Questions people ask before they trust AI with real tools
Is this just auth, approvals, or another policy layer?
No. AEG Gate sits at the execution boundary between AI output and real action. Policy is checked before execution, the path stays token-gated, and the outcome remains inspectable.
What actually stops execution?
The protected path does not run unless AEG Gate approves it and issues a one-time execution token for that path.
What does defer to human mean here?
The action does not auto-run. Human review becomes the next step before execution, and that decision remains inspectable too.
What proof do I get after a decision?
The local flow exposes an inspectable proof packet URL. Approve, refuse, and defer-to-human outcomes all leave proof on the running local service.
Does this replace RBAC, auth, secrets, sandboxing, or policy engines?
No. It complements them. AEG Gate is about the execution boundary itself: whether a protected action is approved, refused, or deferred before anything runs.
How is this different from MCP, tool calling, or agent frameworks?
MCP, tool calling, and agent frameworks help AI connect to tools and workflows. AEG Gate sits at the execution boundary and decides whether a protected action is approved, refused, or deferred before it runs.
Where does this fit in the stack?
Between AI output and the protected action. Keep your existing auth, secrets, sandboxes, and infrastructure controls. AEG Gate adds the decision boundary right before execution.
Do I need to rebuild my stack to use this?
No. Start by putting AEG Gate in front of the actions you do not want running on blind trust. Keep the rest of your stack, then protect more actions deliberately over time.
What does the one-time token actually do?
It is the gate's execution permission for the protected path tied to that decision. The action does not proceed through the protected path without it.
Why not just add a manual approval step somewhere earlier?
Because the critical moment is execution itself. AEG Gate keeps the decision boundary right before the protected action runs, then leaves proof behind so the outcome stays inspectable.
What kinds of actions is this for?
The first surface is aimed at shells, deploy paths, tools, jobs, and cloud-connected actions where blind execution trust is a bad idea.
Why does this matter if models keep getting better?
Better models still create the same core problem: thinking faster does not mean acting with full trust. The boundary belongs at execution time, not only in prompts or planning.
What do I do first?
Download AEG Gate, run the exact local commands shown on this page, and inspect the proof packet on the local service.
Can I try this right now?
Yes. Download AEG Gate, run the exact local flow shown on this page, and inspect proof locally. AEK Kernel and the Refusal-Proof Demo are linked separately for deeper inspection when you want them.
Does this depend on one model provider?
The release shown here is about the execution boundary, not a single model vendor. The important thing is what happens before a protected action runs.
What is public today and what comes next?
AEG Gate is the first public release. AEK Kernel is the trust layer, the Refusal-Proof Demo is the deeper proof harness, and Operational Ancestry comes next.