Show HN: I built an AI that turns GitHub codebases into easy tutorials

This is actually really cool. I just tried it out using an AI studio API key and was pretty impressed. One issue I noticed was that the output was a little too much "for dummies". Spending paragraphs to explain what an API is through restaurant analogies is a little unnecessary. And then followed up with more paragraphs on what GraphQL is. Every chapter seems to suffer from this. The generated documentation seems more suited for a slightly technical PM moreso than a software engineer. This can probably be mitigated by refining the prompt.

The prompt would also maybe be better if it encouraged variety in diagrams. For somethings, a flow chart would fit better than a sequence diagram (e.g., a durable state machine workflow written using AWS Step Functions).

Answers like this are sort of what makes me wonder what most engineers are smoking when they think AI isn’t valuable.

I don’t think the outright dismissal of AI is smart. (And, OP, I don’t mean to imply that you are doing that. I mean this generally.)

I also suspect people who level these criticisms have never really used a frontier LLM.

Feeding in a whole codebase that I’m familiar with, and hearing the LLM give good answers about its purpose and implementation from a completely cold read is very impressive.

Even if the LLM never writes a line of code - this is still valuable, because helping humans understand software faster means you can help humans write software faster.

Well companies lock "frontier LLMs" behind paywalls, and I don't want to pay for something that still might not be of any use to me

Gemini 2.5 Pro Experimental (a frontier model) has 5 RPM and 25 RPD.

Gemini 2.5 Flash Preview 04-17 another powerful model has 10 and 500.

OpenAI also allows you to use their API for free if you agree to share the tokens.

What are "RPM" and "RPD"? I assume not Revolutions Per Minute?