What changes in engineering teams once AI tools "click"?
The setup was simple: six engineers spent a few 2 days experimenting with AI in their real development workflows. Nothing theoretical — just trying things directly against their codebase and normal tasks.
A few observations stood out.
1. Initial skepticism was high
Several engineers were openly skeptical at the start. The general sentiment was something like:
“AI coding tools are interesting, but mostly useful for small snippets.” "I wouldn't put my name on code that wasn't 100% mine" was another... one even said "AI is the devil!"
Most of the team had tried assistants before but hadn’t really changed how they worked.
2. The shift didn’t come from code generation
What surprised everyone was that the biggest changes weren’t about generating code faster.
The moments where things “clicked” tended to be things like:
exploring unfamiliar parts of the codebase
debugging tricky issues
quickly testing alternative approaches
generating scaffolding to explore architecture ideas
Once engineers started using AI more as a thinking partner rather than a code generator, workflows changed pretty quickly.
3. Behavior changed very fast once a couple of the engineers started to use libraries they hadn't used due to time taken to understand how to integrate it.
After that, the rest of the team started experimenting with similar approaches.
Within a week the company apparently saw a huge spike in requests for "AI-tool" licenses internally.
4. The interesting part wasn’t the tool
What seemed to matter more was that the engineers had time and space to experiment together.
A lot of teams seem to have access to AI tools now, but they’re still using them in fairly shallow ways.
When people start experimenting with their real workflows, usage patterns seem to change very quickly.
Curious if others have seen something similar inside their teams.
Specifically:
Where have AI tools actually changed engineering workflows for you?
What use cases ended up being more useful than expected?
Did adoption happen gradually, or was there a “flip the switch” moment?
Would be interested to hear how this is playing out in other engineering teams.