Kiriti Badam
AI/ML Infrastructure Engineer at OpenAI (Codex) / Former Google & Kumo
Works on Codex at OpenAI with a decade of experience building AI and ML infrastructure at Google and Kumo, and has supported over 50 AI product deployments across startups and enterprises.
Dimension Profile
Key Themes
Episode Summary
Kiriti Badam, working on Codex at OpenAI, shares practical frameworks for building AI products successfully, emphasizing incremental deployment that starts with high human control and progressively grants more agency to AI systems. He illustrates through customer support automation examples how companies should start with AI suggestions to humans, then gradually let AI act autonomously as confidence builds, and argues that persistence through the pain of AI adoption is the new competitive moat.
Leadership Principles
- → Start small and build step-by-step — it forces you to think about the actual problem you're solving
- → Pain is the new moat: companies that persist through the difficulty of learning AI implementation win
- → Don't start with full autonomy agents on day one; begin with high human control and graduate complexity
Notable Quotes
"When you start small, it forces you to think about what is the problem that I'm going to solve. One easy, slippery slope is to keep thinking about complexities of the solution and forget the problem."
— On why incremental AI agent deployment leads to better products
"Persistence is extremely valuable. Successful companies right now building in any new area, they are going through the pain of learning this. Pain is the new moat."
— On what separates companies that succeed with AI from those that fail
"You don't start hiking Half Dome every day, but you start training yourself in minor parts and then you slowly improve. That's extremely similar to building AI products."
— Analogy for why you should start with minimal AI autonomy and build up
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