Keep AI coding changes minimal with ponytail the next time an agent answers a null-check ticket with forty changed files. Your reviewer opens the pull request, sees a new folder, an interface with one implementation, and a config object for a value that will never change. The bug fix is in there somewhere. Nobody finds it before lunch.

Ponytail is a skill file that encodes deliberate laziness. Lazy means efficient. I run it on consulting builds where clients measure merge speed and blast radius, because a five-file fix that solves the ticket beats a forty-file cleanup that invents a plugin system. Martin Fowler's note on YAGNI still names the bill: you pay for design you never use, then you pay again to drag it through every later change.

Why agents overbuild

Models train on public repos full of frameworks, tutorials, and aspirational architecture. Ask for a date picker and the prior reaches for a component library. Ask for caching and the prior reaches for a typed cache class with TTL knobs. Neither proves your product needs those pieces this quarter.

Agents also optimize for looking complete. A long diff signals effort, so a one-line fix feels too small and the model pads it with helpers and future-proof options. Reviewers pay in attention. CI pays in flake surface. You pay later when the unused factory blocks a real requirement.

Anthropic's guidance on building effective agents pushes the same bias at the system level: start with simple composable patterns, add complexity when measurement demands it. Ponytail applies that at the pull request level.

The ladder

Stop at the first rung that holds. Run it after you understand the problem, never instead of reading the code.

1. Does this need to exist at all? Speculative need means skip, in one line, out loud. Agents love building dashboards for metrics nobody opens. 2. Does this codebase already solve it? A helper three files over beats a new util package. Re-implementing what already exists is the most common slop I catch in review. 3. Does the standard library cover it? lru_cache, URLSearchParams, Intl.DateTimeFormat, path.basename. Boring tools that already shipped. 4. Does the platform cover it? <input type="date"> before a picker library. CSS before a JS animation runtime. A unique constraint before app-layer dedupe. 5. Does an installed dependency cover it? Use what the lockfile already carries. Adding a package is a product decision, not an agent reflex. 6. Can it be one line? Ship the one line when it handles the edge cases that matter. Two stdlib options of equal size go to the one that survives edges. 7. Only then, the minimum code that works. Few files, plain names, no abstraction until a second call site appears.

Root cause beats symptom patches

A bug report names a symptom. Ponytail still demands the root-cause read. Grep every caller of the function you plan to touch. One guard in the shared function is smaller than a guard in six callers, and patching only the path the ticket named leaves every sibling broken.

Teams get this wrong when they read "small diff" as "touch only the file in the ticket." Small in the wrong place is a second bug. Claude Code best practices put exploration before heavy edits for the same reason. Read fully, then climb.

What ponytail refuses to cut

  • Input validation at trust boundaries
  • Error handling that prevents data loss
  • Security measures you already require
  • Accessibility basics on UI work
  • Anything you explicitly asked for

When you want the full design, say so and get the full design. Ponytail sets a default, and it never overrides product intent.

Non-trivial logic still leaves one runnable check behind: a small assert demo or one focused test that fails when the branch breaks. No fixture factories, no per-function suite unless you asked. Tests follow YAGNI too.

Review signals

Run this on every agent pull request:

1. File count matches the blast radius of the bug or feature. 2. No new interface with a single implementation. 3. No config object for a constant. 4. No drive-by renames or formatting outside the change. 5. No new dependency without an explicit ask. 6. Root cause sits in the shared path. 7. The description names what was skipped and the trigger to add it later.

Two failures send it back with the ladder pasted into the review. Agents respond to concrete rungs. "Make it simpler" invites another creative rewrite.

Two tickets, two outcomes

Cache the API responses on a settings page. Without ponytail you get a CacheService class, TTL config, an in-memory map, eviction tests, an adapter interface, and a README section. With ponytail you wrap the fetch in the language's LRU helper or reuse the cache headers the API already sends, then note that a custom class waits for a profiler.

Fix the null crash in billing when plan is missing. Without ponytail you get optional chaining on the screen that crashed. With ponytail you find every reader of plan, put the default in the shared loader, add one assert for the missing-plan path, and leave the screens alone.

Both tickets look small. They compound in a codebase agents touch daily.

Install it on the team

Put ponytail where your agent loads skills and name it after the job, keep-ai-coding-changes-minimal rather than ponytail-vibes. Paste the ladder as numbered rules. Add two examples from your own repo: one good one-line fix, one rejected overbuild. Set full as the default for product work, lite when juniors need room, ultra only in spikes. Add one checkbox to the pull request template: "Ponytail ladder applied."

Coach against the four repeat offenders. Scaffolded folders get deleted in review. A new state library beside your existing bus gets answered with a path to the existing store. Drive-by formatting belongs to the formatter on save. Long justification essays get one line in the skill: code first, three lines maximum.

Ship the habit this week

Add the ladder to one skill file, apply it to the next three agent pull requests, and count files touched before and after. Tip 3 on agent talk less with caveman keeps the prompt short. Tip 5 on compressing agent context before you code keeps the input short. Ponytail keeps the diff short.

If you want it wired into your workflow with job-named skills and pull request templates, book a call. More notes live in the tips index.

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FAQ

What is the ponytail skill for AI coding agents?

A coding discipline skill that forces the laziest solution that still works: YAGNI first, reuse existing code, prefer stdlib and native features, then ship the shortest correct diff.

Does minimal mean skip tests and error handling?

No. Ponytail never cuts validation at trust boundaries, data-loss protection, security basics, or anything you requested. Fewer files and fewer abstractions, same care.

How do I know an agent ignored ponytail?

Look for new folders, unused interfaces, config for constants, and refactors outside the ticket. A healthy pull request touches the fewest files that fix the root cause.

When should I turn ponytail off?

When you asked for the full design, when you are doing greenfield architecture on purpose, or when a measured bottleneck proves the simple path failed.