IntegrAuth Academy
Identity, security and practical AI — free, from zero. Byte-sized lessons, real diagrams, hands-on labs, zero fluff. Two programs, each with its own exam and certificate.
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The big picture
You started this track with Kai, an AI agent that could read a request, make a plan and call real tools. Now you can give Kai an identity and limit what it reads and does. You can keep a human on the money and switch Kai off fast. This page ties the journey together before the quiz.
The story you just lived
Kai was useful and dangerous. First we controlled the link between the agent and its tools, the MCP plug. Governing MCP put a checkpoint there. Then came data. FGA asks: can this person open this invoice? (See fine-grained authorization.) Kai also answers from your documents, using RAG. So permission-aware RAG hands the model only the pages this reader may see.
Acting is the dangerous half. Anything that spends money waits for a person, on a channel the agent does not control. That is human-in-the-loop approval. The registry shows every agent and gives you a kill switch. Delegated third-party access lets Kai use Maya's calendar without her password.
These controls join in the secure copilot. Then we faced the attacker. Prompt injection is fixed by guardrails around the model, not by a cleverer system prompt. A bad note or a changed tool can bring the attack back later, so poisoned memory and changing tools keeps notes labeled and tools pinned. Kai may hand a job to Sam's agent by delegation. Agent-to-agent delegation keeps Maya's cap and identity on every hop. Agent audit trails seal a tamper-evident record of who did what, for whom and why.
The threads that tie it together
Everything hangs off a human's identity
Kai borrows your power. This drives fine-grained authorization, permission-aware RAG and the copilot.
Scopes are limits; prompts are requests
Real limits live in tokens and policy, outside the prompt. That is why a poisoned instruction in prompt injection still cannot buy anything.
Authority only ever narrows
Every handoff gives away power and never gains it. See human-in-the-loop, the vault and agent-to-agent chains.
Govern what you can see and replay
The registry shows who is out there. Audit trails show what they did.
Now you can say yes to an AI agent in production, and you know how to stop it.
The helper you can trust
Remember the new assistant from the start? Now Kai carries a letter of authority: an identity and narrow scopes. Kai asks before spending. Kai keeps a diary nobody can erase. And you can take the letter back with one switch.
Where these ideas go next
These controls are least privilege, applied to a very fast machine. Keep going with least privilege for machines, identity telemetry and SIEM and service-to-service identity.
Feel ready? The cheat sheet and pop quiz is one page away.