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JevMade field notes / Control-flow comparison and infrastructure introduction

Choose between a small judgment and a multi-step agent

Avi Chawla separates Jev's bounded judgments from open-ended agent work and explains why both still need application-owned controls.

Original by Avi ChawlaAgent workflows

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Credits

“System 1 vs. System 2 Agent Harnesses, clearly explained” by Avi Chawla. Read the original source.

This expanded guide is an AI-narrated adaptation prepared by JevMade. It expands the source’s essential ideas, examples and caveats in JevMade’s own words and is not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

Our summary

A small decision and a multi-step investigation need different control flows. Avi Chawla explains a System One setup in which application code supplies a bounded question and uses the model's answer. A System Two setup lets a larger model propose successive steps as tool results change what it knows.

The distinction is not simply small model versus large model. Both setups leave tool permissions, spending limits and final execution with application code. HarnessRouter gives a product one way to start tasks, watch progress, share files and continue sessions across different coding services. Its small-decision path uses a separate controlling program.

A shared task interface does not make agents reason alike or guarantee their outputs. Self-hosting does not mean every model runs locally. The post links a longer setup article, but neither establishes a controlled accuracy or savings comparison. Cancelling work can stop future steps; it cannot undo an email already sent.

Key takeaways

  1. Use bounded judgments when the answers are known in advance, and a planning loop when the path must develop.
  2. Keep permissions, budgets and side effects under application control in both designs.
  3. Standardise task handling without pretending different agents have identical behavior or reversible actions.

HarnessRouter passes its small-decision tasks to SystemOneHarness, a separate code package. In its real-time mode, actions labelled as only reading data can run without reaching the usual certainty requirement. That label does not prove an action is harmless. Akshay Pachaar's linked article explains how tasks are handled. Neither source establishes measured savings, and cancellation cannot undo completed actions.

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