Insights
Practical perspectives on Agile, engineering leadership, DevOps, and AI-assisted development
What DORA metrics actually tell you — and what they don't
DORA metrics are the most widely cited measure of engineering performance. Here's how to use them as a diagnostic tool rather than a scorecard — and why the distinction matters.
Read articleWhy most Agile transformations fail — and what to do differently
After running Agile transformations across financial services, retail, and automotive, the failure patterns are depressingly consistent. Here's what goes wrong and what actually works.
Read articleRecovering a failing engineering programme: the first 30 days
When an engineering programme is in trouble — missed milestones, eroding confidence, a team under pressure — the first 30 days determine whether recovery is possible. Here's the approach that works.
Read articleThe jump from senior engineer to engineering manager: what nobody tells you
The transition from individual contributor to engineering manager is one of the hardest career moves in tech. Most people aren't prepared for how fundamentally the job changes.
Read articleAI-assisted development in practice: lessons from building four products
Over the last eighteen months we used AI-assisted engineering to build four production products. Here's an honest account of what worked, what didn't, and what the experience changed about how we build software.
Read articleFlow metrics: measuring what DORA can't
DORA metrics tell you how fast and safely you deploy. Flow metrics tell you where your work gets stuck before it ever reaches deployment. Used together they give you a complete picture of engineering delivery.
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