Enforcing consistency costs almost nothing now.

Structure used to be expensive.

Templates took time. Reviews took energy. Enforcement took social capital.

AI changed that.

Structure Is No Longer a Bottleneck

We can now ask for:

  • the same format
  • the same sections
  • the same tone
  • the same constraints

Every time. Without friction.

That makes structure cheap.

Before AI, enforcing structure was a people problem. You could create templates and style guides, but getting engineers to follow them required constant effort.

Code reviews became battles over formatting. Someone would submit a PR with inconsistent naming. A reviewer would request changes. The author would push back. “Does it really matter?” The reviewer would either spend energy explaining why it matters or let it slide to avoid conflict.

This social cost was real. Strict reviewers got labeled as nitpicky. Lenient reviewers saw standards erode. Either way, maintaining consistency required continuous friction.

AI eliminates most of this. Instead of debating whether to follow the template, engineers just ask AI to apply it. No argument. No judgment. Just consistent output.

This changes the economics of structure. When enforcement is free, you can have much stricter standards without creating friction.

Cheap Structure Raises the Floor

When structure is easy, standards rise naturally.

Fewer incomplete artifacts. Fewer unclear decisions. Fewer one-off approaches.

Not because people are better. Because the system supports them.

We saw quality improve across the board, not because engineers changed behavior, but because the default improved.

Before AI, incomplete documentation was common. Engineers would write a quick README and move on. Filling in all the sections felt like busywork. The trade-off between speed and completeness favored speed.

With AI, completeness is cheap. Engineers draft the basics. AI fills in missing sections based on patterns from similar services. The engineer reviews and refines. The result is complete documentation without the tedious work.

This raised the floor. Even services created quickly under pressure had reasonably complete docs. Not perfect, but far better than what we used to accept as “good enough.”

The same thing happened with code quality. Consistent formatting, predictable structure, and standard patterns became the default. Engineers no longer had to choose between moving fast and following conventions. They could do both.

This Is an Underrated Shift

Most teams use AI to generate content.

We use it to enforce shape.

That difference is subtle. It matters a lot.

Generating content is useful. AI can write boilerplate, draft documentation, and suggest code. These are valuable capabilities.

But enforcing shape is more powerful. It means using AI to ensure that whatever gets created follows team standards.

Instead of asking AI to write a README from scratch, we ask it to reformat an existing README to match the template. Instead of asking AI to generate code, we ask it to refactor code to follow naming conventions.

This keeps humans in control of content while delegating consistency to AI. Engineers still decide what to build and how to build it. AI ensures the result looks like everything else the team produces.

This shift also makes reviews faster. When everything follows the same structure, reviewers can focus on substance instead of style. They know where to look for specific information. They can evaluate content on its merits instead of debating formatting.

Final Thought

AI does not lower the bar by default.

It lowers the cost of keeping the bar high.

Related reading: