I started building Stacksona after spending a bunch of time on AI agents and hitting the same wall every time: the agent could actually do the work, but there was no good way to pause it before a risky action, pull a human in, and then let it keep going. Originally I was just trying to solve that one approval step. But once I got into it, I realized approvals were just the tip of it. You also need rules for what triggers a review, notifications, requests that don't just disappear if nobody responds right away, and a real record of what the agent tried, what the reviewer decided, and what happened after. That's basically what Stacksona turned into: infrastructure for human review and runtime governance on top of any agent workflow, so you're not rebuilding all of this yourself every time. I think agents actually get more useful, not less, when there's a human in the loop. This is my attempt to make that easy to bolt on.

Stacksona

The approval layer between AI agents and real actions.

The approval layer between AI agents and real actions.