How I use LLMs
Andrej Karpathy. Karpathy spends explicit chapters on "Be aware of the model you're using, pricing tiers" and "Thinking models and when to use them," then keeps switching between ChatGPT, Claude, Gemini, Grok, and Perplexity throughout the rest of the walkthrough. It is the closest thing to watching the article's cheat sheet applied live by someone with strong opinions about when each tier earns its keep.
AI Expert note
The model-picker habits are valuable; exact model names, prices, context limits and rankings are not stable. Re-run the comparison on your own tasks before standardizing a team recommendation.
What you should get from this
Learn to route work across fast, cheap, deep-reasoning and source-grounded tools instead of using one model for everything.
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Comfort using at least one mainstream chatbot and comparing outputs on the same task.
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MCP is the protocol that's quietly replacing one-off tool integrations across the AI tooling ecosystem. Learn it from the source. By the end you'll have built and deployed your own MCP server, connected an LLM client to it, and understood why this standard is the closest thing the field has to USB-C.