𝐃𝐞𝐬𝐢𝐠𝐧-𝐭𝐨-𝐂𝐨𝐝𝐞 𝐈𝐬𝐧’𝐭 𝐅𝐚𝐢𝐥𝐢𝐧𝐠 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲. 𝐈𝐭’𝐬 𝐅𝐚𝐢𝐥𝐢𝐧𝐠 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐂𝐨𝐡𝐞𝐫𝐞𝐧𝐜𝐞.

We keep blaming "complex UIs."

But that’s not the real problem.

Most AI design-to-code tools don’t fail because your layout is sophisticated.

They fail because they treat your Figma file like a flat image.

Pixels in. Code out.

No structure. No memory. No intent.

So what happens?

You tweak spacing. Regenerate.

A token changes. Regenerate.

A component evolves. Regenerate.

And suddenly your layout drifts.

Hardcoded values creep in.

Constraints disappear.

You’re diffing chaos.

It’s not a generation issue.

It’s an entropy problem.

When you flatten a scene graph into pixels, you lose hierarchy, auto-layout rules, design tokens, component boundaries. The model guesses. And guesses compound.

A better approach is less magical and more boring:

Treat Figma like a compiler would.

Parse the scene graph.

Preserve components and tokens.

Build an intermediate representation.

Generate deterministically into React, Vue, Flutter.

Now regeneration is stable.

Design changes map cleanly to code changes.

Constraints are enforced.

The AI doesn’t get "creative" with your layout.

It’s less wizardry.

But it’s more trustworthy.

The insight?

Design-to-code doesn’t need more intelligence.

It needs more coherence.

Automation isn’t about producing code once.

It’s about producing it again without drift.

Curious - where does drift hurt you most today?

Layout?

Tokens?

Responsiveness?

Component structure?

Let’s talk about the real failure mode.

marcello.cultrera@code-flow-lab.com