[qzira]

When people talk about AI increasing developer productivity, they usually focus on the coding part. In my experience, the bigger change happens after the code is written. When you move from writing code to supervising agents, your output increases — but your cognitive load increases too. Instead of writing every line yourself, you're now monitoring systems: Did the agent go off-script? Did it retry 50 times while I was asleep? What did that run actually cost? The strange part is that the mental burden doesn't disappear just because the agent is autonomous. In some ways it gets worse, because failures become harder to notice early and harder to contain once they start. It starts to feel less like programming and more like running operations for a team of extremely fast, extremely literal junior developers. Curious if others are seeing the same shift.

[Waterluvian]

That really sounds like micro managing jr. developers.

I wonder if the interface for this kind of thing might be better presented as a sort of JIRA ticket system. Define a dependency graph of work with the ability to break down any ticket into more tickets or change priority or relationships etc.

Though I think the micro manage part still doesn’t fit into that model. You’d need the code-level view and not just a ticket covering the tests that satisfy the spec and performance goals.

[qzira]

I think a lot of people feel this tension. Programming used to be mostly about building things directly. You write code, run it, fix it, repeat. With agents it starts to shift toward supervision: define the task, watch the output, correct the drift. It's a different kind of work. Sometimes it feels less like programming and more like managing a very fast team that never gets tired but also never really understands the goal unless you spell it out extremely carefully. I suspect a lot of developers still enjoy the "building" part more than the "supervising" part.

[ender341341]

> That really sounds like micro managing jr. developers.

That's how I tend to describe AI to a lot of non-technical people (I actually generally say it's like having an really fresh intern who can read technical docs insanely fast but needs a lot of supervision).

[qzira]

That's a really good analogy. The interesting part is that the "intern" is not only fast, but also extremely confident. A human intern usually hesitates, asks questions, or signals uncertainty when they are unsure. Agents often produce very clean-looking output even when the reasoning behind it is shaky. So part of the supervision isn't just checking the result, but trying to detect when the confidence is misleading.

[democracy]

Yeah I am not sure many people gonna hang around this - I am not sure I wanna do this role. I like building and delivering and ai is great help but I will not be happy supervising agents, there are better jobs. Unless the money is not to be refused

[qzira]

That's a very real concern. For a long time programming felt like a craft: you build something, run it, improve it. Agent workflows introduce a different kind of work. You're not just building anymore, you're supervising. Some people enjoy that shift toward orchestration. Others really don't. I suspect we'll eventually see tools that try to restore the "build and run" feeling instead of turning developers into supervisors.