Loop Engineering
Building out the supporting infrastructure around a bare agent loop -- scheduled automations, worktrees, skills, plugins, subagents, and memory -- so that a simple 'run until the goal is reached' loop becomes a dependable, self-correcting coding harness.
Context
Loop engineering was named by Addy Osmani in his essay “Loop Engineering” and covered on Episode 30 of the ADI Pod. It starts from the Ralph loop — a /loop that runs an agent over and over until a goal is reached — and names the pieces that turn that bare loop into a real harness:
- Scheduled automations (the “heartbeat”) that run on a timer and do discovery and triage on their own.
- Worktrees so multiple agents can work the same repo without stepping on each other. The industry consolidated here after early Gas Town used multiple full copies of the repository.
- Skills that write down project knowledge the agent would otherwise guess at — the main defense against hallucination and against an agent thrashing without learning from past mistakes.
- Plugins and connectors so the agent can reach past the local filesystem to external systems.
- Subagents, where the load-bearing move is to split the agent that does the work from the agent that reviews it.
- Memory — a markdown file, a ticket board, anything that persists outside the core loop.
By this definition, both the Codex app and Claude Code are already full loop-engineering harnesses; the term is more generic than any one implementation.
Why It Matters
Shimin’s framing on the show traces a progression in how developers direct agents: prompt engineering (tell the agent what to do) → spec-driven development (define the end goal precisely) → loop engineering (keep the goal looser, but bake your judgment into reusable skills and tools). Because the loop turns out so much more code, it amplifies whatever judgment you implant: the metaphor on the episode ran handsaw → table saw (“watch your fingers”) → tree-harvesting heavy machinery, where a mistake risks far more.
The drawbacks Osmani names are the ones the show keeps returning to: verification still falls on the developer (skip it and the output drifts), and cognitive debt bites hardest when a self-running loop breaks at 3am and no one understands the repo anymore.
Related Concepts
- The middle loop — the human work of overseeing agents, parts of which loop engineering automates
- Cognitive debt — the accumulating risk when a loop produces code no human has read
- Workflow automation convexity — the economic backdrop: workflows that approach full automation flip suddenly, not gradually