3 ms·
I'm trying to figure out ways to placate the boss by fitting AI into the edges of my workflow. "Look at these commits and do a review" to find stupid stuff lik
by hakfoo 1y ago
I'm trying to figure out ways to placate the boss by fitting AI into the edges of my workflow.
"Look at these commits and do a review" to find stupid stuff like forgotten exception throws or nulls. Or "Critique this documentation for a different audience"
I don't want to get into the "let the machine write the code" phase because that's the task I enjoy most, and it swaps my efforts into review, which I'm bluntly less confident about (having to follow and second-guess an architecture without being "there" when it was evolved increases the chances I'll miss stuff)
The stuff that AI demos well at-- "refactor 5,000 lines of code", "build a new client from ground level" are simply not what my team works on; we end up doing things where building a prompt to actually make the change we want-- and only the change we want-- takes longer than writing the code itself. 80% of the time is the debugging and planning.
- dearilos 1y agoHow has that worked out so far? I'm building something similar and I found that code review with LLMs is really good when: - You give it specific rules. I built a directory for these because they made the reviewer so much better [1] - The rules you write are things your team already looks for during review (proper exception handling, ensuring documentation, proper comments, etc.) [1] https://wispbit.com/rules https://wispbit.com/rules