MartinFowler.com is the long-running technical blog of Martin Fowler, author, software architect, and Chief Scientist at ThoughtWorks. The site serves as a cornerstone for modern software engineering, featuring influential essays and guides on software architecture, refactoring, agile methodologies, design patterns, and continuous delivery. Martin’s writing combines deep technical expertise with a clear, educational tone, making complex ideas about domain-driven design, microservices, and testing strategies accessible to engineers of all levels. Classic works like Refactoring, Patterns of Enterprise Application Architecture, and Continuous Integration originated from concepts first explored on this blog. With over two decades of archives, MartinFowler.com remains one of the most authoritative and enduring resources in professional software development.
88 articles from this blog
Martin Fowler discusses LLM risks, vibe-coding concerns, and the need for verification over code generation in software development.
Modernizing a legacy Java 1.5 codebase using AI and Docker, with a focus on evidence-based refactoring and testing.
Explores how Domain-Specific Languages (DSLs) guide LLMs to generate reliable, intent-aligned code, using Tickloom as an example.
Martin Fowler shares notes from a Thoughtworks retreat on AI harness engineering and self-hosted models.
A developer shares experiences running small local AI models for agentic coding, evaluating hardware, speed, tool calling, and code quality.
Explores the viability of running local AI models for coding, covering hardware, performance, and quality factors.
Martin Fowler shares fragments from the second Future of Software Development Retreat, focusing on agentic development and its impact on software engineering.
Martin Fowler shares thoughts on LLMs making programming more fun, DDD Europe highlights, and conversation registers with AI.
Case study on building production-ready agentic AI systems for pharmaceutical drug development using RAG and Text-to-SQL.
Analysis of flawed AI productivity metrics, historical automation parallels, and open vs closed AI model performance trends.
Martin Fowler discusses LLM-augmented programming, codebase restructuring with AI, and NHS closing open source repos.
Explores using test suites as regression sensors to maintain codebase quality when working with AI coding agents.
Article discusses the security risks of 'vibe coding' with AI and offers strategies to secure AI-generated applications.
Explores 'vibe coding'—building software by prompting LLMs without reviewing generated code, its benefits, risks, and distinction from agentic programming.
Explore three static code analysis sensors for maintainability in AI-assisted coding, covering linting, dependency rules, and coupling data.
Explores using maintainability sensors to help coding agents keep codebases clean and reduce technical debt.
Martin Fowler shares insights from a retreat on software development's future with agentic programming, LLM code porting, and legacy modernization.
Explores using an LLM to interview humans for context gathering, document creation, and review in complex tasks.
Explores the deeper purpose of code beyond machine instructions, emphasizing its role as a conceptual model and shared vocabulary in software development.
Martin Fowler's Fragments: May 5 covers AI-assisted programming tools, structured prompts, and developer feedback loops.
