A programmer defends YAML against common criticisms, arguing that many complained-about issues stem from improper usage rather than the specification itself. The author shares experiences with YAML in projects like a Discord bot and Space Station 14, noting that explicit deserialization logic prevents problems like implicit type conversion.
Mark Seemann discusses learning programming with LLMs through a reader's letter, exploring how AI tools can create a gap between building functional systems and deeply understanding them. The reader built a sophisticated TypeScript application using AI assistance but struggled with maintenance and ownership, prompting questions about the right relationship with LLMs in professional development. Seemann shares his mixed perspective on AI's impact, expressing concerns about potential mass unemployment among knowledge workers while acknowledging both the technology's capabilities and historical precedent for technological job displacement.
The author argues that AI agents will automate most software development tasks, leaving human software engineers to focus on product strategy, requirements definition, and decisions agents cannot make. With software costs collapsing but demand remaining effectively infinite, the job title may change but software development as a profession will persist, transformed into what the author calls 'product engineering.'
CodeProject, a community platform for programmers offering articles and code across multiple languages, entered read-only mode in October 2024 due to financial losses. The site was acquired by D2 Emerge LLC in November 2024 but went offline in March 2026, with content preserved by the Internet Archive.
Sylvain Huet presented at Hackaday Europe 2026 on simplifying bare metal programming by reducing dependencies and complexity, advocating for systems simple enough for a single developer to fully understand. He showcased Minimacy, an open-source programming language designed to enable transparent, dependency-free development while maintaining safety and performance.
An article explores how AI-assisted programming may produce alienation similar to Marx's theory, particularly regarding loss of ownership and control over code created primarily by large language models rather than the programmer themselves. The author argues that while traditional Marxist conditions don't apply to programmers, AI-based coding creates new forms of alienation through dependency on paid services and loss of code comprehension.