Lua Coroutines and Metatables: The Cheat-Sheet Course
by Victor Chen
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The two Lua features people fake for years, explained properly in under an hour.
Learn Python by automating spreadsheets, files and reports you would otherwise do by hand.
Write Python that scales past a single script and survives contact with a team.
Ship a typed, validated and documented Python API with async endpoints and real tests.
Enough Python to read code and write a useful script, in a single focused hour.
Complexity, structures and problem patterns taught for real code and real interviews.
Write the tests that catch real bugs and delete the ones that only slow you down.
Ninety debugging prompts that push a model past the obvious answer toward the real cause.
One hundred and twenty prompts that turn untested code into a suite you can trust.
Twenty-four agent blueprints with tool schemas, system prompts and real stop conditions.
Prompts that write, explain and stress-test SQL against a schema you paste in yourself.
Understand why models drift, then write instructions that hold across a long conversation.
Fit the right material into a context window and cut token spend without losing accuracy.
Design tool schemas a model calls correctly, and handle the failures when it does not.
Build a small eval suite that tells you honestly whether a prompt change was an improvement.
Move from clever one-off prompts to versioned, tested prompt systems a team can maintain.
Expose your own data and actions to assistants through MCP servers you write and control.
The full craft: prompt architecture, agent loops, evaluation harnesses and cost discipline.
Your first month with model APIs: keys, streaming, retries, cost and one shipped feature.
Understand embeddings well enough to build search that finds meaning, not just keywords.
Chunking, hybrid search and reranking, the parts that decide whether retrieval really works.
Pick, index and operate a vector store without turning your search into a science project.
Build a dataset, run a LoRA fine-tune, and prove it beats prompting for your narrow task.
The maths-light foundation that makes model behaviour, metrics and failures make sense.