Non-Coder Builds AI Prompt Diagnostic Framework with Claude Over Many Sessions

A Reddit user has shared their experience building a project called SMARRT — a diagnostic framework that audits AI prompts before generation — over multiple months, using Claude as their primary collaborator. The user is not a coder, so the entire build was conversational: long sessions of architecture work, framework design, stress-testing logic, and refining how the system handles ambiguous user intent.

How Claude Helped

• Worked through the framework architecture when the user couldn't see the structure yet
• Drafted and refined diagnostic layers (image first, video in progress)
• Acted as a developmental thinking partner — catching gaps in logic, pushing back when something didn't generalize, asking questions the user hadn't thought of
• Stress-tested the framework against edge cases the user couldn't have generated on their own
• Translated vague intuitions into structured, repeatable rules

The honest assessment: SMARRT wouldn't exist in its current form without Claude — not because Claude wrote it, but because Claude held the developmental editor role the user would otherwise have had to hire for.

What SMARRT Does

When a prompt lacks mechanical anchors, models fill gaps with defaults — producing outputs that look polished but miss the intended goal. SMARRT runs a diagnostic on prompts before generation and asks targeted clarifying questions to surface missing intent. Currently it works confidently for image prompts; video is in active development. The underlying framework is intended to generalize beyond these domains.

The user created a free 3-page Image Diagnostic Guide that explains how to apply the framework manually (link in the original Reddit post).