A software engineer describes why building software remains difficult despite AI tools, using a house renovation analogy to explain to non-technical leaders why quick fixes and skipping infrastructure work create cascading problems. The author recounts a hackathon where rapid initial progress gave way to systemic failures when foundational work was neglected.
The Broken Window Theory in software development warns that messy code patterns encourage more disorder, yet teams often apply YAGNI and KISS principles so strictly that simple solutions accumulate into technical debt. As codebases grow, developers tend to copy established patterns rather than introduce needed abstractions, creating a cycle where bad patterns perpetuate themselves.
The Broken Window Theory applies to software development: once messy patterns establish themselves in a codebase, developers tend to replicate them rather than clean them up. While principles like YAGNI and KISS promote simplicity and avoiding premature abstraction, teams risk accumulating technical debt when they never revisit whether simple solutions have outgrown themselves. Teams can combat this by factoring refactoring into estimates, periodically reviewing architectural decisions, and using processes and tooling that make it easier for developers to fix broken windows.
An article discussing two approaches to using AI in software development: accelerators who read and understand generated code to maintain responsibility, and vibecoders who delegate implementation details to AI while focusing on specification and evaluation. The piece argues that the long-term consequences of these divergent practices remain uncertain despite confident claims from either side.
OpenAI's announcement of Astra, an LLM model that automates PCB layout in KiCad, sparked concern among embedded engineers about job displacement. The article argues that while LLMs will likely automate routine design tasks like schematic and board layout work, the future of engineering lies in systems-level thinking, requirements development, and verification—skills where human experience remains irreplaceable.
Cognitive Debt describes the loss of human understanding of system components, distinct from technical debt. The article proposes a scoring method (1-3 scale for complexity and severity) to estimate the Cost of Cognitive Debt and determine appropriate levels of supervision for agentic workflows in software development.
An essay argues that software development's combination of speed, flexibility, low implementation friction, and unlimited possibilities creates psychological conditions that lead people to lose perspective and act irrationally. Unlike physical construction where costs are visible, software changes appear cheap but accumulate hidden expenses, encouraging endless feature additions and creating a culture where every decision feels urgent and strategic.
Bad code accumulates like kudzu, a invasive plant that overtakes ecosystems. The author argues that in an era of easy feature addition, developers must actively delete unused code to prevent complexity bloat, illustrating with an example of removing rarely-used hashtag bubbles from their blog.