AI Agent Governance: Guides & Deep Dives
Field notes from engineers running autonomous agents in production. Architecture, security, compliance, and the comparisons that decide buying.
Four posts that frame the rest.
If you're comparing frameworks or defining a control plane, read these first — the framework comparison, the RAG/.NET comparison, the control-plane definition, and the trust-boundary argument.
Best AI Agent Frameworks 2026: LangChain, CrewAI, AutoGen
Compare LangChain, CrewAI, AutoGen, LlamaIndex, and Semantic Kernel by use case, failure mode, governance gap, durability, and audit readiness.
LangChain vs LlamaIndex vs Semantic Kernel: Which Breaks First? (2026)
All three break without governance. 6 production failure modes — retry storms, state loss, approval bypass — mapped per framework with decision criteria.
What Is an AI Agent Control Plane? Definition and Architecture (2026)
An AI agent control plane is the governance layer that manages policy decisions, approvals, and audit trails across autonomous agent fleets. Learn the architecture and why frameworks alone are not enough.
In-Process vs Out-of-Process AI Agent Governance: Trust Boundary Matters (2026)
Microsoft AGT, Galileo, and APort run in-process. Cordum runs out-of-process. Why trust boundary separation decides whether your AI agent governance survives compromise — and what regulated buyers' auditors expect.
Architecture.
Trust boundaries, control planes, and how Cordum's pre-dispatch model differs from in-process governance.
Stopping Agent Sprawl: Why You Need an AI Control Tower in 2026
ServiceNow and Microsoft are tackling 'Agent Sprawl' with AI Control Towers. Learn why discovery, inventory, and shared policy enforcement are the only ways to manage a fragmented agentic estate.
5 Decision Types Every AI Agent Needs in Production
The five policy decisions that keep autonomous AI agents safe: allow, deny, require approval, constrain, and remediate.
AI Governance in Production (2026): Policy-First Control Plane for Autonomous AI Agents
A technical guide to AI governance in production: pre-dispatch policy checks, approval binding, action constraints, output controls, and audit evidence.
What Kubernetes Taught Us About Governing Autonomous Systems
The agent governance problem looks like container orchestration in 2015. K8s patterns map directly to what agent fleets need.
Multi-Agent Orchestration Needs a Control Plane, Not Another Framework
Every framework is adding multi-agent support. None solve governance across agents. When delegated agents take risky actions, you need a control plane.
Introducing Cordum: The Control Plane for AI Agent Governance
Learn how Cordum adds policy enforcement, approval gates, and SIEM-ready audit trails to AI agent workflows.
Security.
MCP firewalls, prompt-injection containment, attack-vector analyses, and runtime hardening for coding agents.
MCP Firewalls and Runtime Hardening: OpenShell vs. Cordum (2026)
AI agent hardening has moved from prompt injection to 'Code Agency.' Compare OpenShell runtime isolation with Cordum's out-of-process governance and MCP firewalls.
How to Secure OpenClaw Agents in Production: Complete Governance Guide (2026)
A complete guide to secure OpenClaw agents in production with deterministic pre-dispatch governance, approval gates, fail-mode controls, and audit evidence.
MCP Security Risks (2026): 7 Exploitable Failure Modes and How to Detect Them
A production guide to MCP security risks with attacker preconditions, blast radius scoring, detection queries, and containment runbooks.
Policy as Code for AI Agents (2026): Rule Design, Simulation Gates, and Safe Rollouts
A production guide to policy as code for AI agents: deterministic decisions, constraints, simulation workflows, rollback strategy, and audit-ready evidence.
LLM Safety Kernel for AI Agents (2026): Deterministic Policy Decisions and Runtime Guardrails
A production guide to building an LLM safety kernel for AI agents: deterministic policy outcomes, approval binding, constraints, and output safety controls.
AI Agent Security Risks Enterprise Teams Miss: Why 74% See an Attack Vector (2026)
A data-driven enterprise guide to AI agent security risks with top-source gap analysis, runtime control matrix, policy code, and rollout tradeoffs.
Compliance.
EU AI Act, SOC 2, ISO 42001, audit trails, and the evidence regulated buyers' auditors expect.
AI Agent Audit Trails: Compliance Guide for Production Teams
A practical guide to designing immutable AI agent audit trails for compliance, incident response, and governance reviews.
The Agent Governance Maturity Model: Where Does Your Org Stand?
Most companies are at Level 0. Companies shipping agents to production are at Level 3+. A 5-level framework to assess and improve your governance posture.
Why 40% of AI Agent Projects Will Fail (and How Governance Prevents It)
Gartner predicts 40% of agentic AI projects will be canceled by 2027. The root cause is not bad models. It is deploying without governance.
AI Agent Audit Trail (2026): Decision-Level Evidence for Autonomous Workflows
A production guide to AI agent audit trails: decision records, approval lineage, policy snapshots, and run timelines you can defend in real audits.
AI Agent Incident Response Runbook: Severity, Triage, and Recovery Steps (2026)
A practical AI agent incident response runbook with severity triggers, first-15-minute checks, and concrete recovery commands.
AI Agent Compliance Mapping: SOC 2, ISO 27001, NIST AI RMF Runtime Playbook (2026)
Map autonomous AI agent controls to SOC 2, ISO 27001, and NIST AI RMF using runtime evidence contracts and approval integrity checks.
Comparisons.
How Cordum stacks up against IBM watsonx, Microsoft AGT, Temporal, LangGraph, and the agent framework field.
The 2026 Agentic Control Plane Buying Guide: IBM vs Microsoft vs Cordum
Compare the top AI agent control planes in 2026: IBM watsonx Orchestrate, Microsoft Agent 365, and Cordum. Learn about the 'Control Plane Buying Checklist' including RBAC, SSO, and policy-as-code.
CrewAI vs AutoGen (2026): Which Multi-Agent Framework Should You Ship?
A production-first CrewAI vs AutoGen comparison with migration risk, failure-mode testing, and governance patterns.
Temporal vs LangChain (2026): Durable Agent Architecture
Temporal vs LangChain is a layering decision: LangChain for agent logic, Temporal for durable execution, with practical thresholds and tradeoffs.
Temporal vs LangGraph (2026): Durable Agent Architecture
Temporal vs LangGraph for production AI agents: durability semantics, failure thresholds, and two-layer architecture patterns with working code.
MCP vs A2A vs CAP (2026): Protocol Boundaries, Governance Gaps, and a Production Blueprint
A technical comparison of MCP, A2A, and CAP with policy gates, approval flow, and deployment tradeoffs for production autonomous AI agents.
Temporal vs Cordum (2026): AI Agent Governance Comparison
A practical comparison of Temporal and Cordum for AI agents, with concrete retry semantics, rollback behavior, and governance architecture patterns.
Browse by category.
Filter the editorial set by Guide, Comparison, Deep Dive, or Release. Operational runbooks live under /blog/* but are kept off the index to keep this page scannable.
The 2026 Agentic Control Plane Buying Guide: IBM vs Microsoft vs Cordum
Compare the top AI agent control planes in 2026: IBM watsonx Orchestrate, Microsoft Agent 365, and Cordum. Learn about the 'Control Plane Buying Checklist' including RBAC, SSO, and policy-as-code.
Stopping Agent Sprawl: Why You Need an AI Control Tower in 2026
ServiceNow and Microsoft are tackling 'Agent Sprawl' with AI Control Towers. Learn why discovery, inventory, and shared policy enforcement are the only ways to manage a fragmented agentic estate.
MCP Firewalls and Runtime Hardening: OpenShell vs. Cordum (2026)
AI agent hardening has moved from prompt injection to 'Code Agency.' Compare OpenShell runtime isolation with Cordum's out-of-process governance and MCP firewalls.
In-Process vs Out-of-Process AI Agent Governance: Trust Boundary Matters (2026)
Microsoft AGT, Galileo, and APort run in-process. Cordum runs out-of-process. Why trust boundary separation decides whether your AI agent governance survives compromise — and what regulated buyers' auditors expect.
Defining Deterministic AI: Data vs Execution-Layer Control
Learn how data-layer accuracy, model probability, and execution-layer control differ, and why autonomous agents need deterministic governance.
AI Agent Compliance: EU AI Act, NIST, and Global Regulations (2026 Guide)
August 2, 2026 is the EU AI Act high-risk deadline. Maps Articles 9, 12, 13, and 14 to specific technical controls for autonomous AI agents. Covers EU, US, Singapore, China, and ISO 42001.
Agentic AI Governance: What It Means and How to Implement It (2026)
Agentic AI governance is the control layer for autonomous agents that act, decide, and delegate independently. Learn the architecture, decision model, and implementation patterns.
Multi-Agent System Governance: How to Govern Agent Fleets in Production (2026)
When agents delegate to other agents, governance becomes a fleet problem. Learn how to enforce policies, approvals, and audit trails across multi-agent systems with shared and per-agent rules.
What Is Human-in-the-Loop AI? A Clear Guide for Engineering Teams (2026)
Human-in-the-loop AI means a system cannot proceed without explicit human action at defined checkpoints. Learn how HITL works, where it matters, and how to implement it beyond prompt instructions.
What Is an AI Agent Control Plane? Definition and Architecture (2026)
An AI agent control plane is the governance layer that manages policy decisions, approvals, and audit trails across autonomous agent fleets. Learn the architecture and why frameworks alone are not enough.
LangChain vs LlamaIndex vs Semantic Kernel: Which Breaks First? (2026)
All three break without governance. 6 production failure modes — retry storms, state loss, approval bypass — mapped per framework with decision criteria.
Claude Code Leak Analysis (2026): What 500K+ Lines Reveal About Agent Permissions
Deep analysis of the Claude Code source leak. What the exposed harness reveals about permissions, context governance, and the controls every AI agent team should implement now.
AI Agent Security Risks Enterprise Teams Miss: Why 74% See an Attack Vector (2026)
A data-driven enterprise guide to AI agent security risks with top-source gap analysis, runtime control matrix, policy code, and rollout tradeoffs.
How to Secure OpenClaw Agents in Production: Complete Governance Guide (2026)
A complete guide to secure OpenClaw agents in production with deterministic pre-dispatch governance, approval gates, fail-mode controls, and audit evidence.
Pre-Dispatch Governance for AI Agents vs Post-Hoc Safety (2026)
A technical comparison of pre-dispatch governance for AI agents and post-hoc safety with real control-plane timing, fail modes, and validation checks.
AI Agent Orchestration Patterns: Cordum Architecture Deep Dive (2026)
A production guide to AI agent orchestration with code-accurate control-plane architecture, reliability guardrails, and rollout runbooks.
Prompt Injection vs Out-of-Process Governance for AI Agents (2026)
A production guide to prompt-injection mitigation for AI agents using out-of-process governance, fail-mode controls, and deterministic action boundaries.
AI Agent Incident Response Runbook: Severity, Triage, and Recovery Steps (2026)
A practical AI agent incident response runbook with severity triggers, first-15-minute checks, and concrete recovery commands.
AI Agent Compliance Mapping: SOC 2, ISO 27001, NIST AI RMF Runtime Playbook (2026)
Map autonomous AI agent controls to SOC 2, ISO 27001, and NIST AI RMF using runtime evidence contracts and approval integrity checks.
CrewAI vs AutoGen (2026): Which Multi-Agent Framework Should You Ship?
A production-first CrewAI vs AutoGen comparison with migration risk, failure-mode testing, and governance patterns.
Temporal vs LangGraph (2026): Durable Agent Architecture
Temporal vs LangGraph for production AI agents: durability semantics, failure thresholds, and two-layer architecture patterns with working code.
Temporal vs LangChain (2026): Durable Agent Architecture
Temporal vs LangChain is a layering decision: LangChain for agent logic, Temporal for durable execution, with practical thresholds and tradeoffs.
AI Agent Observability: Monitoring, Debugging, and Auditing Autonomous Agents (2026)
Traditional APM does not work for autonomous agents. Learn the three pillars of AI agent observability: decision tracing, behavioral drift detection, and governance audit trails.
AI Agent Sprawl: Why Ungoverned Agent Fleets Are Your Next Security Crisis (2026)
40% of enterprise apps will embed AI agents by 2026. Most teams have no inventory, no shared policies, and no audit trail across agents. Here is how to get control before sprawl becomes a breach.
MCP Security Risks (2026): 7 Exploitable Failure Modes and How to Detect Them
A production guide to MCP security risks with attacker preconditions, blast radius scoring, detection queries, and containment runbooks.
AI Agent Production Deployment Checklist (2026): 20 Controls with Pass/Fail Gates
A production AI agent checklist with 20 controls and pass/fail launch gates, including policy checks, canary thresholds, and rollback drills.
AI Agent Audit Trails: Compliance Guide for Production Teams
A practical guide to designing immutable AI agent audit trails for compliance, incident response, and governance reviews.
OpenClaw Governance: Add Guardrails in Production
A step-by-step tutorial for adding policy checks, approvals, and audit trails to OpenClaw workflows using an agent control plane.
Introducing Cordum: The Control Plane for AI Agent Governance
Learn how Cordum adds policy enforcement, approval gates, and SIEM-ready audit trails to AI agent workflows.
5 Decision Types Every AI Agent Needs in Production
The five policy decisions that keep autonomous AI agents safe: allow, deny, require approval, constrain, and remediate.
What Kubernetes Taught Us About Governing Autonomous Systems
The agent governance problem looks like container orchestration in 2015. K8s patterns map directly to what agent fleets need.
Multi-Agent Orchestration Needs a Control Plane, Not Another Framework
Every framework is adding multi-agent support. None solve governance across agents. When delegated agents take risky actions, you need a control plane.
The Agent Governance Maturity Model: Where Does Your Org Stand?
Most companies are at Level 0. Companies shipping agents to production are at Level 3+. A 5-level framework to assess and improve your governance posture.
Why Coding Agents Need a Control Plane
Claude Code, Cursor, and Devin have access to your repos, CI/CD, and secrets. Most teams hope the model behaves. Here is how to add policy enforcement and approval gates.
Agent FinOps: How to Stop AI Agents from Burning $10K in Tokens
When AI agents autonomously chain API calls, costs compound faster than dashboards can show. Policy-level budget enforcement evaluates cost before execution.
Why 40% of AI Agent Projects Will Fail (and How Governance Prevents It)
Gartner predicts 40% of agentic AI projects will be canceled by 2027. The root cause is not bad models. It is deploying without governance.
MCP vs A2A vs CAP (2026): Protocol Boundaries, Governance Gaps, and a Production Blueprint
A technical comparison of MCP, A2A, and CAP with policy gates, approval flow, and deployment tradeoffs for production autonomous AI agents.
Temporal vs Cordum (2026): AI Agent Governance Comparison
A practical comparison of Temporal and Cordum for AI agents, with concrete retry semantics, rollback behavior, and governance architecture patterns.
CAP Protocol Capabilities (2026): BusPacket, Safety Decisions, Heartbeats, and Deterministic Rollback
A technical guide to CAP protocol capabilities: typed envelopes, pre-dispatch policy decisions, approval binding, checkpoint heartbeats, and compensation-safe rollback.
MCP Governance (2026): Policy Gates for MCP Servers
A production architecture guide for MCP governance with pre-dispatch policy evaluation, approval gates, output safety, and operational SLOs.
Cordum v0.1.0 Release Notes: AI Agent Governance Control Plane
Technical release notes for Cordum v0.1.0: policy-first AI agent control plane with approvals, constraints, and audit-ready evidence.
How to Deploy AI Agents in Production (2026): Architecture, Rollout, and Governance Checklist
How to deploy AI agents in production with fewer incidents: architecture choices, phased rollout, policy gates, monitoring baselines, and rollback drills.
Model Context Protocol (MCP) Guide (2026): Architecture, Wire Flow, and Migration Plan
A practical MCP guide for production teams: architecture, JSON-RPC message flow, MCP vs function calling, and migration steps with tradeoffs.
Best AI Agent Frameworks 2026: LangChain, CrewAI, AutoGen
Compare LangChain, CrewAI, AutoGen, LlamaIndex, and Semantic Kernel by use case, failure mode, governance gap, durability, and audit readiness.
Human-in-the-Loop AI: 5 Patterns That Actually Work in Production
Five production human-in-the-loop patterns for AI agents: approval gates, exception escalation, graduated autonomy, sampled audit, and output review.
AI Agent Security Best Practices: 12 Production Controls (2026 Guide)
12 AI agent security controls that actually work in production. Covers pre-dispatch policy gates, least-privilege scoping, output quarantine, credential rotation, and validation runbooks with code.
AI Governance in Production (2026): Policy-First Control Plane for Autonomous AI Agents
A technical guide to AI governance in production: pre-dispatch policy checks, approval binding, action constraints, output controls, and audit evidence.
Policy as Code for AI Agents (2026): Rule Design, Simulation Gates, and Safe Rollouts
A production guide to policy as code for AI agents: deterministic decisions, constraints, simulation workflows, rollback strategy, and audit-ready evidence.
How to Add Approval Gates to AI Agents: A Step-by-Step Production Guide
Practical guide to AI agent approval workflows with pre-dispatch policy checks, risk-tier routing, Slack and email approvals, idempotency, and audit-ready evidence.
LLM Safety Kernel for AI Agents (2026): Deterministic Policy Decisions and Runtime Guardrails
A production guide to building an LLM safety kernel for AI agents: deterministic policy outcomes, approval binding, constraints, and output safety controls.
AI Agent Audit Trail (2026): Decision-Level Evidence for Autonomous Workflows
A production guide to AI agent audit trails: decision records, approval lineage, policy snapshots, and run timelines you can defend in real audits.
AI Workflow Orchestration (2026): Governance + Reliability
A production guide to orchestrating autonomous AI workflows with explicit DAGs, retry contracts, approval gates, and auditable run timelines.
Ready to govern your AI agents?
Cordum enforces policy before dispatch, requires approvals where risk demands it, and records a complete audit trail.