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05 articles
How to use AI coding assistants to systematically spot injection flaws, auth bypasses, and insecure defaults — with prompts that actually surface real problems.
AI defaults to generic patterns from its training data. Here's how to anchor generated code to your existing conventions — with examples, explicit constraints, and a drift-detection review.
How to prompt AI coding assistants to produce diverse, realistic test fixtures and seed data — not just placeholder values that pass but don't catch real bugs.
How to prompt AI coding assistants to produce pure functions, injectable dependencies, and explicit interfaces — so the generated code is easy to test before you write a single assertion.
Five battle-tested prompting patterns — structure, examples, decomposition, self-checking, and output contracts — that hold up when real traffic hits.