Run AI agents in production, with proof.
4 practical guides on agent identity, human decisions, evidence, durable execution, context, architecture and economics, for teams taking agents from pilot to production.
Governance by design for AI applications: why trust can't be bolted on
Every component was secured. The order still went to the wrong legal entity. Why AI governance added after the prototype fails, and what it means to build it into how the application runs.
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Tenant isolation for AI agents and RAG: why a tenant_id filter isn't enough
Why multi-tenant AI leaks through retrieval, caches, model memory, tools and logs even with row-level security, and ten rules for end-to-end tenant isolation.
Visual policy rules for AI governance: no hidden scripts behind the diagram
Why visual policy builders fail when logic hides in scripts, how to make AI governance rules typed, testable and traceable, and ten design rules.
Governing AI agent tool calls and MCP tools: access isn't authority
How to govern AI agent tool calls and MCP tools: agents as non-human identities, why tool visibility isn't permission, and what per-call allow/block misses.
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See it on one of your own agents
One agent, one consequential action, one target system. We'll walk through identity, approval, durable execution and the record on your own case.