Closed-Loop Engineering for Production Agents
percoAi · reddit · 2026-07-13
The author proposes loop engineering as a concept better suited for production agents than "prompt engineering."
The core idea isn't getting the agent to complete a task perfectly on the first try, but designing the closed loop around it: observing execution results, diagnosing the initial point of failure, deciding whether to retry/recover/rollback/escalate to human intervention, and turning failures into reusable assets like traces, root-cause tags, eval cases, permission changes, recovery rules, or manual review checkpoints.
The author views this as an engineering discipline bridging observability, evals, workflow orchestration, SRE, and product operations, inviting others to share if they are practicing similar methods.
Related event: AI Coding Paradigm Debate: Is Loop Engineering Hype or Silver Bullet(5 posts)→
More from coding & agent
- HeyGen adds a media-sourcing skill for coding agents with 75k images and 10k tracks — HeyGen · 2026-07-22
- Agent search bottlenecks are now about variance, not raw latency — rohanpaul_ai · 2026-07-22
- LangSmith adds tracing for Pipecat, LiveKit, OpenAI Realtime, and Gemini Live — LangChain · 2026-07-22
- An MCP server signs every AI agent tool call into a verifiable Merkle chain — Funky_Chicken_22 · 2026-07-22
- Annotated transcript of a Claude Code team interview is now available — trq212 · 2026-07-22
- Claude Code skill uses 10 Markdown rules to make outputs ADHD-friendly — alex_verem · 2026-07-22