Documentation as AI On-Ramp

For teams looking to get started with AI — without going all-in on AI-generated code — documentation is the easiest place to begin.

During COVID, I left a comfortable role at an EdTech company after many years to join a startup. One of the accomplishments I’m most proud of from that transition wasn’t a feature launch or a system rewrite — it was documentation.

By the time I left, the team was able to operate without me. No technical questions. No late-night Slack messages.

I was able to fully focus on building a new platform because the knowledge lived in the system, not in my head — and the team was able to operate confidently without me.

That didn’t happen by accident. I spent most of my final 4–6 weeks writing, reviewing, and validating documentation.

Nobody becomes a developer because they’re excited to write docs.

But documentation is critical for:

• business continuity

• succession planning

• onboarding

• reducing hidden risk

This is also where AI shines.

If your team isn’t ready to trust AI with production code, start here.

Ask an AI tool to:

• scan your codebase and generate documentation

• surface architectural assumptions

• identify gaps in your testing strategy

• provide a security review

You’re not letting AI build the system. You’re asking it to help you understand the system.

That’s low-risk, high-leverage work — and it makes teams more resilient. If you’re figuring out how to introduce AI into your engineering workflow, this is the on-ramp I’d recommend.

How are you starting to use AI on your teams?

Originally published on LinkedIn — view the original post for comments and reactions.