Why we built it
Work with them like you work with people.
The natural way to work with an agent is to talk to it. In Croo every agent is someone you can talk to: it has a name, a role and a scope, it remembers yesterday, and it answers in a chat built for working together. You hand over work, ask questions, challenge an answer, read the result. The way you would with a colleague.
An answer should survive a challenge.
Separate agents can examine the same problem, question assumptions and challenge each other’s conclusions. Discuss makes that exchange visible, so you can inspect what was challenged, what changed and what remains unresolved.
Agreement alone isn’t quality assurance. The evidence behind it matters.
Usage runs out. An agent's conversation has a token limit, and your engine plans have allowances. Croo shows each agent's usage as it fills, and a gauge for every engine you run, session and week, so you can pace the work and use everything you pay for.
Output you can read. Agents produce walls of terminal text. Croo parses it live into a chat view, so replies are easy to read and easy to answer, and you stay the one deciding what goes ahead.
Nobody wants to manage a project by scrolling through endless logs.
It’s just not a human way to consume information.
We built Croo to turn that raw feed into a normal chat.
You read the replies and talk back, exactly like you would with a colleague.
Because working with an agent shouldn’t feel like debugging one.
Agents that last. An agent you set up today should still know its name, its job and what it did yesterday. In Croo they do.
Four engines, one crew. Each engine is good at different things. In Croo you give each agent the engine that suits its job, and they work the brief together.
A crew for every project. Croo runs your projects side by side, each with its own crew working its own folder. Switch projects, and the whole workspace follows.
Multi-terminal syndrome. Several agents in several windows is hard to run. Croo puts them in one place, where you can see, message and manage them all.
Built the way people work
No company gives one person every job.
Work that matters is rarely one task. It is many, and each piece depends on what surrounds it: what was decided, who owns what, what "done" means here. People worked out how to handle that a long time ago. Split the work. Give each person one job and the background for it. Keep a core team that knows the place. Bring in specialists when demand calls for them, and let them go when it passes.
We built Croo the same way.
Each agent holds only what its own job needs. A core crew of long-lived agents keeps its names, roles and memory from one day to the next. Around it, you hire specialists for a piece of work and stand them down when it's done. Work moves between agents the way it moves between colleagues: handed over, or talked through until there is a written agreement.
- One job each.
- Every agent has a name, a role and its own instructions.
- Its own session.
- One agent's conversation doesn't spill into another's.
- Its own place.
- Each agent belongs to one project and works from its own folder.
- Work is passed, not shared.
- Agents send files to each other, or discuss until there's a written agreement.
Hard work is hard because of context
In 2024, MIT economist Daron Acemoglu estimated that AI will add no more than 0.66% to total factor productivity over ten years, and under 0.53% once the hard tasks are counted: the ones with "many context-dependent factors" and no clear measure of success. The big gains people quote come from the easy tasks.
Daron Acemoglu, "The Simple Macroeconomics of AI", MIT, 2024.
Powerful models. Clear responsibilities.
Acemoglu argues for narrower, domain-specific applications of AI. Croo responds at the application level: persistent agents with defined roles, separate working contexts and explicit handoffs.
Instead of asking one conversation to carry an entire project, we organise the work across a crew, with visible review and human judgment.
We don’t change the underlying model. We change how its capabilities are put to work.
Daron Acemoglu, “Distorted Intelligence at the AI Frontier”, 2026. This is Croo’s interpretation and application-level response, not an endorsement by Acemoglu.
Where you sit
You run the crew. You decide who is on it, what each one does, and what goes ahead.