The False Economy of Cheap Engineering
Cheap engineering can shrink payroll, but it often increases rework, instability, contractor spend, supplier dependence, and total delivery cost later.
Articles
Leadership
Leadership in engineering is the work of improving how teams think, decide, and deliver together. In practice that usually means setting standards, clarifying priorities, mentoring senior people, shaping technical direction, and turning difficult engineering truths into decisions the wider organisation can actually use.
The False Economy of Cheap Engineering. 
Everyone Wants the Best Engineers. Fewer Companies Want to Pay for Them. Everyone Wants the Best Engineers. Fewer Companies Want to Pay for Them
Underpaying senior engineers can look efficient on payroll, but often costs more through weaker hiring, slower delivery, contractor spend, and retention risk.
The Platform Dependency Trap: When Efficiency Becomes Lock‑In. The Platform Dependency Trap: When Efficiency Becomes Lock‑In
Platforms can speed delivery, but cutting internal capability too far can turn efficiency into lock‑in, weak negotiating power, and expensive migrations later.
The AI Governance Gap in Digital Transformation. The AI Governance Gap in Digital Transformation
AI programmes are often adopted tactically, without enough governance for supplier risk, data exposure, quality, workforce impact, or board accountability.
Why AI Makes Senior Engineers More Important, Not Less. Why AI Makes Senior Engineers More Important, Not Less
As AI reduces friction in implementation, the value of architecture, review, domain judgement, mentoring, and failure analysis rises rather than falls.
The Automation Tax No One Measures. The Automation Tax No One Measures
Automation can save labour, but it also creates monitoring, exception handling, vendor, governance, and security costs that many business cases ignore.
AI and the Collapse of Organisational Memory. AI and the Collapse of Organisational Memory
AI knowledge retrieval can weaken organisational memory when summaries hide context, dissent, incident history, product reasoning, and uncertainty.
The Hidden Cost of Replacing Juniors with AI. The Hidden Cost of Replacing Juniors with AI
AGI vs. AI vs. ASI: What Actually Changes? AGI vs. AI vs. ASI: What Actually Changes?
A practical explanation of AI, AGI and ASI for engineering and product teams, covering capability, autonomy, risk, governance, and real‑world impact.
The AI Middle Manager Problem. The AI Middle Manager Problem
AI can automate management reporting, but this article separates status theatre from judgement, coaching, accountability, and real prioritisation.
The AI Productivity Mirage: When More Output Does Not Mean More Value. The AI Productivity Mirage: When More Output Does Not Mean More Value
AI can inflate output without improving outcomes. This article explains why weak metrics, faster generation, and shallow review create a productivity mirage.
AI Will Be OK If We Stop Treating It Like Magic. AI Will Be OK If We Stop Treating It Like Magic
AI will be OK if teams treat it as real technology, not magic, with adoption shaped by judgement, skills, governance, shared access, and careful autonomy.
What is Artificial Superintelligence (ASI)? What is Artificial Superintelligence (ASI)?
Artificial superintelligence means AI that broadly outperforms humans, not just a better chatbot. What ASI means, why it matters, and what remains uncertain.
The AI Layoff Trap: When Local Efficiency Becomes Systemic Fragility. The AI Layoff Trap: When Local Efficiency Becomes Systemic Fragility
AI automation improves productivity, but unmanaged labour displacement risks weaker demand, brittle organisations, concentrated gains, and a race to the bottom.
How to Vet a Senior Next.js Developer for a Replatform or Recovery Project. How to Vet a Senior Next.js Developer for a Replatform or Recovery Project
How to vet a senior Next.js developer for replatforming, recovery, SEO, performance, CMS, Vercel, and production debugging work.
Responsible AI Needs an Owner. Responsible AI Needs an Owner
Responsible AI becomes real only when decision ownership, data handling, audit trails, exceptions, procurement, and support are assigned to people.
Enterprise AI Delivery Starts After the Pilot. Enterprise AI Delivery Starts After the Pilot
Enterprise AI delivery usually fails after the demo, when ownership, governance, support, procurement, data access, and measurement have to become real.
Deep Tech Needs Translation, Not Simplification. Deep Tech Needs Translation, Not Simplification
Deep tech communication should reduce avoidable opacity without pretending hard problems are simple, commercially ready, risk‑free, or easy to deliver.