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Learning · Build · 2025

Pacman, Rebuilt

The scoped learning project where I figured out where AI-assisted development genuinely shines — and where a builder's judgment is still irreplaceable.

Learning projectGame mechanicsAI-assisted dev
1 dayTime to build
HighLearning curve
April 2025Built on

The story

When AI-assisted development got genuinely good, I didn't want to read about it — I wanted to feel where it shines and where it fails. So I picked a scoped, well-understood problem with hidden depth: Pacman.

It looks simple. It isn't. The original's ghosts each run different pursuit logic — one chases you, one ambushes ahead of you, one is unpredictable — and that interplay is what makes the game feel alive. Recreating it meant getting collision handling, tile-grid movement, and ghost state machines genuinely right.

What it taught me

  • Directing AI like a senior engineer directs a team — clear specs in, working code out, review everything.
  • Where AI accelerates (boilerplate, well-documented patterns) and where judgment is irreplaceable (game feel, edge cases, architecture).
  • Confidence. Shipping this is what convinced me the multiplayer platform was achievable — one milestone at a time.

Outcome

A fully playable game — and a new build capability I've used on every project since. (The arrow keys still work.)

Build notes

Tech stack

  • JavaScript
  • HTML Canvas
  • CSS

AI models used

  • Claude Sonnet
  • Claude Opus 4.8
  • GPT 5.4–5.6