You’re using AI coding assistants wrong – they don’t need more freedom, they need better rails. 30 years of coding plus 8 years of AI work taught me why constraints beat creativity.
The story
I’ve spent 30 years writing code and the last 8 pioneering AI solutions. Here’s what nobody tells you about AI coding assistants: they don’t need more freedom – they need better rails.
Most teams hand AI a vague prompt and hope for brilliance. What they get is technical debt that compounds faster than their sprints. The difference between AI that transforms your workflow and AI that creates cleanup work? Constraints with purpose.
Spec-driven development is where this clicks.
You’re not giving AI creative license – you’re giving it precise requirements. Inputs, outputs, edge cases, performance constraints. This isn’t extra work. It’s the work you should be doing anyway, except now you have a partner executing at machine speed.
Custom instructions become your AI’s operating manual. They encode your team’s standards, your architecture decisions, your quality bar. Consistency beats cleverness every time. These instructions embed that consistency into every output.
This is what I mean by “agents on rails” – AI operating within defined scope, with specific tasks and clear success criteria. Instead of a general-purpose AI trying to solve everything, you get specialized agents doing one thing exceptionally well.
Why this compresses development cycles:
Precise specs mean AI generates production-quality code on the first pass. Rails prevent drift. Human oversight stays meaningful – you’re reviewing focused code, not sorting through creative chaos. The specs you write today become reusable patterns tomorrow.
Here’s what makes this stick: involving your team in defining those s
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