GoKawiilNew framework proposes three-part harness to keep AI agent loops from drifting
A developer builder describes a shift from simple test-pass/fail agent loops to a more structured 'harness' architecture for autonomous coding agents. The design separates a development agent that modifies a feature, a product agent that only sees what a real user would see, a behavior driver that simulates real requests, and a scorer/controller that identifies the next capability gap to fix, with repository state carrying lessons between sessions.
GoKawiil's interpretation of the reporting above, not reported fact.
As companies push AI agents to build features autonomously, simple pass/fail testing loops can mask real failures—like a UI that looks done but stores no data, or a right answer reached for the wrong reason. This proposed harness architecture matters because it addresses a core reliability gap in agentic software development: ensuring longer, faster agent iteration actually converges on correct behavior rather than just appearing to work.
- Basic test-pass/fail agent loops fail to catch failures outside predefined tests, like broken data storage or reward hacking.
- The proposed harness separates development context from what a product agent or user actually sees, preventing leakage.
- A controller uses evidence from a scorer to decide the next capability gap, with repository state preserving lessons across sessions.
Designing Data-Intensive Applications by Martin Kleppmann — If you're building harnesses and feedback loops that have to expose real failures rather than just green tests, Kleppmann's book is the classic deep dive into how systems actually break under load, state, and evolution. It pairs well with the article's point that the process around the feature is its own system worth engineering.
See Designing Data-Intensive Applications by Martin Kleppmann on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: jx0.ca — Jarred Kenny, 2026-08-29
Published there as: “Building Autonomous Goal Loops That Deliver”
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