Docs & Code Guide

Keeping docs accurate in fast-moving teams: shrink the surface, generate what you can, stamp what you verify

A team that ships weekly keeps documentation accurate with three moves, in order: shrink the surface until only content that must be manually maintained remains, generate everything derivable from a source of truth, and stamp whatever survives as manual with a visible last-verified date. The failing alternative is trying to keep a large hand-written surface current at shipping speed, which no amount of discipline sustains: the surface must get smaller and more automatic, not the team more diligent.

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7 min readFor startups whose docs lag the product by a quarter

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Move 1: shrink, and stop documenting what code says better

Every page is a maintenance liability priced at shipping speed, so the first move is deleting liabilities. Stop documenting things the code states authoritatively: config values, endpoint lists, environment variables, dependency versions. Retire design docs once the thing ships, marked as historical rather than maintained. Drop per-sprint process pages that describe how the team worked in March. What earns a manual page is judgment and orientation: why the system is shaped this way, what to do at 3 a.m., how a new hire finds their feet.

A concrete cut list comes from git: pages nobody has touched in six months are either stable reference, candidates for generation, or dead. The one-liner below surfaces them; expect the honest answer for a third of most wikis to be archive.

# Archive candidates: docs pages untouched in 180 days
cutoff=$(date -d '180 days ago' +%Y-%m-%d)
git ls-files docs | grep '\.md$' | while read -r f; do
  last=$(git log -1 --format=%cs -- "$f")
  [ "$last" \< "$cutoff" ] && echo "$last  $f"
done | sort

Move 2: generate what has a source of truth

Anything derivable should be derived: API references from the OpenAPI spec, schema docs from the database or dbt manifest, changelogs assembled from merged PR titles. Generated content is the only class that stays accurate at weekly shipping speed for free, because its accuracy is a build step rather than a habit.

Architecture diagrams are the highest-value generation target because they are the most expensive page to maintain by hand and the first thing a new hire opens. An AI agent connected to the Datadef MCP server can redraw the platform diagram from what it reads in the repository, invoked as one command after a merge or in a scheduled CI job; Datadef does not watch the repo, so the loop is explicitly agent- or CI-triggered, and the API key it needs comes with paid plans. Scope honesty: this covers architecture and data diagrams, not prose. For keeping written walkthroughs synced to code, a code-coupled tool like Swimm is the right category, and generated diagrams simply remove one whole class of manual updates from your surface.

The generated diagram then lives in your docs as one live embed rather than pasted screenshots, so every page showing it follows an edit within minutes, the pattern a single source of truth for architecture describes. The trade-off: embed URLs exist only for projects shared public, which confidential architectures may not accept.

Move 3: stamp the manual remainder

What survives moves one and two is small: runbooks, onboarding, architecture rationale. Small enough to stamp: each page carries a visible last-verified date and owner, updated by a minutes-long verification pass rather than a rewrite. The stamp does two jobs at shipping speed: it tells readers which pages to trust, and it makes staleness visible instead of silent, since an unstamped quarter is a flag anyone can see.

The protocol details live in documentation review cadence; the short version is verify, fix the five-minute lies, ticket the rest, stamp. On a shrunken surface this costs each engineer minutes per sprint, which is the only budget a fast team will actually pay.

What weekly shipping changes about the rhythm

At a weekly cadence, calendar-driven review is always too late, so events must carry the load: the release itself is the trigger. A 15-minute docs slot in the weekly release ritual, what shipped, which pages does it invalidate, who stamps them, closes the loop while the change is still in everyone's head. Teams that write release notes already have this moment; the docs pass is the same meeting doing double duty.

The same logic argues against docs perfectionism: a fast team's target is not a complete wiki but a small, current one, where living documentation covers the derivable majority and stamps cover the judgment minority. Completeness at the cost of accuracy is the losing trade, because readers forgive a missing page and do not forgive a lying one.

The three moves on one line

Delete what code says better, generate what has a source of truth, and stamp the small manual remainder at every release. Accuracy comes from a smaller surface, not a more diligent team.

FAQ

How do you keep product documentation in sync with what actually ships?

Three moves: shrink the documentation surface by deleting pages that duplicate what code states (config values, endpoint lists) and archiving dead ones; generate everything derivable from a source of truth (API references from OpenAPI, schema docs from the database, architecture diagrams regenerated from the repository); and stamp the small manual remainder with a last-verified date at each release. The release ritual itself becomes the update trigger.

What should a fast-moving team stop documenting?

Anything the code answers authoritatively: configuration values, environment variables, endpoint and dependency lists. Design docs once the feature ships, kept as dated historical records rather than maintained pages. Process pages describing how the team worked during a past quarter. What remains worth manual effort is judgment and orientation: architecture rationale, runbooks, and onboarding.

How do fast teams keep architecture diagrams current?

By regenerating instead of redrawing. An AI agent connected to the Datadef MCP server reads the repository and updates the diagram to match, run as one command after a merge or in a scheduled CI job. Nothing watches the repo automatically, so teams wire the call into the release ritual or CI. The diagram then appears in docs as a live embed URL, so every page showing it follows an edit within minutes.

Does docs-as-code solve documentation for startups?

It helps with the trigger problem, because docs living next to code can ride the same pull request, but it does not make hand-written content accurate at shipping speed. The bigger levers are shrinking the surface and generating from sources of truth; process alone gives a fast team well-versioned stale pages. Use docs-as-code for the manual remainder, not as the whole strategy.

What is the minimum viable documentation process for a startup?

Four elements: a docs surface small enough to fit the team's attention (delete or archive the rest), generated references and diagrams wherever a source of truth exists, a visible last-verified stamp on every manual page, and a 15-minute docs pass inside the weekly release ritual asking which pages this release invalidates. That is the whole process, and it survives deadline pressure because every piece costs minutes.