I’ve been wondering, is anyone actually getting real value out of GenAI for software engineering? We’ve been working with teams across fintech and enterprise software to adopt AI in a serious way, and here’s the honest truth: most AI tools are either too shallow (like autocomplete) or too risky (like autonomous code-gen). But between those extremes, there’s real potential.
So, what’s working? We built a tool that does the boring stuff that slows teams down: managing tickets, fixing CI errors, reviewing simple PRs. All inside your stack, following your rules. It’s definitely not magic, and it’s not even elegant sometimes. But it’s working.
I’m curious, how are others walking this line between AI hype and utility? What’s working for you? What’s a waste of time?
Let’s focus on the real value that GenAI can bring to software engineering, beyond the hype and the risks. Share your experiences, and let’s explore what’s possible.