Loop engineering in Claude Code: keep documentation aligned with the codebase
Most teams do not have a documentation problem because they dislike writing. They have one because code changes continuously while plans, PRDs, feature notes, and runbooks have no reliable moment to catch up.
Coding agents make that gap more visible. A single session can update a feature, its tests, and several adjacent modules before anyone has reopened the original plan. The useful question is not “can the agent write documentation?” It is: can we build a repeatable loop that notices when the repository and its explanation diverge?
Two different meanings of “loop”
Claude Code’s underlying agent loop is the execution mechanism: the model evaluates the current state, calls tools, receives their results, and repeats until it returns an answer without more tool calls. The Agent SDK documentation describes this as a sequence of turns with controls for tool permissions, turn limits, budgets, and observability.
Loop engineering sits one level above that mechanism. As Addy Osmani argues , the leverage moves from writing the next prompt yourself to designing a system that repeatedly discovers work, assigns it, verifies it, records state, and decides what should happen next.
The agent loop gives an agent the ability to inspect and act. A work loop decides when it should inspect, what evidence counts, where the result is recorded, and when a human must make the call.
A practical example: the Documentation Drift Loop
Start with a narrow goal: surface documentation that no longer matches recently changed code. Do not start by giving an agent permission to rewrite every document in the repository.
Every two hours: inspect the newest changes
The short-cycle run compares the Git changes since its last successful checkpoint with the documentation that describes those areas. Its input can include the current diff, changed paths, recent commits, and selected documentation folders such as plans, PRDs, feature docs, and runbooks.
For each change, the loop should answer a small set of concrete questions:
- Does a plan or feature document describe behavior that the code no longer has?
- Has an API, configuration option, workflow, or ownership boundary changed without an accompanying explanation?
- Is the required documentation present but now ambiguous or incomplete?
- Is there enough evidence to propose a small correction, or should this become a review item for the team?
The output is not a sweeping rewrite. It is a compact drift report: the changed code, the related document, the suspected mismatch, and a suggested next action. If the evidence is clear, the loop may prepare a small patch or a draft PR; otherwise it should create a review item. Each run records its checked commit range and result in durable state so the next run does not rediscover the same work.
Once a week: review the whole picture
The two-hour loop is deliberately local. Its job is to catch fresh drift while the change is still easy to understand. The weekly loop has a different job: look across the repository’s history, unresolved drift reports, merged changes, and high-value documentation.
This broader pass can group related changes, highlight repeated omissions, and produce a short review packet for the team. It should call out documents that need a deliberate decision rather than a mechanical edit — for example, a PRD whose product intent changed, or an architecture note that no longer reflects ownership.
The cadence matters. Fast checks reduce surprise; slower reviews provide context. Treating both as the same task usually produces either noisy alerts or a weekly report that arrives too late to help.
Design the stopping condition before the prompt
A loop is only useful when “done” is observable. “Keep our docs current” is a direction, not a stopping condition. A better condition for a short-cycle run is: all commits since the previous successful checkpoint have been checked against the selected documentation, and every potential mismatch has a recorded disposition.
The loop should also have explicit limits:
- Scope: restrict the first version to known documentation locations and files related to changed paths.
- State: persist the last reviewed commit, findings, and human decisions outside the current conversation.
- Budget: cap turns, time, and spend. Open-ended instructions like “improve the docs” can run longer than intended.
- Permissions: begin read-only or draft-only. Let the loop propose changes before allowing it to create them.
- Verification: use a separate review step or agent to check the proposed finding against the diff and the document.
These constraints are not bureaucracy. They are what make a recurring agent useful on Monday as well as on the first impressive demo.
Keep the author and the checker separate
The model that found a mismatch is not the best authority on whether it is real. A second pass should verify the claim against the code, the document, and the intended scope. For high-impact documents, a human should still decide whether the proposed wording is correct.
This separation protects against a common failure mode: an agent sees a local implementation detail and “updates” a product document to match it, even though the code is the thing that drifted. The goal is alignment with intent, not documentation that automatically rationalizes every change.
Start small, then earn autonomy
The first useful version of this loop can be modest: read the Git range, inspect the related docs, save a report, and send it to review. Once its findings are accurate and its state is reliable, it can draft focused updates. Only after that should a team consider giving it broader write access.
That is the promise of loop engineering. You are not outsourcing engineering judgment to a timer. You are turning a recurring, easy-to-forget check into a visible system with evidence, limits, and an owner.
