] - Performance management utilizes Eigen reviews (a PageRank-inspired graph algorithm) instead of traditional annual HR reviews to evaluate employee contributions continuously based on peer voting[51][53] Funding and Financial Strategy - Deep tech companies require careful runway estimation, often raising **twice** the capital calculated for the next critical value inflection point to account for experimental uncertainties and waste[120][121] - Organizations aggressively pursue revenue generation and long-term sustainability alongside ambitious research roadmaps to overcome the slow financial decline typical of capital-intensive sectors[123][124] Medical Technology and Innovation - Brain-computer interface (BCI) and neurotechnology developments serve as radical longevity and healthcare stories, delivering profound effect sizes and clinical results compared to conventional pharmaceuticals[111][112] - Retinal prostheses integrate solar cell microchip implants with camera-equipped glasses and laser projectors to bypass damaged rods and cones, achieving significant clinical milestones such as patients completing **300-page** novels[4][5][6]