Coding standards, process conventions, and the governance practices that transform individual preferences into collective consistency.
Welcome to the diplomacy of development, where style guides prevent wars, linters keep the peace, and process discipline separates sustainable teams from those perpetually firefighting. These standards stories capture the evolution from wild west coding to civilised collaboration.
architecture (5)
System design principles and architectural patterns that shape resilient, maintainable software solutions.automation (6)
Systematic approaches to eliminating repetitive tasks through scripting, version control workflows, and intelligent tooling.configuration (5)
Configuration management strategies that bring order to chaos across development environments and production systems.devops (6)
Containers, reproducible environments, and operational practices bridging the gap between development agility and production stability.industry (2)
Workforce trends, market shifts, and systemic forces reshaping who builds software and how the profession evolves.infrastructure (6)
Networks, cloud platforms, monitoring, and the foundational systems that determine whether digital services scale or collapse.patterns (6)
Design patterns and anti-patterns that separate maintainable codebases from technical debt graveyards.productivity (7)
Workflow optimisations, terminal mastery, and tool choices that multiply developer effectiveness without sacrificing code quality.quality (12)
Software quality principles—from debugging and testing to the practices that distinguish robust systems from those held together by hope.security (5)
Security engineering, credential management, and the defensive practices that protect systems from threats both obvious and obscure.ssh (4)
Secure shell mastery and remote access patterns that turn distributed systems into a unified workspace.standards (7)
Coding standards, process conventions, and the governance practices that transform individual preferences into collective consistency.
The copilot paradox: when coding faster makes your codebase worse
AI coding assistants promise dramatic productivity gains, but independent research tells a contradictory story. When controlled studies, delivery metrics, and 211 million lines of analysed code all point in the same uncomfortable direction, the industry narrative deserves scrutiny.
Null: the billion-dollar mistake that keeps compounding
In 1965, a computer scientist added a feature to a programming language because it was easy to implement. Sixty years and countless production crashes later, every modern language designed for reliability has arrived at the same conclusion: that decision was catastrophically wrong.
The symptom-fix trap: Why patching consequences breeds chaos
In the relentless pressure to ship features and fix bugs quickly, development teams fall into a destructive pattern of treating symptoms rather than root causes. This reactive approach creates cascading technical debt, multiplies maintenance costs, and transforms codebases into brittle systems that break under the weight of accumulated shortcuts.
The velocity trap: when speed metrics destroy long-term performance
Velocity metrics were meant to help teams predict and improve, but they have become weapons of productivity theatre that incentivise gaming the system while destroying actual productivity. Understanding how story points, velocity tracking, and sprint metrics create perverse incentives is essential for building truly effective development teams.
Sprint overcommitment: the quality tax nobody measures
Three features in parallel, each "nearly done". The authentication refactor sits at 85% complete. The payment integration passed initial testing. The dashboard redesign awaits final review. None will ship this sprint—all will introduce bugs next sprint. Research shows teams planning above 70% capacity experience 60% more defects whilst delivering 40% less actual value.
Technical debt triage: making strategic compromises
Simple CSV export: one day estimated, three weeks actual. User data spread across seven tables with inconsistent types—strings, epochs, ISO 8601 timestamps. Technical debt's real cost isn't messy code; it's velocity degradation. Features take weeks instead of days. Developers spend 17 hours weekly on maintenance from accumulated debt.
The hidden cost of free tooling: when open source becomes technical debt
Adding file compression should have taken a day. Three packages needed different versions of the same streaming library. Three days of dependency archaeology, GitHub issue spelunking, and version juggling later, we manually patched node_modules with a post-install script. Open source is free to download but expensive to maintain.