My AI over-engineered everything. So I gave it a ponytail.

Description and use

Ponytail is a workflow that curbs over‑engineering by AI‑generated code, applying a decision ladder and documenting shortcuts for future upgrades.

Problem

AI coding agents tend to over-engineer solutions, adding unnecessary abstractions that increase maintenance burden.

Outcome

Ponytail reduced code complexity, avoided unnecessary abstractions, and introduced clear upgrade paths, improving maintainability and deployment speed.

Workflow

• Ask AI for a feature
• Apply ponytail ladder: 1) Does it need to exist? 2) Is it already in the codebase? 3) Does the standard library cover it? 4) Does a native platform feature cover it? 5) Is an existing dependency sufficient? 6) Can it be one line? 7) If none, write minimal code
• If a shortcut is taken, add a "ponytail:" comment noting the ceiling and upgrade path
• Harvest all ponytail comments for later review

Evidence

Ask an AI coding agent for a cache and you'll get a cache class. With a TTL. And an eviction policy. And an interface for the cache, in case you ever want a second cache. And a factory for the interface.

Source

Ponytail is a list of questions, asked in order. The agent stops at the first rung that works: ...

Source

The ponytail answer was a 20-line launcher that starts the API and the worker as two processes in one container, and exits the container if either dies so the host restarts it.

Source

Ponytail shipped the image running TypeScript directly, with a comment naming the ceiling and the exact upgrade path.

Source