Almega

The whole point of an agent is to hand it the work and walk away. But the moment it acts on its own, it can spend money, deploy code, delete data, send messages — and you have no real grip on what it actually does.

So you reach for the obvious fix: put the rules in the prompt. "Don't spend over $50. Don't touch prod." It feels like control. It isn't.

A model honors an instruction right up until it's task-motivated not to. A prompt injection from a page it reads can override your rules in a single line. A loop bug ignores them entirely. The instruction was never a wall — it was a wish.

And when you run a fleet of agents, accountability collapses: which agent did what, when, and why? "I told it to be careful" is not an answer you can prove — to a customer, an auditor, or yourself.

What's missing is a boundary that lives outside the agent — one a bug, an attack, or the agent itself can never get past. A frame you set once, a human gate on what's sensitive, and a ledger that never forgets. That is Almega.

# set the frame once — the agent can't change it set_frame("ops-bot", allow=["read", "search"], require_approval=["deploy", "file.delete", "payment"], block=["shell.exec"], ) # the agent asks before anything sensitive request("ops-bot", "deploy", "deploy #418 to prod") # → held for your one-click approval · logged

Delegate everything.
Within limits they can't cross.

Connect

Set the frame

Approve

Audit

"Just tell it the rules"

An Almega frame

Back Almega early — and never pay full price.

Let your agents work.
Sleep at night.