Task-oriented agents

We keep a task list so we don’t forget what matters. AI does the same thing now, only faster and without the sticky notes on our monitor. The twist is she keeps changing the list as she works.

Start with one job

A task-oriented agent is just AI with a to-do list. She picks one job from the list, does it, and then writes down the next thing to try. That’s the loop. Nothing fancy—like us clearing email one message at a time.

BabyAGI

BabyAGI made this loop famous. It was a small script that kept creating and re-ordering tasks toward a single goal. Give her “research solar panels,” and she’ll break it down, try a step, then suggest another. She wasn’t smart, but she showed how the loop could grow into something useful.

Why reprioritize

Lists get messy. Some tasks stop making sense once new info shows up. A good agent keeps shifting the order so the work stays relevant. That’s the secret sauce: she’s not just executing—she’s deciding what comes next.

What we learn

We see her juggle priorities, and it feels familiar. We do the same when a bug report lands in our lap mid-project. The value isn’t that she’s perfect. It’s that she helps us adapt without losing the thread.

Our take

We should treat task-oriented agents as partners, not magicians. They’re good at surfacing the next step and keeping our focus steady. If we let them handle the reshuffling, we save brain cycles for the parts only we can do.