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Practical guides to AI-driven development, full-stack architecture, and solving production problems.
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Use AI to reproduce a bug before asking it to fix anything
Turn an intermittent bug report into a controlled reproduction before using AI to propose a fix, then prove the correction changes the same observable failure.
Review an AI generated pull request for plausible but wrong code
Review AI generated code by tracing contracts, challenging assumptions, and reproducing failure paths that a passing build and plausible diff can easily miss.
Give an AI coding assistant enough repository context without overwhelming it
Build a focused context packet for an AI coding assistant using the real entry point, data contract, neighboring patterns, and checks needed for one repository change.
Turn a vague feature request into a testable engineering plan
Turn an ambiguous feature request into observable behavior, explicit constraints, and a small engineering plan an AI assistant can implement and you can verify.
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