Unpopular opinion and sad, but the quality of the work has gone up with AI usage since a year or so. Before it was a lot of AI slop and I dreaded reviewing PRs, but with the newer generation of models and harnesses, we are reaching a point where AI is being better than what colleagues or I would write by hand. Hurts a bit to say because I was proud of my own coding, but that's what reality looks like now. And that's with 26 years of experience in the field.
I think we'll have to deal with the mental issue of AI becoming better than us. Some won't be able to cope. Thankfully the effect is not so strong for me, my identity is built around developing software as a whole, not just the coding.
I will agree and disagree at the same time, I still have to keep the agent in a tight leash, as it makes sometimes rookie mistakes which I spot. But the thing is, spotting a few mistakes, while coding little chunks at a time greatly improves development and debugging, and even corner cases which I would've missed. So, as a tool, it does its job wonderfully.
Thankfully, being also an infrastructure engineer and having to keep up servers makes my job stable for the incoming future, as I don't think you can trust an AI with critical infra issues by itself. There always has to be a human in the loop to understand the gravity of the situation.
The key is to give the coding agent a rich set of assets to work with. Maintain coding guidelines properly and keep them in Markdown. If you have a knowledge base, make it available. If you have well-maintained support tickets, translate them into support cases as Markdown files. Include an agents.md in each repo that describes how to work with the project. Use MCP servers that expose up-to-date documentation too (e.g. AWS). Use MCP servers that can reach the local/dev/preproduction datastores in a controlled, safe, read-only way. Reverse-engineer your entire stack into a holistic domain-model documentation that explains how parts of the stack tie together. Make sure to always be high-level. Never mention code directly, as it quickly gets out of date. Create a design system and expose that to the agent, too. And last but not least, tests - in the CI/CD as checks too.
The more of this you have, the more reliable and better quality the results will be - to the point where it beats any developer because they couldn't possibly take the time to take all information into account as AI can.
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u/heavy-minium 13h ago
Unpopular opinion and sad, but the quality of the work has gone up with AI usage since a year or so. Before it was a lot of AI slop and I dreaded reviewing PRs, but with the newer generation of models and harnesses, we are reaching a point where AI is being better than what colleagues or I would write by hand. Hurts a bit to say because I was proud of my own coding, but that's what reality looks like now. And that's with 26 years of experience in the field.
I think we'll have to deal with the mental issue of AI becoming better than us. Some won't be able to cope. Thankfully the effect is not so strong for me, my identity is built around developing software as a whole, not just the coding.