After 30+ years coding, I’ve watched teams waste hours on AI that generates creative but wrong solutions. The AI isn’t broken – your instructions are missing.
The story
After 30+ years writing code and 8 years building AI solutions, I’ve watched teams waste countless hours wrestling with AI that generates creative but wrong solutions. The AI isn’t broken – your instructions are missing.
Here’s the pattern: developers treat AI coding tools like magic boxes. Throw in a prompt, hope for decent output. When GitHub Copilot or Claude generates code that doesn’t match your patterns, uses the wrong libraries, or violates your security practices – that’s not an AI problem. That’s a specification problem.
You’re asking it to guess what you want instead of telling it what you need.
Spec-Driven Development: Give Your AI Rails
Create a `.github/copilot-instructions.md` file in your project. Define your coding standards, tech stack, data access patterns, security requirements. The AI reads this before suggesting code.
Suddenly your AI assistant generates code that fits your existing systems. Not because the AI got smarter – because you gave it context and constraints.
I’ve seen development teams save 25 hours weekly once they implemented clear specifications for their AI workflow. The difference between chaos and productivity is how well you define requirements upfront.
Why This Actually Matters
Consistent specifications mean consistent code. Security requirements become automatic checks. Maintainability improves because the AI learns your patterns and applies them everywhere.
This is where most AI consulting falls apart – they sell you tools without teaching your team how to instruct them. Teaching developers to write better specificatio
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