Studying three coding-agent codebases, I kept seeing the same patterns. Same feature, 7.5x fewer tokens than the Clean Architecture version. I’ve been calling it Grounded Code, for now.
<a href="https://dev.to/jucelinux/your-codebase-has-a-new-primary-reader-and-its-paying-75x-more-3khn" target="_blank" rel="noopener nofollow">https://dev.to/jucelinux/your-codebase-has-a-new-primary-reader-and-its-paying-75x-more-3khn</a>

Laughing Face

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An analysis of three coding-agent codebases reveals recurring patterns that dramatically reduce token usage compared to Clean Architecture approaches — up to 7.5x fewer tokens for the same feature. The author introduces the term 'Grounded Code' to describe this emerging style optimized for AI coding agents as the primary readers of code.

Grounded Code

This is a useful framing: code now has a second primary reader — the coding agent.
That doesn’t mean “less architecture.” It means architecture needs to be cheaper to recover from context: clear data flow, fewer unnecessary layers, specs near the code, tests as harness, and docs/ADRs as the knowledge base.
The new quality question is:
How many tokens does an agent burn before it understands the safe change surface?
My take: future maintainable code will be spec-driven, harness-backed, and token-aware. Not just clean for humans, but grounded enough for agents to modify safely across sessions.