PRD Driven Context Engineering

PRD-Led Context Engineering

Memory as Infrastructure — an operating system for building products with AI agents

*Your AI partner is brilliant in one session and amnesiac by the next. This repository is the fix:
a fork-ready methodology that turns documentation into a knowledge graph humans and AI navigate
together — so the 50th session is smarter than the 1st.*

Quick Start · The Idea ·
The Lifecycle · The Skills ·
Live Demo Views

⭐ If this changes how you build with AI, star the repo — stars put this method in front of the next team drowning in context drift.

The Problem: AI forgets. Teams drift.

Every era of software solved memory its own way — and broke it its own way:

- Waterfall had Static Memory. Write everything down upfront: certainty, at the cost of change.
- Agile moved fast and created Fragmented Memory. Knowledge scattered across tickets, wikis, and chats; shared understanding evaporated.
- AI-assisted building adds a third failure: Amnesiac Memory. The model that architected your system yesterday has never heard of it today.

The common mistake is treating these as tooling problems. They are *memory* problems.

PRD-Led Context Engineering builds Shared Memory: it treats AI as a team member, not a tool, and keeps documentation synchronized with code so humans and AI navigate the same truth.

The Idea: Memory as Infrastructure

This methodology comes from two converging experiences.

Leading human teams — alignment always followed the same pattern: rally around a single Source-of-Truth artifact and the team moves as one. Without it, even great talent drifts.

Partnering with AI — sometimes the model performs at a senior level, sometimes it hallucinates. The variable was never the model's intelligence. It was the Context Density provided: rich,…