Intelligence + Continual Learning = Expertise — Yu Su, NeoCognition
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- context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
It gives a precise account of why coding agents generalize where other agentic work does not, which is directly useful when scoping what an can be trusted to do.
“Scheduling a meeting is not finding a shared slot on everyone's calendar. It is a constraint optimization over authority, priority, and urgency, and an expert sees that immediately where a very capable model does not.”
AI Engineer
“Expertise is accumulated, situated competence, and almost nobody is scaling it.”
AI Engineer
“Code is already a language native world, symbolic and structured, with tests standing in for rewards. The rest of digital work is millions of micro worlds, each with its own local physics, far too heterogeneous for one static model to compress.”
AI Engineer
“scale intelligence alone and you get what he calls the world's smartest novice, brilliant at whatever is put in front of it and accumulating nothing between problems”
AI Engineer
“if continual learning gets good enough past some threshold of raw capability, the thing worth scaling stops being the model”
AI Engineer
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