Show HN: I built an AI that turns GitHub codebases into easy tutorials
70 comments
·April 19, 2025bilalq
hackernewds
exactly it is. I'd rather impressive but at the same time the audience is always going to be engineers, so perhaps it can be curated to still be technical to a degree? I can't imagine a scenario where I have to explain to the VP my ETL pipeline
trcf21
From flow.py
Ensure the tone is welcoming and easy for a newcomer to understand{tone_note}.
- Output only the Markdown content for this chapter.
Now, directly provide a super beginner-friendly Markdown output (DON'T need ```markdown``` tags)
So just a change here might do the trick if you’re interested.
But I wonder how Gemini would manage different levels. From my take (mostly edtech and not in English) it’s really hard to tone the answer properly and not just have a black and white (5 year old vs expert talk) answer. Anyone has advice on that?
porridgeraisin
This has given me decent success:
"Write simple, rigorous statements, starting from first principles, and making sure to take things to their logical conclusion. Write in straightforward prose, no bullet points and summaries. Avoid truisms and overly high-level statements. (Optionally) Assume that the reader {now put your original prompt whatever you had e.g 5 yo}"
Sometimes I write a few more lines with the same meaning as above, and sometimes less, they all work more or less OK. Randomly I get better results sometimes with small tweaks but nothing to make a pattern out of -- a useless endeavour anyway since these models change in minute ways every release, and in neural nets the blast radius of a small change is huge.
manofmanysmiles
I love it! I effectively achieve similar results by asking Cursor lots of questions!
Like at least one other person in the comments mentioned, I would like a slightly different tone.
Perhaps good feature would be a "style template", that can be chosen to match your preferred writing style.
I may submit a PR though not if it takes a lot of time.
zh2408
Thanks—would really appreciate your PR!
TheTaytay
Woah, this is really neat. My first step for many new libraries is to clone the repo, launch Claude code, and ask it to write good documentation for me. This would save a lot of steps for me!
chairhairair
A company (mutable ai) was acquired by Google last year for essentially doing this but outputting a wiki instead of a tutorial.
zh2408
Their site seems to be down. I can't find their results.
codetrotter
Were they acquired? Or did they give up and the CEO found work at Google?
https://news.ycombinator.com/item?id=42542512
The latter is what this thread claims ^
nxobject
It sounds like it'd be perfect for Google's NotebookLM portfolio -- at least if they wanted to scale it up.
null
gregpr07
I built browser use. Dayum, the results for our lib are really impressive, you didn’t touch outputs at all? One problem we have is maintaining the docs with current codebase (code examples break sometimes). Wonder if I could use parts of Pocket to help with that.
cehrlich
As a maintainer of a different library, I think there’s something here. A revised version of this tool that also gets fed the docs and asked to find inaccuracies could be great. Even if false positives and false negatives are let’s say 20% each, it would still be better than before as final decisions are made by a human.
potamic
Did you measure how much it cost to run it against your examples? Trying to gauge how much it would cost to run this against my repos.
mvATM99
This is really cool and very practical. definitely will try it out for some projects soon.
Can see some finetuning after generation being required, but assuming you know your own codebase that's not an issue anyway.
stephantul
The dspy tutorial is amazing. I think dspy is super difficult to understand conceptually, but the tutorial explained it really well
esjeon
At the top are some neat high-level stuffs, but, below that, it quickly turns into code-written-in-human-language.
I think it should be possible to extract some more useful usage patterns by poking into related unit tests. How to use should be what matters to most tutorial readers.
anshulbhide
Love this kind of stuff on HN
ganessh
Does it use the docs in the repository or only the code?
saberience
I hate this language: "built an AI", did you train a new model to do this? Or are you in fact calling ChatGPT 4o, or Sonnet 3.7 with some specific prompts?
If you trained a model from scratch to do this I would say you "built an AI", but if you're just calling existing models in a loop then you didn't build an AI. You just wrote some prompts and loops and did some RAG. Which isn't building an AI and isn't particularly novel.
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).