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[ARTICLE · art-165168] src=ai-techwriter.com ↗ pub= topic=ai-tools verified=true sentiment=↑ positive

I use AI to draft software docs

A technical writer uses AI to draft software documentation by treating the model like an intern: assigning it source material from engineering tickets, product requirements and design documents, supplying the team's templates and style guide, then testing the resulting instructions against the actual UI, API or scripts before publishing. The writer asks the AI to flag gaps and conflicts in the source material, fixes simple edits directly, and updates the agent's instructions when it omits prerequisites so the same mistake does not recur in the next document; drafts then go to subject matter experts for review of edge cases and implementation limits. The writer says AI handles repeatable work such as copying information across documents and checking drafts against the full style guide, freeing time to understand the product and help users.

read2 min views3 publishedNov 6, 2026

I’ve been using AI to draft software docs. I treat it much like an intern: I give it an assignment, provide examples, check its work, and explain what needs to change. Whether it’s AI or an intern, I have to document those lessons for the next time.

Here’s how I use AI with software docs.

Start with the user #

Say I’m documenting a new security feature. I start with the person using it, often a security administrator. I assume they know security, but may not know our product.

What are they trying to do? What do they already know?

I need answers before I ask AI for a draft.

Give AI the assignment #

I gather information from engineering tickets, product requirements, design documents, and conversations with developers. The sources don’t always agree. Requirements change, and some decisions are never properly recorded.

I ask AI to flag gaps and conflicts. I investigate the ones that matter.

Then I give the agent our documentation templates and style guide, along with the source material. I want a draft that fits the way we document the product, not a new format invented for every feature.

Test what AI writes #

Now I try the instructions myself.

Depending on the feature, I work through the UI, call the API, or run scripts. Can I complete the task? Are the steps accurate? Did AI miss a prerequisite? Does the product behave as described?

Sometimes I find documentation errors. Sometimes I find a product issue. Sometimes testing reveals details beyond the source material.

This is where domain knowledge makes a difference.

Fix the draft – and the instructions #

I make simple edits myself. There’s no reason to rewrite a prompt just to fix a UI label or cut a needless sentence.

But if AI leaves out prerequisites, I update the agent’s instructions to check for them. Then I ask for another draft and see whether the change works.

This reminds me of working with an intern, or heck with a rebellious teenager. I can explain a mistake once, but with AI I need to put that explanation in the instructions. Otherwise, I may get the same mistake in the next document.

Get an SME review #

Once I’m satisfied, I send the draft to subject matter experts (SMEs) for their review.

I know the product well enough to explain the feature and challenge troublesome suggestions. SMEs make mistakes, too. I ask them to verify details I can’t confirm myself, such as unusual edge cases or implementation limits.

After that review, I make final changes and publish.

Why I use AI #

AI takes on repeatable work, including copying information across documents. That saves time I can spend understanding the product and helping users.

I’m not teaching AI to do my job. I’m teaching it to handle repeatable tasks. I also use it to check my work against our complete style guide.

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