I shipped a beta, almost production-grade PWA fast, less than a day
Speed with AI isn’t the hard part. Staying coherent is. Here’s the SR-SI workflow that prevents drift and makes fast builds stay structurally clean.
AI Workflow Architecture further reading, page 7
AI workflow architecture matters because AI adoption fails when tools know the task but not the operating context around it.
AI-assisted development breaks around prompt 200, but it doesn't have to
The 200-prompt wall isn’t a model limitation — it’s a memory architecture problem. SR-SI adds an external memory layer to prevent context collapse.
SR-SI in practice: what a context document actually looks like — and what it replaced
A concrete look at how SR-SI works in practice: what the context document contains, how it’s structured, and how it replaces the hidden re-explanation overhead of AI-assisted development.
You don't fix a memory problem by adding more memory
Bigger context windows aren’t memory systems. The fix is structure: a shallow index that points to truth and lets AI re-orient without drowning in history.
Why AI outputs feel 60% relevant
When AI lacks your context, it returns the average answer with confident tone. The fix isn’t better prompting — it’s an orientation layer that makes your team’s knowledge findable before execution.