Comment by kace91
4 days ago
Even discounting lines of code:
- get a feature request/bug
- understand the problem
- think on a solution
- deliver the solution
- test
- submit to code review, including sufficient explanation, and merge when ready
260 PRs a month means the cycle above is happening once per hour, at constant speed, for 60 hours work weeks.
The premise of the steps you've listed is flawed in two ways.
This is more what agentic-assisted dev looks like:
1. Get a feature request / bug
2. Enrich the request / bug description with additional details
3. Send AI agents to handle request
4a. In some situations, manually QA results, possibly return to 2.
4b. Otherwise, agents will babysit the code through merge.
The second is that the above steps are performed in parallel across X worktrees. So, the stats are based on the above steps proceeding a handful of times per hour--in some cases completely unassisted.
---
With enough automation, the engineer is only dealing with steps 2 and 4a. You get notified when you are needed, so your attention can focus on finding the next todo or enriching a current todo as per step 2.
---
Babysitting the code through merge means it handles review comments and CI failures automatically.
---
I find communication / consensus with stakeholders, and retooling take the most time.
One can think of a lot of obvious improvements to a MVP product that don't requre much regarding "get a feature request/bug - understand the problem - think on a solution".
You know the features you'd like to have in advance, or changes you want to make you can see as you build it.
And a lot of the "deliver the solution - test - submit to code review, including sufficient explanation" can be handled by AI.