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#ai-explained

The AI Explained series: short, focused episodes on individual AI building blocks — transformers, attention, tokenization, memory, tool use, multi-agent systems, and more.

11 posts below, newest first.

Securing AI Agents from Doing Bad Things

Show notes for AI Explained Part 31 — sandboxing, permission scoping, instruction hierarchy, and the metrics that tell you whether your agent is safe to ship.

Subjects that frequently appear alongside #ai-explained. Click through to see every post on each one.

#ai 11 posts

How LLMs actually work — tokenization, embeddings, RAG, fine-tuning, agents — explained for engineers who ship production code, not papers.

#llm 11 posts

Large language models — how they think, why they fail, what RAG fixes, and how to evaluate them. The fundamentals every engineer building on top of an LLM should internalise.

#ai-agents 1 post

How autonomous AI agents reason, plan, use tools, and stay aligned with your intent — the ReAct loop, agentic RAG, and multi-agent orchestration.

#security 1 post

Practical software security for engineers — secrets handling, threat modelling, least privilege, prompt injection, sandboxing, and AI-specific attack surfaces.