The internals, in plain words.
Internals Decoded explains the internals of AI in plain, conversational language. We take apart the models, agents, and tools shaping the world right now and explain them in plain words, deep enough to be true and simple enough to follow. The whole library is free to read.
Deep and readable, at once.
Most writing about AI picks a side. It is either rigorous and impenetrable, or friendly and shallow. We try to hold both, so the same piece can meet you whether the topic is new to you or something you already build with every day.
Go under the hood, every time.
The question is always what is really going on inside, from a beginner’s first prompt to a production agent system. We show the structures underneath, the tradeoffs behind them, and why things are the way they are, in language you can actually follow.
You keep hearing these terms and want to understand what is actually happening underneath, not just the headline.
You work with these tools and want the model behind the model, so the tradeoffs you make are informed ones.
You design systems and need the reasoning behind a design, not just the recipe, so you can adapt it to your own.
Everything here is free to read, and there is a lot of it. If your team is building with AI and wants a hand with the hard parts, we would be glad to hear about it.
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