One employee. Real work. Trust earned over time.
Train it in Chat, connect the work it needs, and start cautiously. Review the proof, correct the same employee, and decide one Action’s trust setting from evidence.
From first brief to useful work
The employee you train is the employee that does the job. One Chat carries the brief, real work, and corrections.
Brief it in Chat
Tell one ready employee the business job you want handled, in plain English — the way you'd brief a new hire.
Connect the work it needs
Add only the Connectors and data that job needs. Each Connector shows what it can and cannot do before you connect it.
Give it a real job
Start with realistic work and cautious Action trust. Safe work can move; anything outside the trusted surface stops or waits.
Review the proof
See what it checked, why it acted or held, the risk, the run cost, and the exact work waiting for you.
How trust compounds
Correction changes the same employee, and evidence — not a promise — informs the next trust decision.
Correct it in the same Chat
Approve the exact held work when it is right, or explain what should change in plain language.
See the Training change
The correction becomes a visible rule or preference in Instructions. You can edit or remove it, and the next similar run shows whether it worked.
Keep related work together
Let the same employee keep the shared context, rules, Connectors, and trust when the next job is closely related.
Decide one Action’s trust setting
Use the evidence to keep or change that Action’s owner setting. Current safety floors can still hold work for approval.
Grow the employee before multiplying employees.
Related work usually belongs with the same employee because it shares context, data, rules, and trust. Create another only when the audience, brand, permissions, or risk boundary is genuinely different.
Context compounds
Related work keeps the same memory, Skills, Connectors, and owner corrections.
It starts cautious
New Actions begin at the trust level you choose, with deterministic safety floors underneath.
Evidence informs trust
Review shows the work, risk, cost, and learning that inform one Action’s setting without bypassing platform floors.
You see everything it did.
Each run records what woke the employee, what it checked, why it acted or held, what changed, what it cost, and what it learned. That is the proof you use to correct the work and decide what to trust next.
Train your first AI employee today.
Describe the job in plain language, connect the work it needs, and start cautiously. The same employee learns from your corrections and earns trust through evidence.
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