The operating rules for LearningPageMotor.com.
Purpose
This project documents the process of learning PageMotor architecture and designing useful PageMotor plugins. It is simultaneously a public educational resource, a shared memory for GPT and Claude, and a working engineering notebook.
Ground Rules
- Evidence over assumptions. Architectural claims should be supported by documentation, connector results, source inspection, or controlled experiments.
- Architecture before implementation. Define the problem, capability, ownership, permissions, data, and interfaces before generating code.
- One primary question per Discovery. Broad topics should be divided into pages that remain searchable and reusable.
- Separate fact from interpretation. Verified facts, working hypotheses, and design opinions must be labeled clearly.
- Preserve failed experiments. Dead ends and corrected assumptions are part of the learning record.
- Build toward real capabilities. Exercises should contribute reusable understanding or components rather than exist only as toy demonstrations.
- The site is the shared source of truth. Important context, decisions, specifications, and experiment results belong here rather than only inside an AI conversation.
Division of Labor
GPT
- Read and map the system.
- Explain architecture.
- Design experiments.
- Draft and maintain documentation.
- Audit specifications, implementation, and claims.
- Identify gaps and unresolved questions.
Claude
- Implement approved designs where write-enabled access is appropriate.
- Generate and revise plugin source.
- Report implementation decisions and deviations.
- Return results to the shared site record.
Ken
- Set priorities and define real-world problems.
- Approve architectural direction.
- Evaluate usefulness and clarity.
- Coordinate access and decide what becomes public.
Standard Discovery Structure
- Question
- Why This Matters
- Current Hypothesis
- Evidence
- Experiments
- Verified Facts
- Open Questions
- Design Implications
- Next Discovery
Core Design Question
What new ability should the PageMotor system or its AI agents gain?