AI Security
You blocked ChatGPT on the corporate network and added an acceptable-use policy. The incident log did not change, because shadow AI is not a discipline problem. It is a workflow problem: people take the faster path you did not give them.
AI in Software Delivery
Your developers ship code faster, pull-request volume doubles, and the lead-time number your board watches does not move. The speedup was real. It just relocated the constraint to the stages nobody re-staffed.
AI Strategy
Every prototype demoed beautifully. Six months later nothing has shipped, and "our AI strategy is basically a list of pilots" stops being a confession and starts being a diagnosis. Here are the eight stages that move a prototype into production.
AI operating model
Your engineers are shipping more code than ever and the delivery metrics still have not moved. The gap is usually a missing control layer: written intent that an agent's output gets reviewed against, before anything is generated.
AI Enablement
Most open with license count: a procurement number dressed up as a transformation metric. Here is what an honest dashboard drops, what it tracks instead, and why it is really a decision about your operating model.
Quality Harness Engineering
Quality Harness Engineering: The Emerging Stack for Reliable AI Systems
AI governance
Every AI failure I have investigated had a human who pushed the button. Automation is a delivery mechanism, not a transfer of responsibility.
AI Adoption
Eighteen months in, the licenses are paid and the dashboards haven't moved. AI adoption fails as procurement and succeeds as role redesign. Five issues that compound in this exact order.
AI Security
Most AI rollouts ship the tool before the policy. By Q3 the org has the habits the policy was meant to prevent. Ship policy first - in days, not quarters.
AI Enablement
Dev, QA, PM, BA, SA - five delivery roles, five different ways AI breaks them. Generic training fits none. The fix is a per-role playbook with four components, the last of which is the part a manager can inspect in five minutes.
AI Adoption
The 4-Level AI Adoption Evaluation Model: How to Tell What Your Delivery Team Has Actually Changed
AI Adoption
Most AI programs stall around month nine because nobody can show the board what actually changed. A five-rung ladder that places an org by the artifacts it produces - PRs, ADRs, test plans, postmortems - and names the missing operating asset at each rung.