AI doesn't fail because it's bad at your industry
A workshop-facing argument that many AI failures come from missing organisational orientation, not weak industry knowledge.
AI Workflow Architecture further reading, page 2
AI workflow architecture matters because AI adoption fails when tools know the task but not the operating context around it.
What AI workflow should produce six weeks out - the benchmarks that tell you if it's working
A benchmark guide for judging whether an AI workflow is holding six weeks after implementation, using re-briefing, consistency, failure diagnosis, and maintenance as signals.
The difference between a team that uses AI and a team with AI workflow. It's not subtle.
A workshop-facing piece on why scattered AI use only becomes team capability when prompts, tickets, product decisions, and review habits share one record.
What coherent AI context looks like across a real sprint - and why most teams never build it
A short sprint-level explanation of why AI context architecture reduces repeated rebriefing and makes product work more coherent over time.
I've gotten lazy in the best way
With SR-SI, AI stops being a tool you instruct and becomes a teammate that remembers. I offload file-path and wiring details so I can stay in product thinking and discovery.