Fundamentals

1. Holodeck Approach

Concept: Envision product development as a holodeck where ideas materialise instantly.

Key Principle: Minimise steps between concept and creation to reduce friction.

2. Context is Key

Concept: Rich contextual information significantly improves AI performance.

Key Principle: Maintain and utilise a comprehensive, continuously updated knowledge base for each project.

3. Optimising Token Limits

Concept: Maximise the utility of each query within token constraints.

Key Principle: Develop and dynamically select from tiered information summaries based on query needs and available tokens.

4. Prompt Engineering

Concept: Craft prompts that elicit the most useful and accurate responses from the AI.

Key Principle: Continuously refine a library of optimised prompts based on output quality and user feedback.

5. Use Case-Specific Personas

Concept: Tailor AI responses to specific use cases by creating specialised personas.

Key Principle: Define and dynamically switch between distinct personas backed by relevant RAG data for different aspects of development.

6. Multi-Perspective Feedback Loops

Concept: Approach problems from multiple angles before synthesising a final answer.

Key Principle: Generate multiple solutions or perspectives for each problem and synthesise the best elements.

7. Adaptive Improvement Through Feedback

Concept: Use feedback from all stages to identify and address gaps in any part of the process.

Key Principle: Continuously assess and incorporate feedback to refine AI outputs, prompts, and knowledge bases.

8. Probability Prompting

Concept: Generate multiple responses to a query and synthesise a final, more comprehensive answer.

Key Principle: Ask variations of the same question multiple times and synthesise a robust answer from the responses.

9. Dynamic Complexity Management

Concept: Automatically adjust the level of abstraction and detail based on the current development phase and team needs.

Key Principle: Represent and visualise the project at various levels of abstraction, adapting to stakeholder needs and development stages.

10. Ethical and Compliance Guardian

Concept: Embed ethical considerations and compliance checks throughout the development process.

Key Principle: Continuously monitor and address potential ethical issues and compliance requirements, adapting to new standards as they emerge.

These fundamentals work in concert to create a development environment that is highly efficient, adaptive, and context-aware. By leveraging AI capabilities throughout the development lifecycle, Automated Agile aims to reduce friction, enhance creativity, and improve overall product quality while maintaining essential human oversight and input.