SRE / DevOps / coding mostly in the Azure and .NET ecosystems.
The problems I have to solve tend to be the horrible ones that nobody has answers to, anywhere on the Internet, so unsurprisingly the AIs aren't good at it either.
The trick has been to use the AIs for what they are good that, which used to be "nothing" for me at least, but now I can use them productively for certain "spot" tasks.
Random examples:
- Cross-language and cross-platform benchmarking of a bunch of different database clients to see how they stack up. I gave the AI a working example in one language and got it to whip up a series of equivalents with other DB drivers and languages. Sure, it's trivial, but it's way faster than doing it myself!
- Crash dump analysis using WinDbg. I read somwhere that "vibe debugging" of kernel dumps totally works, so when I had an actual crash I gave it a go for laughs. With AI help I managed to extract the name of the specific file that had NTFS corruption and was crashing the server. Deleted the file, restored it from backups, and the server was good to go again!
- If you ever watch the top mechanical engineers on YouTube, they all make their own tools instead of just buying them. Jigs, extenders, unusual sizes, etc... IT work is the same. As a recent example, I got Gemini to make me a code-AST rewriter for a specific issue I wanted to clean up in bulk across a huge code base. Using the Roslyn compiler SDK is a bit fiddly, but it spat out a working tool for me in under an hour. (This is not something you can solve with a script full of regex, it needed a proper parser to handle commented-out blocks and the like.)
> Sure, it's trivial, but it's way faster than doing it myself
That's the clincher for me. So much software work is just excecuting on a design, not inventing anything new. Being able to do 5x the trivial work in an hour is life changing, and it lets me pull my head out of that work to see how I can make larger process improvements. AI doesn't need to rewrite the linux kernel in Rust to be extremely valuable to the average developer
Sounds like interesting work, thanks for sharing! "Vibe debugging", hah, I like that one. The latest crop of models is definately unlocking new capabilities, and I totally get the desire to make your own tools. I do that to a fault sometimes, but it's nice to have a simple tool that does exactly one thing, exactly the way you want it.
I've been pair programming with the models for a while, and wrote some "agents" before I knew to call it that back in the dark days of GPT-3.5, but only recently with the latest models unlocking capabilities beyond what I could achieve with handwritten code.
