You spend a few minutes generating a spec, then agents go off and do their coding, often lasting 10-30 minutes, including running and fixing lints, adding and running tests, ...
Then you come back and review.
But you had 10 of these running at the same time!
You become a manager of AI agents.
For many, this will be a shitty way to spend their time.... But it is very likely the future of this profession.
Anyway… watch the videos the OP has of the coding live streams. Thats the most interesting part of this post: actual real examples of people really using these tools in a way that is transferable and specifically detailed enough to copy and do yourself.
For each process, say you spend 3 minutes generating a spec. Presumably you also spend 5 minutes in PR and merging.
You can’t do 10 of these processes at once, because there’s 8 minutes of human administration which can’t be parallelised for every ~20min block of parallelisable work undertaken by Claude. You can have two, and intermittently three, parallel process at once under the regime described here.
The number you have running is irrelevant. Primarily because humans are absolutely terrible at multitasking and context switching. An endless number of studies have been done on this. Each context switch cost you a non-trivial amount of time. And yes, even in the same project, especially big ones, you will be context switching each time one of these finishes it's work.
That coupled with the fact that you have to meticulously review every single thing the AI does is going to obliterate any perceived gains you get from going through all the trouble to set this up. And on top of that it's going to be expensive as fuck quick on a non trivial code base.
And before someone says "well you don't have to be that thorough with reviews", in a professional settings absolutely you do. Every single AI policy in every single company out there makes the employee using the tool solely responsible for the output of the AI. Maybe you can speed run when you're fucking around on your own, but you would have to be a total moron to risk your job by not being thorough. And the more mission critical the software the more thorough you have to be.
At the end of the day a human with some degree of expertise is the bottleneck. And we are decades away from these things being able to replace a human.
How about a bug fixing use case? Let agents pick bugs from Jira and let it do some research and thinking, setting up data and environment for reproduction. Let it write a unit test manifesting the bug (making it failing test). Let it take a shot at implementing the fix. If it succeeds, let it make a PR.
This can all be done autonomously without user interaction. Now many bugs can be few lines of code and might be relatively easy to review. Some of these bug fixes may fail, may be wrong etc. but even if half of them were good, this is absolutely worth it. In my specific experience the success rate was around 70%, and the rest of the fixes were not all worthless but provided some more insight into the bug.
You spend a few minutes generating a spec, then agents go off and do their coding, often lasting 10-30 minutes, including running and fixing lints, adding and running tests, ...
Then you come back and review.
But you had 10 of these running at the same time!
You become a manager of AI agents.
For many, this will be a shitty way to spend their time.... But it is very likely the future of this profession.