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Testing your AI generated code like a human reviewer

Testing your AI generated code like a human reviewer The best test I know for agent written code: delete the implementation and see if the tests fail. If they still pass, they were never testing anything. Agents love writing tests that only check the code runs and not that it is right. Add one rule to your rules file. Make every test prove a behavior, not an implementation detail. That single…

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You do not need a big AI setup to get value

You do not need a big AI setup to get value The most useful AI workflow I have is one file. A short AGENTS.md contract that tells the agent how to behave in my repo. No framework. No prompt library.

Compression Is Prediction — and It Explains Why LLMs Actually Work

Here's something that blew my mind recently: compression and language modeling are, at their core, trying to solve the exact same problem.

  • LLMs function as advanced compression algorithms predicting next data in sequence
  • Training minimizes cross-entropy loss, reducing bits to encode training data
  • Improved compression methods enhance LLM performance and expand capabilities

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