The Stack
An AI agent is a system that uses a language model to do a job for you — not just answer a question, but pick the next step, use tools, and keep going until the work is finished. A chatbot waits for you. An agent takes the goal and acts. That
The Frontier
Fine-tuning is the step where an AI model that was already trained on a huge, general dataset gets trained a little more on a smaller, specific dataset — so it becomes an expert at one particular job instead of a jack-of-all-trades. It is the most common word
The Frontier
Test-time training (TTT) is a technique where an AI model keeps learning — updating its own weights — while it is actually working on a task, instead of arriving fully formed from its one-time training phase. It is the difference between a worker who shows up with a fixed instruction
The Stack
MCP — the Model Context Protocol — is an open standard that lets AI assistants plug into external tools and data sources the way a USB-C cable plugs into any device. It gives a chatbot or agent a universal socket for databases, calendars, code repos, calculators, and thousands of other systems,
The Stack
RAG — retrieval-augmented generation — is a technique that lets an AI model look things up in a document store before it answers, by pulling the most relevant passages into the conversation. Instead of relying only on what it memorized during training, the model gets the right pages placed in front
The Frontier
An open-weight model is an AI model whose trained parameters — the billions of numbers that encode everything it has learned — are released for anyone to download, run, modify, and build on. The weights are the model: once they are public, the technology itself is out in the world, not
The Frontier
A context window is the amount of text a language model can look at at one time — its working memory. It is measured in tokens (roughly three-quarters of an English word each), and it caps how much of your prompt, your conversation, or your document the model can actually
The Frontier
Chain of thought is the step-by-step reasoning a language model generates before it gives a final answer — the "show your work" part of AI problem-solving. Instead of jumping straight from question to answer, the model writes out its intermediate steps, and that simple change measurably
The Guardrails
AI watermarking is a hidden, machine-readable signature embedded in AI-generated content — text, images, audio, or video — that lets a detector verify which model produced it. You can't see it, and neither can most people who copy or edit the content; it's a pattern woven
The Guardrails
Prompt injection is a security exploit in which hidden instructions inside text an AI reads trick it into doing something its user never asked for. The AI doesn't get hacked the way a server gets hacked — it gets talked into behaving badly by words on a page. It&