Learn AI Agent Security

A plain-English guide to generative AI — what it is, how large language models work at a high level, and what they can and cannot do today.

Learn what a prompt is, why the way you ask matters, and practical tips for getting better results from any AI tool.

AI agents can send emails, book meetings, and spend money on your behalf. This article explains what agents are, why permissions matter, and how to stay in control.

AI tools sometimes make things up. This article explains why it happens, how to spot it, and practical ways to reduce it with better prompting.

A practical guide to writing better AI prompts. Includes five before-and-after rewrites that show exactly how small changes produce dramatically better results.

A plain-English comparison of the three most popular AI assistants. What each does well, where each falls short, and how to choose the right one for your needs.

AI agents do not just talk — they act. This article explains the key difference between chatbots and agents, and why autonomy, tool use, and memory change everything.

Concrete examples of what AI agents can do right now — from booking travel to writing reports to managing code. No hype, just real capabilities and honest limitations.

Tokens are how AI models measure text. This article explains what they are, why they affect your experience, and what context windows and token limits mean in practice.

What happens to your data when you use ChatGPT, Claude, or Gemini? This article explains training data policies, how to opt out, and what enterprise plans offer.

MCP is a standard that lets AI models connect to external tools safely. This article explains what it is in plain English, why it matters, and how it connects to Multicorn Shield.

Most AI agents ask for far more access than they need. This article explains the principle of least privilege in plain English and shows you how to think about scoping what an agent can do.

AI agents can send the wrong email, make an accidental purchase, or delete important files. This article walks through real error scenarios and explains why guardrails need to exist before something goes wrong.

A practical guide to spending controls for AI agents — per-transaction limits, daily caps, and approval thresholds. Includes real examples and shows how Multicorn Shield enforces them.

An audit trail is a tamper-evident record of everything your AI agent does. This article explains what that means, why it matters for compliance, and how it helps you stay in control.

A practical checklist for deciding whether an AI agent is safe to deploy. Covers permission footprint, data handling, spending controls, kill switches, and more.

A practical guide for teams of 10-50 people: which tasks to automate with AI agents, which to keep human, and how to roll out safely without a dedicated AI team.

The story behind Multicorn Shield: an AI agent called OpenClaw, a $200 dinner no one approved, and the open-source permissions layer we built to make sure it never happens again.