Microsoft Agent Governance and Independent Control Planes
Microsoft's agent governance stack — the open-source Agent Governance Toolkit, Entra Agent ID, Purview — and where an independent control plane fits.
AI agent security, identity, governance, cost, and the engineering behind the control plane.
Microsoft's agent governance stack — the open-source Agent Governance Toolkit, Entra Agent ID, Purview — and where an independent control plane fits.
What insurers deploying AI agents in underwriting and claims must meet: the Colorado AI Act, EU AI Act high-risk rules and the NAIC model bulletin.
How law firms and legal departments govern AI agents: privilege protection, matter-level access, ethical walls, and audit-ready evidence.
A practical guide to what AI agent observability must cover — cost, behavior, and policy compliance — and the key criteria for choosing the right tooling.
Calculate AI agent cost per completed task, including failed attempts and retries. Use a reproducible example and a checklist for a defensible benchmark.
What public bodies deploying AI agents must meet under the EU AI Act and administrative law: high-risk uses, transparency, registration and human review.
Set enforceable AI agent budgets with reservation-based enforcement, graduated thresholds, and clear attribution — before overruns reach your invoice.
The OWASP LLM Top 10 read through an agent lens, how it differs from the Top 10 for Agentic Applications, and the controls that address each risk.
AI guardrails and LLM firewalls both inspect content but solve different problems. Learn the distinctions, evaluation approaches, and fail-mode trade-offs.
How to keep AI agent data within jurisdictional boundaries, satisfy GDPR and cross-border transfer rules, and produce the evidence regulators expect.
Any agent with a fetch tool is an SSRF primitive with a natural-language interface. The attack paths, why allow-lists beat denylists, and how to bound egress.
How to give each AI agent its own identity and authenticate it with scoped, short-lived credentials — so every action is attributable and revocable.
An honest framework for deciding whether to build AI agent governance in-house or buy a platform, weighed by risk, team capacity, and time-to-value.
A practical checklist for AI agent incident readiness: inventory, instant revocation, tamper-evident audit trails, runbooks, and communication templates.
An API gateway manages traffic; an AI control plane governs agents. Learn the five critical gaps gateways leave open and what a control plane adds.
Loop-and-burn failures drain AI budgets fast. Learn the blast radius, five root conditions, and the layered controls that stop runaway spend before the invoice.
Criteria for evaluating AI agent governance platforms, then a disclosed list of platforms as of October 2026, grouped by approach and what each is best for.
Provenance, attestation, and runtime verification protect AI deployments from compromised third-party agents and tools — and how supply chain security works.
ISO/IEC 42001 sets requirements for AI management systems. See what the standard expects and how agent governance controls map directly to its Annex A clauses.
Most agents reach production with no promotion gate. The lifecycle stages worth defining, what each gate should check, and how to keep promotion fast.
A practical AI agent compliance checklist covering identity, tamper-evident audit trails, GDPR erasure, EU AI Act risk tiers, and vendor due diligence.
Indirect prompt injection hijacks tool-using AI agents through poisoned external content. Learn the attack vectors and layered controls that contain them.
Guardrails and agent configuration are security controls and need their change discipline: version policy, review changes, prove which version was in force.
Apply the NIST AI RMF to AI agents: map GOVERN, MAP, MEASURE, and MANAGE to controls like agent inventories, threat models, audit trails, and revocation.