Effectiveness anti-patterns — part 6: YAGNI: don’t abstract before the second use case
A practical YAGNI story from data engineering: keeping a CI workflow intentionally narrow until the second real use case appeared.
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Code Quality
How I improved AI-generated Python code by setting clear instructions
A reflection on turning one AI-generated Python prototype into reusable coding-agent guidance: clearer implementation boundaries, stronger quality expectations, and a shared quality bar before prototypes become real tools.
Shaping with AI
Clean, structured, multi-destination, non-blocking logging in Python
Still relying on print statements to debug your Python code? There’s a much better way: clean, structured, multi-destination, non-blocking logging.
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