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Explainers

The concepts behind the launches, explained once and kept current — so the next announcement makes sense.

65 stories

All explainers · 65

Research · ExplainerHow to read a system card: a builder's guide to AI safety documentationSystem cards run to hundreds of pages. What the sections mean, which safety frameworks they report against, how to read eval tables critically, and a checklist.Oct 9·7 min read

Research · ExplainerContext windows vs memory vs RAG: what each one actually doesA 1M-token window, a chatbot that "remembers you" and a retrieval pipeline solve different problems. Here's how each works and when to use which.Oct 9·7 min read

Developers · ExplainerMCP resources vs tools vs prompts: who decides, and when to use eachMCP servers expose three primitives with three different owners: the model, the app and the user. Here's how each works on the wire in the 2026-07-28 spec, plus what happened to sampling, roots and elicitation.Oct 9·6 min read

Agents · ExplainerWhat "agentic" really means in 2026Every AI product now calls itself agentic. Here's the definition the labs themselves use, how the tool loop works, and how to tell a real agent from a relabeled chatbot.Oct 9·6 min read

Agents · ExplainerWhat is MCP? The Model Context Protocol explained (2026 edition)MCP is the open standard that lets AI apps plug into tools and data. Here's how it works, who governs it, what changed in the stateless 2026-07-28 spec, and where the risks are.Oct 9·9 min read

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