Expect content that balances technical insight with measured reflection, seasoned with just the right amount of humour. These ideas and observations refused to stay quietly in mind, now shared to spark meaningful discussions and fresh perspectives.
AI copilot scrutiny and microservices cost reckonings opened 2026—popular engineering choices faced overdue questions about whether fashionable solutions create more problems than they solve.
Companies do not keep repeating software failures because nobody noticed. They repeat them because the lesson had nowhere durable to live, no owner, and no budget attached. The post-mortem sits in the wiki. The trap stays armed.
Nearly every engineering organisation conducts post-mortems after major incidents, yet roughly half of all production incidents are repeats of problems already documented and supposedly resolved. The gap between writing the document and changing the system is where organisational learning goes to die.
Attackers no longer need to breach your software directly. They compromise a package buried in your dependency tree and let routine installs spread the damage. Recent supply chain attacks show how fragile modern trust chains have become.
The software industry has spent 25 years learning a simple truth: broken products ship faster, cost less, and often face limited legal consequence. Now the same industry deploys AI systems alongside formal arguments that hallucination cannot be fully eliminated in general-purpose use. AI didn't start this trend. It scaled it.
Most applications log prolifically and explain nothing. Gigabytes of output fill storage, drive six-figure observability bills, and when production breaks at three in the morning, the only entries that matter are the ones nobody thought to write.
The most engaged employees are burning out fastest whilst their disengaged colleagues coast through untouched. When the people who care most are consistently the ones who leave first, something structurally broken is being ignored.
The industry adopted microservices as the default architecture for modern systems, but the tax is coming due. When the company that helped popularise distributed services publishes a 90% cost reduction by returning to a monolith, the assumption deserves reexamination.
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.