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[[{“value”:”Thanks to Neon for making this video possible, check it out here: https://get.neon.com/4dTo3CI
Can a harness built around a System One model like TypeSafe’s Jev make an AI agent better? I built one on Pi and Gemini 3.8 Flash, pointed it at a messy Postgres database full of traps, and ran 15 tests. The part that helped wasn’t the one I expected, and when the harness said no, the agent went looking for a way around it. Thanks to Neon for sponsoring this video: every agent run got its own throwaway branch of production.
Resources:
Neon: https://get.neon.com/4dTo3CI
TypeSafe / Jev: https://typesafe.ai
LangChain, Building a Harness with Jev: https://www.langchain.com/blog/building-a-harness-with-jev
Elvis Saravia’s Pi harness guide: https://x.com/omarsar0/status/2102762406204076532
Pi coding agent: https://pi.dev
Code: https://github.com/PromtEngineer/jev-harness
0:00 Custom Harness with Jev
1:28 System 1 vs System 2
1:53 What is Jev?
3:26 Architecture: Pi + Gemini + Neon
4:17 Decision point 1: the router
4:56 Decision point 2: the context picker
5:27 Decision points 3 & 4: gate and verifier
7:06 Demo: the Brightcart database
12:48 The gate and LangChain’s middleware
14:40 Cost, tokens and the verifier
15:46 Does it actually help?”}]] Read More Prompt Engineering
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