- AI DSL Development
- Building the Languages That Shape AI-Driven Software
- Chapter 1
- Why DSLs Matter in the Age of AI
- The Reliability Crisis in AI-Assisted Development
- Why Natural Language Fails as a Programming Interface
- The DSL Solution: Structured Language for Reliable AI
- Historical Precedents: DSLs Are Nothing New
- Why LLMs Amplify the Need for DSLs
- The Transition: Prompts → Specs → DSLs
- Real-World Impact: A Case Study
- Key Takeaways
- What’s Next
- Chapter 1
- Why DSLs Matter in the Age of AI
- The Reliability Crisis in AI-Assisted Development
- Why Natural Language Fails as a Programming Interface
- The DSL Solution: Structured Language for Reliable AI
- Historical Precedents: DSLs Are Nothing New
- Why LLMs Amplify the Need for DSLs
- The Transition: Prompts → Specs → DSLs
- Real-World Impact: A Case Study
- Key Takeaways
- What’s Next
- Chapter 2
- Foundations of Domain Language Engineering
- What Is a Domain-Specific Language?
- Core Principles of Domain Language Engineering
- Types of DSLs
- The Linguistic Stack: Building Blocks of DSLs
- Domain Modeling: From Reality to Language
- Principles from Formal Language Theory
- The Difference Between Prompts, Specs, and DSLs
- Design Trade-offs
- Mental Models for DSL Design
- Key Takeaways
- What’s Next
- Chapter 3
- Designing Semi-Formal DSLs for AI Interpretation
- What Makes a DSL “Semi-Formal”?
- Core Design Principles for AI-Oriented DSLs
- Grammar Design: Making It Parseable
- Schema Design: Enforcing Structure
- Type Systems for DSLs
- Handling Ambiguity and Defaults
- Versioning Strategies
- AI-Specific Considerations
- Key Takeaways
- What’s Next
- Chapter 4
- AI-Centered Specifications: The New Engineering Contract
- Specifications in the Age of AI
- The Anatomy of an AI-Centered Specification
- Layer 1: Metadata — Context and Traceability
- Layer 2: Intent — The “Why” and “What”
- Layer 3: Structure — The “How” at High Level
- Layer 4: Constraints — The Guardrails
- Layer 5: Validation — Proof of Correctness
- Complete Example: Payment Processing Spec
- Best Practices for AI-Centered Specs
- Key Takeaways
- What’s Next
- Chapter 5
- Co-Designing Abstractions With LLMs
- The Collaborative Design Loop
- Technique 1: AI as a DSL Critic
- Technique 2: AI as a Domain Vocabulary Miner
- Technique 3: Negotiating Abstractions
- Technique 4: Validating Expressiveness
- Technique 5: Generating Test Cases
- Technique 6: Discovering Missing Abstractions
- Technique 7: Iterative Refinement Loop
- Key Takeaways
- What’s Next
- Chapter 6
- Creating Micro-DSLs for Real Development Workflows
- What Are Micro-DSLs?
- 1. Backend Development: API Specification DSL
- 2. Frontend Development: Component Spec DSL
- 3. DevOps: Deployment Pipeline DSL
- 4. Testing: Test Scenario DSL
- 5. Architecture: Service Boundary DSL
- 6. Data Migration DSL
- Key Takeaways
- What’s Next
- Chapter 7
- Validation, Determinism & Reliability in AI Execution
- The Reliability Challenge
- The Validation Stack
- Layer 1: Schema Validation
- Layer 2: Syntax Validation
- Layer 3: Semantic Validation
- Layer 4: Output Validation
- Layer 5: Runtime Validation
- Achieving Determinism
- Building Guardrails
- Monitoring AI Reliability
- Key Takeaways
- What’s Next
- Chapter 8
- Best Practices, Anti-Patterns & Failure Modes
- Introduction: Learning from Failures
- Best Practices
- Anti-Patterns
- Common Failure Modes
- Debugging DSL Issues
- Checklist: DSL Health Check
- Key Takeaways
- What’s Next
- Conclusion
- Becoming a Domain Language Engineer
- The Journey So Far
- The Core Insights
- The Paradigm Shift
- Why This Matters for Your Career
- Your Next Steps
- Resources to Master Next
- The Future: What’s Coming
- A Call to Action
- Final Thoughts
- Thank You
- Stay Connected
- About the Author
- Geison Flores
- AI DSL Development
AI DSL Development
The Shift From Prompting to Domain Language Engineering
Prompt engineering is dying. The future belongs to domain language engineers—developers who design structured DSLs that make AI reliable, deterministic, and scalable. This practical guide teaches you how to build the languages that shape AI-driven software. With templates, and real-world examples, you'll transform from AI user to AI architect. Stop negotiating with ChatGPT. Start engineering systems that work.
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About
About the Book
This book is not about prompt engineering. It's about domain language engineering — the practice of designing structured vocabularies, semi-formal specifications, and domain-specific languages (DSLs) that enable reliable, maintainable AI-assisted software development.
You will learn:
- Why DSLs Matter — How structured languages provide a reliability layer for AI systems
- Foundations — Core principles of domain language design, linguistic patterns, and semantic precision
- Design Techniques — How to create semi-formal DSLs that balance expressiveness with constraint
- AI-Centered Specifications — How to write specs that LLMs can reliably interpret and execute
- Co-Design Patterns — How to use AI to improve your DSL through iterative refinement
- Practical Micro-DSLs — Real-world examples from backend, frontend, DevOps, testing, and architecture
- Validation & Determinism — How to enforce correctness, detect invalid outputs, and build guardrails
- Best Practices — Common mistakes, anti-patterns, and failure modes to avoid
Author
About the Author
Geison Goes
Geison Flores começou a escrever software quando tinha catorze anos em um 486, seu primeiro software foi um sistema de gerenciamento de vídeo-locadoras escrito em Clipper.
Mas começou a escrever código para viver por volta do ano de 2004 em startups empresas de consultoria e continuou sua carreira em empresas como Hewlett Packard e ThoughtWorks.
Como consultor na ThoughtWorks ele esteve envolvido em projetos de empresas listadas na Fortune 500 e em grandes clientes locais como a Globo.com. Já na Hewlett Packard como engenheiro de software teve a oportunidade de ajudar a criar e implantar grandes projetos de software. E atualmente na Globo ajuda a elevar os serviços de streamming aos maiores níveis de escalabilidade.
Em seu tempo livre também é jogador de poker e maratonista de séries, saiba mais em about.me/geisonfgf.
Contents
Table of Contents
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