Builders Unscripted: Ep. 5 - Derya Unutmaz
Summary
A medical researcher with deep immunology expertise reveals how reasoning AI models like o1-preview represent an inflection point for scientific discovery—moving beyond literature synthesis to actually predicting experiment outcomes. She now starts each day with Claude, using AI-as-IDE to prototype complex simulations and biological models in hours instead of months.
Key Takeaways
- Reasoning models (o1-preview, o3) crossed a critical threshold that GPT-4 couldn't: they can reason through complex, multi-disciplinary scientific questions and provide trustworthy predictions about experiment outcomes—not just summarize existing knowledge.
- Use cross-domain metaphors to unlock AI reasoning: Derya framed immune-cancer dynamics as a 'battle royale game' to get o1-preview to generate novel immunology scenarios—proving that creative prompt structuring helps reasoning models break into new territory.
- AI-as-IDE democratizes prototyping for non-coders: what previously took weeks or months (building simulations, apps, games) now takes hours with Claude, enabling rapid iteration on ideas the moment they emerge—compressing development cycles by 10-100x.
- Medical/biotech founders should adopt early: Derya realized biology's complexity demanded AI in the 1990s (pre-deep learning), but the infrastructure only became usable post-ChatGPT. Early adopters with domain expertise have a multi-year window before commoditization.
- Build credibility through authentic community participation: OpenAI invited Derya to test o1-preview specifically because she was actively sharing insights on X about AI's potential for science—visibility + expertise = early access to cutting-edge tools.
Related topics
Transcript Excerpt
Derya, thank you so much for being here. Thank you. I'm very excited. Likewise. Very psyched to have you, because you're obviously a very unique kind of builder. Quite unlike the builders we usually talk to. You have a medical background, but you also work in, you know, bioscience, bioengineering, and you're pushing into AI in a way that, like most builders don't, coming at it with this real depth that you have in so many topics, like from biology to cancer to immunology. So very excited to dive in. Thank you. Thank you very much. Maybe the first question, like if you if we rewind, like, when did you first realize that biology and science were going to need AI? Yeah, I think that was, right after I graduated from medical school. When I realized the complexity of the biological system. In f…