A developer explores using conversational AI to generate niche blog topic ideas, focusing on the process rather than AI-generated content.
Applies the 'less, but better' design philosophy to test automation, arguing for quality over speed and quantity of tests.
Argues that software engineers must prove their code works through manual and automated testing, not just rely on AI tools and code reviews.
Learn how to teach AI agents to understand and use custom enterprise libraries and domain-specific languages using Kiro and MCP.
A developer discusses the non-deterministic nature of LLMs like GitHub Copilot, arguing that while useful, they cannot take ownership of errors like a human teammate.
Analyzes the rise of AI-powered IDEs, questioning their necessity versus existing extensions and exploring their features and motivations.
A software engineer argues that technical blogging remains valuable, inspired by a book on writing effective posts and using AI as an editorial tool.
A guide to the top AI-powered coding tools and extensions available for C# developers using Visual Studio and Visual Studio Code.
The article argues for the value of 'Expert Generalists' in tech, individuals who span multiple specialties, and how to identify and cultivate them.
Explores the value of 'Expert Generalists'—professionals who span multiple specialties—and how to identify, hire, and train them.
Explores the key traits of 'Expert Generalists'—professionals who bridge multiple specialties—and their growing importance in tech.
A software engineer critiques the 'democratization' of AI in development, arguing it oversimplifies and risks creating fragile software without CS fundamentals.
Developer revives his old AI startup's brainstorming tool by building a GitHub Copilot Extension, using VS Code's speech features and LLMs.
Podcast episode discussing AI tools for developers, including chatbots for code generation, problem-solving, and navigating obscure technologies.
Interview with Sema CEO Matt Van Itallie on using generative AI for code analysis, developer productivity, and explaining software to non-technical executives.
An analysis of 900 popular open-source AI tools, categorizing them into infrastructure, model development, and application layers.
Opinion on Apple's new M3 Macs and AI developer tools, discussing performance plateaus and the challenge of convincing users to upgrade.
