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I’ve found it’s very useful for understanding snippets of code, like a 200-line function. But systems are more than “lots of 200-line functions” - there’s a lot
by blowski 3y ago
I’ve found it’s very useful for understanding snippets of code, like a 200-line function. But systems are more than “lots of 200-line functions” - there’s a lot of context hidden in flags, conditional blocks, data, Git histories.
Maybe one day, we’ll be able to run it over all the Git histories, Jira tickets, Confluence documentation, Slack conversations, emails, meeting transcripts, presentations, etc. Until then, the humans will need to stitch it all together as best they can.
- darkerside 3y agoI can't think of a reason you couldn't specifically train an AI on your own large code base. After all, current LLMs are trained on effectively the entire internet.
- zappchance 3y agoUnless your documentation is 20~100x the size of your codebase and written in a conversational tone, the LLM won't be able to be asked any questions about it using English. If your only aim is to use it like Copilot, sure, it's useful.
- sandos 3y agoSo the first step is to let the LLM write the documentation.... :)
- still_grokking 3y agoSure. Because it understands the code so well.
- oceanplexian 3y agoYou might be able fine tune a model on pull requests if they have really high quality descriptions, high quality commit messages, and the code is well documented and organized.
- still_grokking 3y agoI'm really not sure this is irony or a serious comment.
- blowski 3y agoI haven't yet seen anything that can scan an entire codebase and build, say, a data lineage to understand how a value in the UI was calculated. I'm sure it's coming, though.
- still_grokking 3y agoIt's coming, I'm sure. Just right after we have invented AGI.