Really enjoyed this deep dive. What stood out to me was the emphasis on the work around the agent, not just the code it generates. Context, environment, permissions, testing, and especially human review can easily become the real bottlenecks.
I also liked the idea of treating an agent task as more than just a prompt—having a clear goal, starting revision, constraints, acceptance criteria, and ownership makes the result much easier to evaluate.
The reminder that “tests passed” isn’t the same as “the change is correct” is probably one of the most important points here. AI can speed up the implementation, but the engineering judgment still has to remain in the loop. Great practical perspective!