The Key to Self-Improving Agents is a Verification Loop
fatih_koc · reddit · 2026-07-13
The author built an agent system designed not just to "complete tasks," but to actively improve its own pipeline. It continuously observes outcomes, decides on next steps, submits PRs for both products and its own code, and uses a ledger to mark every change as confirmed, rejected, or inconclusive—ultimately deferring to a human merge gate.
The key takeaway is that making this system work isn't about stacking complexity. It relies on controlling the context size for each run, delegating non-critical judgments to deterministic code, and avoiding bloated toolchains or massive skill files. The most crucial element is the verify step: without clear verification, the system accumulates unexplainable modifications, breaking the self-improvement loop.
The author concludes by asking the community: when building autonomous agents, how do you effectively close the "verification" loop to ensure the system actually learns rather than just executes actions?
Related event: Developer Creates Self-Improving AI Agent System(2 posts)→
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