Comment by ex-aws-dude
25 days ago
That’s funny I’ve been doing that too
Trying to crank out all the tools I never had time to build because I think we’re going to get cut off eventually
25 days ago
That’s funny I’ve been doing that too
Trying to crank out all the tools I never had time to build because I think we’re going to get cut off eventually
This seems seductive, but how do you get past the wall of "fixing XYZ or adding convenience ABC isn't on our pre-planned roadmap" so you can't get buy in from people who have to sign-off or deploy stuff?
Maybe that type of awkwardness is specific to my firm, but that's sort of what killed my drive to try to do that. We used to have one day every second week for that sort of work, but since it was scattered around, the tasks ended up disappearing-- nobody reviewed them and they didn't get merged.
So now they're trying to do a week-long internal hackathon to recover that vision, but I feel like that's going to produce a handful of big-bang ideas and not the 25 tiny tools that would actually streamline things.
Same. I've used it for debugging failed canary tests which required scripts and very specific knowledge on the canary platform that I wouldnt of ever spent time on.
I also have scripts to fetch specific database assets and forward them to slack channels so I can easily share them with a group rather than manually running a query and generating them.
I had a theory about improving a product. I asked it to build an offline simulation setup to try various implementations. The results were a bit fishy but i decided to give it a try and A/B testing is showing similar results.
And now im vibecoding a locally hosted dashboard. This one is less useful for anything specific, and more of a minor quality of life improvement, but its fun to just vibe code and see changes happen occasionally. Its not a critical thing.
I find it very useful for debugging tasks like that but it always ends up costing me like $3 despite doing incredible work. And then one of the other engineers at my company will rack up like $200 in tokens in one day producing tens of thousands of SLOC and we end up actually shipping about the same stuff. Sometimes I wonder if it's bad agent use discipline (just pointing it at massive codebases and having it read it all from scratch each time) and sometimes I wonder if they're just using it for personal projects. Because none of that code seems to land in prod, and I've found that cranking out 10s of thousands of SLOCs at a time is a recipe for a mess.
But depending on how much you get paid hourly, $3 would be very little comparatively, no?
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I don't think we will. I think this level of token cost/availability will trend cheaper and faster, long term. These companies that spent too big and too fast might try to limit it and raise the prices and they might be temporarily successful but they'll very quickly be taken over if they keep doing it.
May I ask what tools did you make so far? And what is on your roadmap?
Not OP, but a very simple example: I use AI to review my work before opening a PR for my colleagues to review. I ask it to review the commits in my branch. Instead of consuming tokens just to instruct it how to use git operations and other tools to find the commits since the base commit, I asked AI to create a little bash script to make patch files commit1.patch, commit2.patch, commit3.patch, etc, for all the commits in my branch since the base commit. Now I just use this script to prepare the context of commits to review.
I feel like an imposter here, I’m definitely not using AI as much as it seems everyone is :( I can’t imagine using hundreds of dollars of tokens a day. But maybe this little tip for reviews might be helpful to someone.
> Instead of consuming tokens just to instruct it how to use git operations
Claude already knows how to use git and jj, very well.
I also find it useful for review, and sometimes I use multiple passes to review for different categories. Like security, performance and so on.
Not op, made a tool to convert Microsoft OneNote notes to Obsidian canvas and Markdown. First it used a python lib which was too limiting. Then it used windows API to plug into OneNote and read the doc in its original XML form. That made the conversion correct and fully featured.
Not OP, but I've been focusing on linting and automation.
Custom lint rules to encode best practices that previously relied on astute/alert code reviewer to call attention to. This is handy not just for humans but it steers the bots too. Or turning on some existing rule that required a big cleanup/migration to be compliant with. Now I just throw an LLM at it, since they're often laborious but mechanical changes. Which is the sweet spot for an LLM.
Also automating everything I can. That annoying release process that everyone hates but wasn't quite long/arduous enough to justify the time before? It's now automated. GitHub workflows for all the things.
This kind of stuff will forever be useful, even if the bottom drops out and the bubble bursts. And none of it is reliant on AI to run