A new Coddy Developer Survey found that four in five developers, 80%, say their use of AI has felt more like a dependence than an advantage.
A new Coddy Developer Survey found that four in five developers, 80%, say their use of AI has felt more like a dependence than an advantage.
I’m curious what tasks are you using GitHub Copilot for? I left the industry before AI got huge so I was never pressured to use the tools.
It can write code decently well and fast, and is amazing at finding stuff in a large project.
But you still 100% need to verify what it does and truly understand it.
This isn’t what I was asking for, I’d like to see something like, “When tasked with X AI did Y” with breakdowns between simple bug fixes to standing up a monolith in a legacy environment.
I mean that you would have to test yourself. To me it seems like AI funnily enough has the same issues as humans, and that’s that it works worse in legacy codebases full of tech debt, and in large monoliths.
But it can still be an invaluable tool.
All agents are pretty much the same. Think of it like pair programming with someone, except that someone doesn’t have feelings and you can micromanage them.
In general, I give it instructions for what I want to accomplish. It has a “plan mode” that basically instructs the LLM to give me an execution plan to approve before actually doing it. We iterate on the implementation plan together and then when I satisfied I let it generate code.
It generated diffs essentially that I can approve or deny directly, in aggregate or by individual chunk.
I can (and do) provide custom instructions that it loads whenever I start a session. Instructions are basically md files, but it can be any text.
It’s a very different way of writing code, but if you ever pair programmed with a knowledgeable junior then that’s kind of what it feels like.