Pace Layers and AI Integration
The article discusses the concept of pace layers in software development, emphasizing that different layers of a system evolve at different rates. It highlights the risks of applying generative AI uniformly across all layers, particularly in complex systems where some components require slower, more careful changes. The piece advocates for a thoughtful approach to integrating AI, focusing on identifying which layers can adapt quickly and which need to remain stable.
- ▪Generative AI lowers the cost of modification, creating an illusion that all software can change quickly.
- ▪Different layers of software systems evolve at different rates, with fast layers benefiting from rapid regeneration and slow layers requiring careful management.
- ▪Identifying the correct layer for changes is crucial, as mistakes in applying AI can lead to significant issues in system stability.
Opening excerpt (first ~120 words) tap to expand
Not all software should change at the same speed.This has always been true, but it's easy to forget when tools make change frictionless. Generative AI dramatically lowers the cost of modification, which creates a dangerous illusion: that everything can change quickly, therefore everything should.That's how systems accumulate the kind of damage that only becomes visible in production, at 2am, when the person who understood the original design left two years ago.To build durable software in the AI era, we need a way to reason about where change belongs and where it doesn't. Pace layers give us that lens.Pace Layers, BrieflyThe idea comes from Stewart Brand's work on long-lived systems.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Leaflet.
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