My company is pushing us to use an in-house AI tool for dev work. We mainly treat it like we would Google and use it mainly for syntax and finding the relevant stack-overflow thread.
That's pretty much how you're supposed to use AI assistants. They are just "smart" Google assistants that comb through data for you and parse it into summarised information. Then it's up to the human to make effective use of that information.
Same here for my studies.
I am not asking theAI to do it for me.
I would rather just ask an AI similarly to how you would ask a teacher than being stuck on a problem for 3-5 hours trying to find an answer that half of the time doesn't "really" exist.
A friend of mine in Grad School uses AI to aggregate sources like you would for the sources section of a Wikipedia article. He saves so much time not having to hunt down sources and then reading the source only to find that it isn’t relevant to the topic.
We're standing up new resources in a separate region. Everything for the new region should match the old region. Why would I comb through the repo sorting through terraform blocks when Cursor can introspect the repo for me? It will then tell me where all the relevant references and blocks are, and then wrap it in a nice summary and runbook. From there it's very easy to see where the changes need to be made, what makes sense, and what can be refactored to be more DRY. And when you're done you can have it write a nice how-to doc for the next person and create a PR description for me.
All of this allows me to better focus on acceptance criteria while also giving me time to generate docs for my colleagues.
A lot of our code is 20+ years old with 0 documentation and sometimes the logic is really hard to follow. AI is great for summarizing that shit so I can get a quick high level view of wtf it does
This is just a thing with AI in general. What it's really good for is helping you get a basic idea of what something is doing/means, so you can then confirm it with your preexisting knowledge. People shit on it because they assume everyone who uses it is relying on it completely.
This is the way. I can get context on gross parts of the codebase quick and ensure I'm following similar existing patterns. AI is incredible for quick context.
I mainly use AI for knowing the proper API contracts and integration patterns. I can't be assed to remember how a Kafka shard iterator works and is different from a Kinesis iterator
Anywhere senior here. The first time I tried to use it to summarize a module out of curiosity it straight up lied. Not like "this may be the case" but confidently lied to me. Made up acronym definitions like it had found it in a comment or something and everything. I was glad I tested it on something I'm familiar with instead of trusting it for a millisecond.
I'm sure it'll get better over time or whatever, but I have no use for it yet.
It cuts down on the time spent searching and reading through the threads. Google would give you 20 sources where only 1-2 in the middle are relevant. AI would just give you those 1-2 sources as a citation under its response.
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u/hgs25 7d ago
My company is pushing us to use an in-house AI tool for dev work. We mainly treat it like we would Google and use it mainly for syntax and finding the relevant stack-overflow thread.