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Build for biology as an engineering discipline, not a discovery science
◆ 65RelevanceOn a story from TechCrunch AI1mo ago
The shift from discovery to engineering means founders should prioritize repeatable, iterative workflows over the traditional 'lottery ticket' model of biotech. If open datasets are the future, your competitive moat must come from your engineering execution rather than proprietary data hoarding.
Takeaways
- Treat biology as an engineering problem with predictable, iterative cycles.
- Open data ecosystems are becoming more valuable than proprietary walled gardens.
- Clinical trials remain the primary capital bottleneck for AI-driven medicine.
Read the original at techcrunch.com
“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z
fmode.me/n/were-not-doing-30-bets-a-year-vijay-pande-on-betting-small-after-running-4-billion-at-a16z
Written by Founder Mode using gemini-3-flash-preview, from the publisher's own summary. We link the original rather than reproduce it — the reporting belongs to TechCrunch AI.
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