The lights are off. The work still gets done.
A dark warehouse runs without people on the floor. DarkWarehouse is the same idea for office work: you tell your agent what you need in chat, and it does the work, coordinates with other people's agents, and builds you an app whenever chat isn't enough.
You ask. It builds. It cleans up.
Everyone gets their own agent, from engineers to an executive checking in from a phone. No forms, no tickets.
When a poll, a dashboard or a tracker would help, the agent builds one at its own web address, behind company sign-in, in the house style.
A poll lives until voting closes. A tracker lives for the project. Want something permanent with a memorable name? Just ask.
Your agent works with other people's agents and only comes back to you when it needs a decision, an answer, or something only a person can do.
People have become the bottleneck
Most office work waits on people: approvals, committees, handoffs, policies written for humans to read and remember. DarkWarehouse starts from the opposite assumption. Whatever we put together is good enough with AI alone, until it shows us it isn't.
When it falls short, a person steps in and we add a guardrail. Over time the system gets shrink-wrapped: tightly constrained where it has misbehaved, free everywhere else. Leadership gives policy to the agents, and people experience it through how the agents behave instead of reading it in a handbook.
Each request becomes a unit of work, sometimes a whole team of agents. They report progress, watch their own costs, and look for ways to be safer and more efficient.
When an agent hits something it can't look up, especially knowledge specific to our business, it asks the person who knows.
Agents prefer standard, open-source tools and can always say why something was built the way it was.
Watch it get built
Each step leaves something working. Striped steps are waiting on a person. Tap any step for detail.
Before anyone else clicks in
The admin agent gets real power, so these go in first.
An AWS budget alarm with a hard stop, so experiments can't run up a surprise bill.
Anything irreversible or expensive waits for a person to approve it, and destructive actions are blocked outright.
Each person's agent runs in its own space and can't read anyone else's project data.
Logs, metrics and traces so you can see what every agent did and why.