Agents
good framing from @ch3nweiii - a lot of agent steps are yes/no calls, not generation Jev answers those as typed questions with calibrated pr…
good framing from @ch3nweiii - a lot of agent steps are yes/no calls, not generation Jev answers those as typed questions with calibrated probabilities, so the frontier model sticks to the hard work w
good framing from @ch3nweiii - a lot of agent steps are yes/no calls, not generation Jev answers those as typed questions with calibrated probabilities, so the frontier model sticks to the hard work where those calls sit in a harness: https://www.langchain.com/blog/building-a-harness-with-jev https://x.com/ch3nweiii/status/2108664035109470637 whoever built this realized we've been using our smartest AI for the dumbest possible jobs your 20-200/mo frontier model is researching, writing code, planning… and then you're paying that same brain to decide YES / NO. Jev flips that. it's a tiny decision model that sits in fr…
Related
- I like this framing a lot: agent improvement is harness improvement, not model improvement The interesting interventions are often at the to…
- A great read from @LangChain Best framing I've seen for agent architecture. Every non-model piece like the filesystem, sandbox, compaction, …
- Free SemIf this week is useful. Typed outputs + probabilities look like a cleaner way to route agents than parsing LLM text every time.
Source: Harrison Chase (X) | 2026-10-10