Explore the challenges and productive uses of AI in software development, from managing low-quality generated code to leveraging LLMs for TDD and workflow optimization. Discover how developers are adapting to maintain code quality and boost productivity with AI tools.
Discover common developer experiences with AI coding assistants and learn key strategies to significantly improve the acceptance rate of code suggestions. Master the art of prompting and iterative refinement to get production-ready code faster.
Explore the challenges and solutions for transforming rapid AI prototypes into stable, production-ready applications. Learn about pricing, scope management, and targeting the right audience when building a service for "vibe-coded" projects.
An analysis of whether startups can be successfully built using AI 'vibe coding'. We explore the current limitations at scale, practical workflows for developers, and the rise of AI-generated 'slop apps' tied to course-selling.
An analysis of why many skilled software developers are hesitant to adopt AI coding assistants, citing concerns over code quality, long-term maintainability, and the nature of their work.
An analysis of how software engineers are truly feeling about AI tools, exploring the deep divide between reported productivity boosts and the frustrating reality of debugging AI-generated 'slop'.
The term 'vibe coding' has emerged to describe AI-assisted programming, but what does it really mean? Explore the debate between relying on AI intuition and using structured, specification-driven approaches for maximum productivity.
Developers are using AI to code faster, but promotions and profits remain elusive. This analysis explores why individual productivity gains aren't translating into career advancement and who is truly benefiting from the AI revolution.
When management mandates AI use, is quitting the only option for discerning professionals? This analysis explores the debate and offers a strategic approach to adapt, learn, and integrate AI on your own terms.
A Hacker News discussion explores why many programmers still prefer 'old-fashioned' coding without LLMs, citing joy, understanding, and learning concerns. Is AI-free coding obsolete or essential?