Summary

Dan Shapiro surveys the emerging ecosystem of 'Dark Factories' — automated systems that turn specifications into shipping software using AI. He identifies the core pattern as the 'trycycle': a simple loop where AI writes code, checks its work, and iterates until it succeeds. He profiles three implementations of increasing complexity — Steve Yegge's Mad Max-themed Gastown, StrongDM's configurable Attractor pattern, and his own Go implementation called Kilroy — before introducing Trycycle, a minimal Claude Code skill that implements the pattern in plain English. His thesis is that AI crossed a threshold from 'slightly-lossy' to 'slightly-gainy' in iterative self-improvement, making these simple retry loops surprisingly powerful.

Key Insight

The fundamental pattern powering AI software factories is a simple retry loop — plan, implement, check, repeat — that works because AI models have crossed the threshold where iterative self-correction produces net improvements.

Spicy Quotes (click to share)

• 4

  AI gets better when you do more of it.

• 7

  It seems trivial, but it's an unstoppable bulldozer that can bury any problem with time and tokens.

• 7

  It used to be that when a model was fed its own output, it would break fix 9 things and break 10 – like a busy and productive company that was losing just a bit of money on every transaction.

• 7

  But sometime last year, the models crossed an invisible threshold of mediocrity and went from slightly-lossy to slightly-gainy.

• 6

  Every software factory has a trycycle at its heart. Some of them are just surrounded by deacons and digraphs.

• 3

  Then a thought struck. What if this was just a skill?

• 3

  The best part, though, is that because it's just a skill, it's instantly part of your dev flow. There's no configuration or learning curve.

Tone

enthusiastic, practical, irreverent