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AI-Generated Docs and Tutorials

TL;DR

• AI can produce docs and tutorials quickly. It will get facts wrong, miss edge cases, and sound generic.
• Your job: verify, deepen, and add the details only someone who knows the product can add.
• Never publish AI output without review. Developer trust is hard to earn and easy to lose.

Docs are table stakes. Tutorials drive adoption. Both take time. AI can draft them — and that draft will have errors. Outdated API references. Wrong code samples. Missing "gotchas." Your readers will find them. Your job is to catch them first.

What AI Does Reasonably Well

Structure and flow:

• Getting-started guides, API overviews, step-by-step tutorials. AI knows the patterns.
• Use it for scaffolding. Replace the content.

Boilerplate and templates:

• "Here's a typical structure for an integration guide." Fine. You fill in the specifics.
• Don't waste time on format. Waste time on correctness.

Explanations of common concepts:

• "What is OAuth?" "What's the difference between REST and GraphQL?" AI can draft reasonable explanations.
• Still verify. AI will confidently state outdated or oversimplified things.

What AI Gets Wrong

Accuracy:

• API versions, parameter names, response formats — these change. AI trains on snapshots. It will hallucinate "current" behavior.
• Always verify against source. Docs, code, or the actual API.

Product-specific nuance:

• "When should you use our batch API vs. real-time?" AI doesn't know your product's trade-offs.
• Only you (or your team) can write that. Add it.

Edge cases and gotchas:

• "This works unless you're on the free tier" or "Note: this endpoint is rate-limited." AI tends toward happy path.
• You know the footguns. Document them.

Tone and audience:

• AI defaults to generic, slightly marketing-y prose. Developers want direct, scannable, honest.
• Edit for voice. Your docs should sound like your best support engineer, not a brochure.

The Workflow

1. Prompt with context — Product, audience, what you want to cover. Get a first draft.
2. Verify facts — Every API call, every example. Run the code. Check the version. Fix errors.
3. Add nuance — Gotchas, alternatives, "when not to use this." AI won't.
4. Edit for voice — Cut fluff. Add personality. Make it scannable.
5. Publish with ownership — Your name or your team's. You stand behind it.

When to Use AI, When Not To

Use AI for:

• First drafts of new sections
• Boilerplate (changelog templates, standard headers)
• Translating existing docs to new formats

Don't use AI for:

• Security-sensitive or compliance-critical docs
• Brand-new features (AI won't have the details)
• Anything you wouldn't feel comfortable defending in a support ticket

Do This Next

1. Generate one doc with AI — Pick a section you need. Get the draft. List every error or gap you had to fix. That's your QA checklist for next time.
2. Create a verification checklist — "Before publish: ran code samples, checked API version, added gotchas." Use it on every AI-assisted doc.
3. Establish a voice guide — 3–5 rules for your docs (e.g., "direct, no hype, code-first"). Apply them when editing AI output.