Explores motivated reasoning in the context of AI concerns for software development, questioning personal biases.
Recap of Codemotion Madrid 2026, a tech conference with talks on AI, hiring practices, and developer mentorship.
Explains why AI cannot bear legal or social responsibility, emphasizing that only humans can be accountable in business and tech services.
A developer argues that coding is just a tool for problem-solving, and AI doesn't threaten a developer's true value or creativity.
An essay arguing that some bureaucracy, wisely chosen, is better than none, using historical and organizational perspectives.
GitHub Copilot Rubber Duck uses a second AI model to review code plans, catching subtle errors in multi-file tasks.
Speculative analysis on the future of agentic AI in software development, focusing on economic sustainability and geopolitical implications.
A programmer reflects on unpaid overtime, implicit pressure, and the moment they chose to enforce work boundaries.
A blogger revives their old blog, moving from Wordpress to a static site generator, and plans to write more about software development and technical subjects.
Mitchell Hashimoto argues software success today comes from building blocks that enable quantity over quality, using AI to glue components together.
Explores why the term 'consciousness' is problematic in AI discussions and argues for using 'awareness' instead.
Explores harness engineering concepts to build trust in AI-generated code from coding agents.
Announcing a new podcast episode on Agentic Feature Owners, featuring Jessitron, with reflections on code and life.
Explores which programming language is best for LLM-based code generation, questioning if machine code is viable.
AI reveals most knowledge work is scaffolding overhead, not core tasks, making it easy to automate.
A balanced perspective on using AI and LLMs as tools, not for everything, with practical examples from web browser documentation work.
A balanced perspective on using AI as a tool, discussing when it's useful and wasteful, with examples from web browser documentation work.
Argues spec-driven development with AI tools is waterfall methodology in disguise, advocating for leaner, discovery-based approaches.
Critique of AI's 'frictionless' promise, arguing human expertise and collaboration remain essential despite automation hype.
A daily tech reading list covering AI agents, software engineering practices, LLMs, and developer tools.
