Unify CTO breaks down cutting agent costs 95% before launch
brandon_galang · x · 2026-08-29
LangChain's Max Agency podcast interviews Unify co-founder & CTO Connor Heggie. Unify builds agents for go-to-market teams — giving every sales rep "an engineer in their back pocket" rather than replacing reps. Key topics:
- Cutting inference costs 90-95% two weeks before launch
- The 15-requests-per-second ceiling hidden inside OpenAI's prompt cache
- Optimizing prompt caching hit rates; fork vs child subagents
- Why your LLM judge must be a different model family
- The Speed Audit: why one row at a time beats a table of 1,000
- Why Unify's subagents are just a function call, and ditching full VMs for a Python REPL
- Locking memory to keys instead of letting the agent freestyle
- What self-driving work taught him about running evals
Related event: Unify CTO Explains Slashing AI Agent Costs by 95% Before Launch(3 posts)→
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