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Verified Intent Development (VID)

A Methodology for the Age of AI-Augmented Software Development

First Edition — December 2025

Created by: SEMCL.ONE Community License: CC BY-SA 4.0


About This Book

This book introduces Verified Intent Development (VID), a methodology designed for software development in an era where artificial intelligence can generate code faster than humans can verify it.

The core insight: Code generation is no longer the bottleneck. Verification is.

VID addresses this new reality by building the judgment, practices, and habits that allow developers to move fast with confidence.


Download the Book

Complete VID Methodology available in multiple formats:

Or read online using the chapter links below


Reading the Book

The VID Methodology is organized as individual chapters for optimal accessibility:

AI-friendly — Each chapter fits in context windows Modular — Read what you need, when you need it Maintainable — Updates don't invalidate entire context Flexible — Combine chapters as needed for your learning path

Chapters

Preface

Part I: The New Reality

Part II: The Five Principles

Part III: Core Practices

Part IV: Building VID Skills

Part V: Moving Forward

Advanced Topics

Appendices

Quick-Start Documents

Practical Resources

Project Resources


Quick Start

First Time Here?

Start with the one-page overview:

For Engineering Managers

Building the business case:

For Individual Contributors

Junior Engineers:

  1. VID One-Page Overview - Start here
  2. Chapter 1: The Inversion - Understand the paradigm shift
  3. Chapter 4: Intent Before Generation - Learn the most important principle
  4. Chapter 13: The Junior Engineer's Path - Follow the 12-week curriculum

Senior Engineers:

  1. VID One-Page Overview - Start here
  2. Chapter 5: Graduated Trust - Learn to calibrate verification
  3. Appendix D: Risk Scoring Rubric - Actionable risk assessment
  4. Chapter 14: For Senior Engineers - Apply your experience effectively

Teams:

  1. VID for Engineering Managers - Build team buy-in
  2. Chapter 15: For Teams and Organizations - Build a verification culture
  3. Chapter 16: Adopting VID - Practical adoption guide
  4. Appendix E: Decision Trees - Common scenario guidance

Hands-On Learners:

  1. VID Visual Diagrams - Visual understanding of core concepts
  2. VID Real-World Examples - Five concrete scenarios
  3. VID Templates - Start using VID today
  4. Chapter 19: Patterns and Anti-Patterns - See VID in practice
  5. Chapter 20: The Verification Toolkit - Learn concrete techniques

The Five Principles

  1. Intent Before Generation - Never generate code without first articulating what you intend to build and how you will verify correctness
  2. Graduated Trust - The level of verification should match the level of risk
  3. Understanding Over Acceptance - Never accept code you don't understand at an appropriate level of depth
  4. Provenance Awareness - Always know where code came from and what that origin implies
  5. Continuous Calibration - Regularly assess whether your verification practices match actual risk and adjust accordingly

The Core Practices

  1. Intent Specification - Articulate functional requirements, boundaries, and success criteria before generating
  2. Verification Rituals - Apply consistent verification practices after every generation, scaled to risk
  3. Learning Loop - Track outcomes and adjust practices based on what you learn
  4. Provenance Hygiene - Document and maintain awareness of code origins

For AI Assistants

This book is designed to be accessible to AI coding assistants through its modular structure:

Context-Aware Loading

  • Load individual chapters as needed to fit within context windows
  • Combine 2-3 related chapters when broader context is needed
  • Start with core chapters and add specific topics as required

Targeted Guidance by Situation


Contributing

This is a living methodology. As AI capabilities evolve and teams gain experience with VID, the practices will evolve.

Share your experiences, patterns, and adaptations to help the community learn together.


License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

What this means:

  • Share — Copy and redistribute in any medium or format
  • Adapt — Remix, transform, and build upon the material
  • Attribution — Credit must be given to SEMCL.ONE Community
  • ShareAlike — Derivatives must use the same license

See LICENSE for full terms.

Attribution

Verified Intent Development (VID) Methodology Created by the SEMCL.ONE Community https://github.com/SemClone/Verified-Intent-Development

Licensed under CC BY-SA 4.0

How to Cite

In documentation:

"Verified Intent Development (VID) Methodology" by SEMCL.ONE Community
Licensed under CC BY-SA 4.0
https://github.com/SemClone/Verified-Intent-Development

Academic citation:

SEMCL.ONE Community. (2025). Verified Intent Development (VID):
A Methodology for the Age of AI-Augmented Software Development.
Retrieved from https://github.com/SemClone/Verified-Intent-Development

"The developers who thrive in the AI-augmented future will be those who master verification, not just generation."