AI Strategy
How to Roll Out AI Agents Safely
A staged rollout playbook for AI agents: inventory risk, run a scoped pilot with guardrails in place, define go/no-go criteria, and expand on evidence.
Blog
Insights & updates
AI agent security, identity, governance, cost, and the engineering behind the control plane.
AI Agent Security
Trust Scoring Models for Autonomous Agents
How agent trust scoring models aggregate identity, behavior, and attestation signals into a runtime gate that controls what autonomous agents can do.
AI Agent Security
Tool-Use Safety: Sandboxing Agent Actions
Contain what AI agent tools can do: tool-level scoping, allow-lists, dry-runs, and human approval gates for high-consequence irreversible actions.
Platform & Operations
How to Rate-Limit AI Agents
Design abuse-resistant rate limits for AI agents: choose the right unit, window shape, and enforcement scope to protect costs and downstream systems.
AI Governance & Compliance
Designing Guardrails: Block, Redact, or Warn?
Choose the right enforcement action for AI agent guardrails — block, redact, or warn — and understand the fail-open vs fail-closed security trade-off.
AI Governance & Compliance
Audit Trails That Hold Up: Cryptographic Integrity
What makes an audit trail credible to an auditor or court: hash-chaining, per-row digital signatures, and external anchoring explained for engineering teams.
AI Governance & Compliance
How to Keep PII Out of Agent Prompts and Logs
Keep PII out of AI agent prompts, responses, and logs using detection-and-redaction controls that satisfy GDPR, HIPAA, and audit requirements.
AI Agent Security
Secrets Management for AI Agents
Keep API keys and credentials out of agent prompts and source code. The four pillars of secrets management: storage, delivery, access control, and rotation.
Identity & Access
RBAC vs ABAC for AI Platforms
RBAC governs who can configure agents; ABAC governs what agents can do per request. Learn which model fits each authorization decision on an AI platform.
AI Strategy
What Is an AI Control Plane?
An AI control plane unifies identity, policy, guardrails, and audit across your entire agent fleet — so you govern every AI interaction from one place.
Identity & Access
How to Implement Least Privilege for AI Agents
Apply least privilege to AI agents with scoped credentials, per-connection policies, and delegation constraints that shrink your blast radius.
AI Strategy
Self-Hosted vs Managed AI Governance
Self-hosted AI governance gives full data residency control; managed shifts operational burden to the vendor. How to choose for your team.
AI Strategy
Choosing an AI Agent Management Platform: A Buyer's Guide
A structured buyer's framework for evaluating AI agent management platforms across identity, governance, cost control, observability, and compliance evidence.
Platform & Operations
How to Monitor MCP Tool Calls
Gain full visibility into every MCP tool call an AI agent makes — with attribution, policy decisions, and cost data needed for security and compliance.
Platform & Operations
Orchestration Patterns for Multi-Agent Systems
Compare pipeline, hub-and-spoke, and blackboard orchestration patterns for multi-agent AI — with security, cost, and auditability trade-offs for each.
AI Agent Security
Agent-to-Agent Protocols and Interoperability
How to design safe A2A interoperability: agent cards, secure discovery, scoped credentials, and cross-org trust — in under 8 minutes.
AI Governance & Compliance
Human-in-the-Loop Approvals for High-Risk Agent Actions
Human-in-the-loop approvals pause AI agents before high-risk actions, preserve throughput with async queues, and build an auditable approval trail.
AI FinOps
Cost Control for LLM Applications
Where LLM costs hide in agentic applications, how to attribute them per agent and run, and the reservation-based enforcement that stops overspend at dispatch.
Platform & Operations
Observability for AI Agents: Logs, Metrics, and Traces
How logs, metrics, and distributed traces apply to AI agents—what to instrument, where costs hide, and how to connect all three for fast incident triage.
Platform & Operations
Rate Limiting and Abuse Prevention for AI APIs
Request counts alone don't protect AI APIs. The layered controls that work: per-connection limits, spend caps, tool allow-lists, and trust gates.
AI Agent Security
Data Exfiltration Risks in Agentic AI
Agentic AI creates novel data exfiltration paths via over-broad tool access, chatty outputs, and prompt injection. Learn how to contain each risk layer.
AI Agent Security
Prompt Injection: Threats and Defenses
Prompt injection hides malicious instructions in content AI agents process. How direct and indirect variants work, and what defenses reduce the risk.
AI Agent Security
Zero Trust for AI Agents
Zero trust for AI agents means verifying every identity, enforcing least-privilege policy at every hop, and using behavioral trust scores at runtime.
AI Governance & Compliance
SOC 2 for AI Platforms: What Auditors Look For
SOC 2 auditors scrutinize AI platforms harder than traditional SaaS—learn which controls matter most, from tamper-evident audit trails to agent access.