AI Agent Security
Why AI Infrastructure Needs a New Security Model
Traditional IAM secures human users, not AI agents making thousands of calls per minute. Why a connection-centric model is the right foundation.
Blog
Insights & updates — page 12
AI agent security, identity, governance, cost, and the engineering behind the control plane.
AI FinOps
The Unit Economics of Agentic Products
A framework for modeling unit economics in agentic products — cost per task as a variable formula, margin sensitivity, and the drivers that move it.
AI Governance & Compliance
How to Discover AI Agents: Methods Compared
How to discover the AI agents you run, compared: registration, repository scans, telemetry, access logs, consoles and surveys, and what each one misses.
AI FinOps
Reserved Capacity vs On-Demand LLM Spend
A decision framework for choosing reserved capacity versus on-demand LLM spend, based on workload predictability, volume confidence, and switching cost.
AI FinOps
A Procurement Checklist for Agentic AI Tools
A procurement checklist for evaluating agentic AI tools across cost structure, integration burden, governance fit, and organizational readiness.
AI Strategy
Guardrails vs Policies: Message Checks vs Traffic Rules
Guardrails check what is said; policies govern rate limits and time windows. How the two AI control layers differ, and why neither replaces the other.
AI FinOps
Negotiating LLM Provider Contracts
The commercial levers in an LLM provider contract — commitment structure, overage treatment, data-use terms, and portability — and how to evaluate each one.
AI FinOps
Costing AI Agent Downtime
A method for costing AI agent downtime as a formula across direct, cascading, and recovery terms, so availability investment can be sized rationally.
AI Governance & Compliance
AI Agent Governance vs Model Governance: What Differs
How AI agent governance differs from model governance: runtime controls on what a deployed agent may do, versus checks on the model itself.
AI Strategy
Building Secure Multi-Agent Workflows
Secure multi-agent workflows with authentication at every hop, scoped delegation tokens, and content guardrails on every message—three patterns explained.
AI FinOps
Chargeback vs Showback for AI Agent Costs
A decision framework for choosing chargeback or showback to allocate AI agent costs internally, with the data prerequisites and failure modes of each.
Platform & Operations
Scoping MCP Tool Permissions: Least Privilege for Tools
Grant AI agents the minimum MCP tool access they need — no more. Learn how allow-lists, per-tool rate limits, and policy gates prevent blast-radius breaches.
AI FinOps
Board Reporting on AI Risk
A template and cadence for reporting AI agent risk to the board — exposure, control coverage, incidents, and regulatory posture — in board-appropriate language.
Platform & Operations
MCP Server Security Checklist (OWASP-Mapped)
An MCP server security checklist in seven domains, from authentication and tool permissions to tool poisoning and logging, mapped to the OWASP MCP Top 10.
AI FinOps
The AI Agent Vendor Security Questionnaire
A ready-to-use security questionnaire for AI agent and MCP tooling vendors, covering identity, isolation, audit, retention, subprocessors, and exit.
AI FinOps
Building a Total Cost of Ownership Model for AI Agents
A TCO model structure for AI agents that covers inference spend, tooling, integration, oversight labor, and failure cost — with a worked illustrative example.
Platform & Operations
What Is the Model Context Protocol (MCP)? A Practical Guide
MCP gives AI agents a standard way to call external tools and retrieve context. Learn what it is, how it works, and the security controls it needs.
AI FinOps
Making the AI Agent Business Case to a CFO
How to structure an AI agent business case for a CFO — fully loaded cost, risk-adjusted value, payback framing, and the questions engineering teams miss.
AI Governance & Compliance
UK AI Regulation: What Agent Operators Need to Know
The UK governs AI agents through existing sector regulators and cross-cutting principles, not a single AI Act — the control mapping operators need to prepare.
Platform & Operations
API-First: The Praesidia API Surface
Every platform action is an API call. Learn how Praesidia's OpenAPI-described surface lets you automate governance, integrate tooling, and extend the platform.
AI Governance & Compliance
AI Regulation in the UAE and Saudi Arabia for AI Agents
The UAE and Saudi Arabia govern AI agents through national strategy bodies, data-protection law, and free-zone rules rather than a single binding AI statute.
AI Governance & Compliance
Singapore's Model AI Governance Framework, Applied to Agents
Singapore governs AI through a voluntary framework and testing tools rather than binding law — the control mapping agent operators should build anyway.
Platform & Operations
Platform Operator Access: What Praesidia Staff Can Do
How Praesidia's platform operators are kept apart from your organization's roles, which changes take two of them, and what they leave in your audit trail.
AI Governance & Compliance
South Korea's AI Framework Act: A Compliance Primer
South Korea's AI Framework Act creates a binding risk-tiered regime for high-impact AI — the obligations agent operators should map to now.