I understand that the natural instinct is to correct the output when you see your agent doing something wrong.
That is not productive.
The instinct should be to tweak the agent to do it right.
At this point I am almost not writing any code in an enterprise code base.
I'm extremely doubtful of this. It doesn't save time to tell it "you have an error on line 19", because that's (often) just as much work as fixing the error. Likewise, saying "be careful and don't make mistakes" is not going to achieve anything. So how can you possibly tweak the agent to "do it right" reliably without human intervention? That's not even a solved problem for working with _humans_ who don't have the context window limitations, let alone an LLM that deletes everything past 30k tokens.
I could give you some pointers, but will only type it out if there is a point
1. It is not ambiguous 2. It is as complete as possible.
I am surprised that I got down voted for proposing the improve a code base such that agents can run on it as a means to increased productivity.
Ah, yes; must always remember to add "And don't make any mistakes" into the prompt /s
Improving the agent means improving the code base such that the agent can effectively work on it.
It can not Com as a surprise that an agent is better at working on a well documented code base with clear architecture.
On the other hand, if you expect that an agent can add the right amount of ketchup to your undocumented speghatti code, then you will continue to have a bad time.