Field notes on agent systems

Agent Harness

Engineering reliable coding agents through structured context, executable tools, cumulative memory, external evaluation, and disciplined feedback loops.

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Premise

The system around the model determines the ceiling.

Series index

Field-tested notes

Case studies and design patterns for agents that must improve continuously without losing reliability, traceability, or control.

Harness 02
Research NotesSelf-ImprovementEfficiencyMulti-Agent

Optimize What Transfers: Notes on Building a Self-Improving Agent Harness

What we tried before SoL-Pi, why we ended up optimizing token efficiency, and what the project taught us about thin harnesses, recursive improvement, and multi-agent systems.

From Harness 02 Core lessons
  1. 01Validate on tasks the search never saw.
  2. 02Judge a harness by the cost of solving, not by its size.
  3. 03Count new results, not iterations.
Harness 01
Case StudyValidationMemoryMulti-Agent

How a Coding Agent Reached the Global Top 10 on AgentTank in Under 24 Hours

How structured priors, shared failure memory, replay-driven iteration, and rigid validation gates took an AgenTank coding agent from unranked to a global peak of #7.