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1
Inside an LLM: Corpus to Next Token
Follow the full lifecycle: corpus and tokenizer, learned vectors and the transformer block, the pre-training that chooses the numbers, and one-token-at-a-time decoding.
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2
Reasoning Effort
The knob buys serial compute. Its returns are concave and task-dependent. How to set it without superstition.
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3
Orchestration and Subagents
One context window is the wrong shape for big work. Fan-out, pipelines, and verification with a return contract.
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4
Loops and Skills
The while-loop that turns a text predictor into a worker, and procedure packaged as files an agent loads on demand.
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5
Harness Engineering
The software around the model: tools, permissions, context budgets, and feedback design. In preparation.