Why isn't this already solved?
Because the hard part was never the software. A process starts in one or two heads, then spreads across teams, tools, and exceptions until no one can see the whole thing end to end. And you can't safely change what no one fully understands. Every fix runs into the same trap:
Automation tools
The process gets buried in the wiring of six apps. When something breaks, it's archaeology.
See full comparison →Raw AI agents
The process runs inside a black box. Impressive in a demo, unexplainable in production.
See full comparison →Custom & vibe-coded builds
The process freezes into code nobody fully understands. Including, soon, whoever wrote it.
What changed is that AI agents can finally do both halves: run real operational work, and build the understanding of the process in the open, where your team can see it and change it.
Raw capability isn't enough. A raw agent drifts; you can't observe it, and you can't iterate on it. What makes it dependable is the scaffold around the agent: the stated process, the guardrails, and the record of every run.
We spent a decade building work management and AI products. Building that scaffold is what we do.
Explore MalleableEvery stage carries its own guardrails: the outcome, the required actions, the allowed apps, and where the agent can use judgment.