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No jargon for its own sake. No sales copy dressed up as explanation. Just honest accounts of how these things actually work.

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The universe · 40+ concepts, 22 fields, 60+ tools

See every field, concept, and tool — and where you fit.

A spatial map of the whole archive. Take the quiz to overlay your own trajectory through it.

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Field guides

AI in your field →

What these concepts actually mean for medicine, law, design, finance — and 16 other fields.

All concepts — 40 articles

Agentic Memory

How AI agents remember things across runs — and why most of them don't, really.

5 min read→

AI Agents

When AI stops answering and starts doing — and then, very often, hits a wall

9 min read→

AI Safety & Alignment

The problem of building AI that reliably does what you actually wanted — not what you literally asked for

11 min read→

Attention

The single mechanism behind every model since 2017 — and the one that quietly burns most of the compute.

8 min read→

Chain-of-Thought

When 'think step by step' actually earns its keep — and when it's just expensive theater.

6 min read→

Constitutional AI

When the model judges itself — Anthropic's bet on alignment without exhausting the rater pool.

6 min read→

Context Windows

What the model can see right now — and why the edges matter

6 min read→

Diffusion Models

How AI learned to make images by starting with pure noise and finding the signal

8 min read→

Distillation

Teaching a small model to imitate a big one — and what gets lost in the lesson.

5 min read→

DPO

The cheaper, often-as-good RLHF alternative — and why most labs quietly moved to it.

6 min read→

Embeddings

The coordinates that give language a sense of direction

7 min read→

Evals

How you measure whether a model is good at the thing you actually care about.

5 min read→

Fine-Tuning

Teaching a model new habits, not new knowledge

8 min read→

Function Calling

The JSON-shaped API that turned chat models into clients of the real world.

6 min read→

Hallucination & Grounding

Why AI models confidently make things up — and what you can actually do about it

8 min read→

In-Context Learning

How models 'learn' from examples in the prompt — without changing a single weight.

6 min read→

Jailbreaks

How users get aligned models to do what they were trained not to do.

5 min read→

KV Cache

Why long conversations are cheaper than they look — and the reason your API bill behaves the way it does.

5 min read→

Model Context Protocol

The open standard that lets AI models talk to your tools without a custom integration per model

7 min read→

Mixture of Experts

How modern models pretend to be huge while doing the work of something smaller.

5 min read→

Model Cards

The documentation labs publish when they release a model — and what they leave out.

4 min read→

Model Collapse

What happens when models train on text written by other models — recursively.

4 min read→

Multiagent Systems

What happens when AI models try to coordinate with each other — and the new failure modes that come with it

9 min read→

Multimodal Models

When AI learned to see, listen, and read — at the same time, in the same head

7 min read→

Prompt Engineering

The craft of talking to a model that will take you exactly as literally as it decides to

7 min read→

Prompt Injection

The new SQL injection — when input data quietly becomes instructions the model follows.

5 min read→

Quantization

Why a 70B-parameter model can run on your laptop — and the quality you trade for it.

5 min read→

Retrieval-Augmented Generation

How AI learned to look things up before opening its mouth

8 min read→

Reasoning Models

What changed when models started thinking before they answered.

6 min read→

Retrieval & Reranking

Why the document your RAG system retrieves first is rarely the document you want.

5 min read→

RLHF

Humans rate, model learns, weird things happen — the post-training that made models pleasant to talk to.

7 min read→

Scaling Laws

Why bigger keeps working — and the question of where it stops.

7 min read→

Structured Output

Forcing the model to fill in a shape — and why it's harder than it looks.

5 min read→

Synthetic Data

Models training on text other models wrote — and why this isn't always bad.

5 min read→

Temperature & Sampling

Why 'more creative' is not the same as 'more random' — and the knobs that actually matter.

5 min read→

Tokenization

The first thing every model does to your words — and the thing that quietly limits what it can do.

6 min read→

How AI Models Are Trained

From random noise to a model that can reason — the actual pipeline

10 min read→

Transformers

The architecture that changed what AI could do with language — and then everything else

8 min read→

Vision-Language Models

How CLIP and its descendants taught text and images to live in the same coordinate system.

5 min read→

Watermarking

Invisible signatures on AI-generated text — and why most don't survive contact with reality.

4 min read→