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18 minutesPydantic is all you need: Jason Liu
Learn why schema-first LLM calls need typed objects, validators, retries and explicit handling for malformed or hallucinated fields.
Watch nextAndrej Karpathy. This is the clearest end-to-end explanation on YouTube of what an LLM actually is — pretraining, tokenization, SFT, RLHF, reasoning RL, tool use, hallucinations — at the level of detail an engineer needs to reason about model trade-offs. Watch it once and the "GPT-class vs. open-weights vs. reasoning model" decisions in the article stop feeling like brand choices and start feeling like training-recipe choices.
Model names, pricing and capabilities change quickly. Use this for the decision pattern, then verify current model behavior before adopting it.
This is the clearest end-to-end explanation on YouTube of what an LLM actually is — pretraining, tokenization, SFT, RLHF, reasoning RL, tool use, hallucinations — at the level of detail an engineer needs to reason.
Continue through the same learning path with the next curated companion videos.
