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The big picture
Large language models (LLMs) — the technology behind Claude, ChatGPT, Gemini, and Grok — are systems trained on huge amounts of text that can read, write, reason, and increasingly act: using tools, browsing, writing code, and completing multi-step tasks as "agents." Enterprises use them for customer support, coding, document analysis, research, and workflow automation. What's state-of-the-art changes every few months — which is exactly why this site exists.
The security angle
- Prompt injection — attackers hide instructions in content an AI reads, tricking it into leaking data or acting badly.
- Data leakage — what goes into an AI tool may leave your control; no-training guarantees matter.
- Shadow AI — employees using unapproved tools. Governance beats prohibition.
- Agent permissions — an AI that can act needs least-privilege thinking, like a new hire's account.
The product angle
- Build on APIs, differentiate on your data and workflow — your integration and evals are the moat.
- Evals before vibes — measure output quality on your tasks before and after every model swap.
- Human-in-the-loop — ship AI features with review steps first; remove them as confidence grows.
Learn the language
Every term you'll meet in these stories is explained in plain English in the AI, decoded page.