How teams and practices change when the model writes the code.
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If you want to understand why AI works the way it does today, you don't need to read a hundred papers. You need to read about five, in order, and understand what each one changed. Everything since is, to a first approximation, a refinement or a scaling-up of ideas these introduced.
When you build software with an AI agent day to day, the thing you run out of first isn't intelligence — it's context. The window is finite, attention inside it isn't free, and a session that starts sharp gets duller as it fills with the exhaust of the work: verbose command output, whole files read to find one function, stale documentation, the residue of three tasks ago.
Here is a shift that has already happened, whether or not your documentation noticed: a large and growing share of the readers of everything you write are no longer human. They're language models — reading your docs to answer a question, your README to use your library, your marketing page to tell someone what you do. Andrej Karpathy has been making this point for a while, and it lands harder every month: the primary reader of a lot of your writing is now an LLM, and you are probably still writing for a human.