Stop "Vibe Coding" and Start Driving: Mastering the CLEAR Framework

Most of us are trying to race an F1 car without learning how to drive first.

I had the chance to sit down with Matt Green and Moshe Mikanovsky on the Product for Product Podcast (EP 147) to talk about something I've been working through with engineering teams: how to move beyond intuition-driven AI coding (a.k.a. "vibe coding") and into a methodology that actually ships production software.

EP 147 - AI Tools: CLEAR with Marcos Polanco

The Problem with How We're Using AI Right Now

The tools are extraordinary. Bolt.new, Cursor, Claude, Gemini...the raw capability is genuinely staggering. But capability without structure is how teenagers crash fast cars.

In the episode, we used the F1 analogy because it fits: driving one of those cars at full throttle without training doesn't make you fast...it puts you straight into the wall. That's exactly what happens when engineers add requirements "willy-nilly" in conversation.

The CLEAR Framework

CLEAR is the methodology I developed to give AI the structure it needs to produce work you can actually ship:

C - Context Onboard the AI like a new hire. Use Behavior-Driven Design (BDD) to define clear, testable expectations before a single line of code is written. If the AI doesn't understand the job, no amount of prompting fixes it downstream.

L - Layout Act as the manager. Break the project into scoped, bounded pieces. An AI handed a large, ambiguous task just gets confused.

E - Execute Use Test-Driven Development (TDD). Have the AI write the tests first, then write the code to pass them. This is a massive forcing function for quality.

A - Assess Use a second, independent LLM to QA the work. If you're coding with Claude, verify with Gemini. Run "5 Whys" on any bug before accepting a patch.

R - Run Ship it, instrument it, and feed analytics back into the next iteration. Loop, closed.