I Reduced AI Coding Iterations by 70%

I reduced AI coding iterations by 70% after testing countless agentic coding strategies.

The most efficient approach boils down to one principle: write the specification, then let the AI build to spec.

Most developers waste hours in back and forth cycles because they skip straight to implementation. This five step framework eliminates that friction.

Here is how it delivers results:

Step 1: Define the feature with surgical precision Start with a clear outcome statement. Tight scope accelerates AI performance.

Step 2: Create a comprehensive specification document Document the user journey, technical requirements, edge cases, and success metrics. This becomes your blueprint.

Step 3: Enrich with repository context using a framework Feed in architecture patterns, coding standards, and existing components. Cursor, Claude Code, and Antigravity all capture this intelligence effectively.

Step 4: Run plan mode to surface gaps Use plan mode (available in all three tools) to identify implementation risks and refine context before coding begins. This surfaces issues when they cost least to fix.

Step 5: Execute with the complete guide Hand the refined specification to the editor and watch it ship the implementation with minimal supervision.

Critical addition: Include testing criteria and evaluation metrics in your initial prompt. When agents know how you will grade their work, accuracy and throughput improve dramatically.

I built a reusable framework guide that streamlines this entire process. DM me and I might share the template. Happy to chat through specific implementation challenges.