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Agent-Driven Development

How to Stay in Control While Delegating Development to AI Agents

Code is cheap. The real challenge now is managing AI agents.

This book is a translation into English of Управляемая разработка с AI-агентами which was originally written in Russian

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About

About

About the Book

In early 2025, with the rise of vibe coding, it seemed that AI agents would turn software development into a near-direct transformation of prompts into working programs. Reality turned out to be more complex. While code generation can be delegated, the complexity of development does not disappear—it shifts. The challenge moves to defining tasks, structuring context, managing constraints, and maintaining control over how a product evolves.

This book addresses that shift.

This book introduces Agent-Driven Software Management (ADSM), an original methodology developed by the author. It provides a practical approach to delegating development to AI agents while maintaining control, preserving product integrity, and ensuring that results remain suitable for further development.

ADSM is based on real-world experience. In the author's work, code generation for a new version of the Tequila Framework platform was fully delegated to agents, while the primary effort moved to documentation, context design, and execution control. This book distills that experience into a structured approach.

If you are already using AI agents in development and facing issues with instability, unpredictability, or loss of control, this book offers a way to turn that experience into a disciplined engineering process.

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This book is a translation into English of Управляемая разработка с AI-агентами which was originally written in Russian

Author

About the Author

Alex Gusev

Alex Gusev is a web engineer with over 25 years of experience. Throughout his career, he has worked in multiple roles, including software development, system administration, database administration, network engineering, systems integration, and DevOps.

His professional background includes building and maintaining production web applications in domains such as banking and finance, electronic payments, and e-commerce. He has worked with a wide range of programming languages and technology stacks, applying them to real-world systems and evolving requirements.

In recent years, his primary focus has been on JavaScript as a universal platform for application development. Through it, he develops and articulates his own engineering approach to building web systems and organizing the development process.

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Contents

Table of Contents

Introduction

Loss of Manageability

  1. Human Model of Agent
  2. Anthropomorphic Impression
  3. Human-Agent Difference
  4. Source of the Loss
  5. Symptoms
  6. Human-Agent Pair
  7. Work Shift

Axioms of ADSM

  1. Initial Problem
  2. Role of Axioms
  3. Three Axioms
  4. Practical Meaning
  5. Effect of Acceptance
  6. Cost of Ignoring
  7. Foundation of ADSM

Documentation Anchor

  1. Anchor Function
  2. Documentation Scope
  3. Roles of Key Artifacts
  4. Project Memory
  5. Document Areas
  6. Documentation as Code Template
  7. Agent Output to Documentation
  8. Developer Gains
  9. Project Costs
  10. Role of AGENTS.md

Agent Working Context

  1. Initial Prompt
  2. Two Contexts
  3. Context Entry
  4. Context Fit
  5. Context Layers
  6. AGENTS.md Role
  7. AGENTS.md Hierarchy
  8. Context Assembly
  9. Context Management

Agent Executor

  1. Agent Instrument
  2. Useful Scope
  3. Role Distribution
  4. Documentation Focus
  5. Agent Configuration
  6. Context Structure
  7. Delegation Setup
  8. Anthropomorphism Cost

Development Spiral

  1. Feedback Function
  2. Spiral Turn
  3. Feedback Cycle
  4. Documentation Clarification
  5. Expectation Formation
  6. Local Implementation
  7. Feedback and Autonomy
  8. Spiral Turn Cost

ADSM Applicability

  1. Cost of Future Changes
  2. Best Use Cases
  3. Effect Amplifiers
  4. Project Requirements
  5. Delegation Safety
  6. Effect Limits
  7. Excessive Use
  8. Developer Role Shift
  9. Practical Outcome

Practical Example

  1. Example Project
  2. Basic Generations
  3. Result Invariant
  4. Stable Error
  5. Context Change
  6. Repeated Generation
  7. Observable Change
  8. ADSM Connection
  9. Practical Outcome

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