JPMorgan just said it’s deploying AI agents that run for one to two hours with no human in the loop. Eventually, their analytics chief says, agents will run coherently for days, then weeks. The read is that the tech is finally close to clearing the governance hurdles that held it back.
Building this kind of system is what I do, so here’s the part of the story I’d want a leadership team to actually hear.
Long-running autonomy sounds like a duration problem. It isn’t. The longer an agent runs unsupervised, the more a small early mistake compounds — a wrong assumption in minute three becomes a wrong deliverable in hour two. Runtime doesn’t reduce that risk. It multiplies it.
“Intellectual coherence” — their phrase, a good one — isn’t correctness. An agent can be perfectly coherent and consistently wrong. Coherence is what makes the wrong answer convincing.
So when a team wants its agents running longer, I don’t start with the model. I start with three questions. Where does the agent check itself against ground truth? Where does it stop and confirm? What is it structurally not allowed to do alone? Answer those and you’ve earned the runtime. Skip them and you’re just scaling your blast radius.
And here’s what makes it real for everyone who isn’t JPMorgan: they can spend their way to the answer on a near-$20 billion tech budget. Most companies can’t. They get there by being deliberate — knowing which questions to ask before the pilot, not after the walk-back.
If you’re early in this, start there. Not with how long it can run. With what it’s allowed to do when no one’s looking.