A Big-Picture Framework for AI(opens in a new tab)
My big-picture, framework-level thinking about AI products, presented as a mind map.
On AI, business, and ways of working. Selected for a clear point of view, lessons from practice, or something useful to apply again.
My big-picture, framework-level thinking about AI products, presented as a mind map.
From local efficiency to business outcomes: define the goal, identify constraints, and use an MVP to test the most critical uncertainty.
Distinguish creating value from capturing it: once AI is no longer the bottleneck, look again at the variables limiting opportunities, resources, and outcomes.
How trust builds through everyday delivery: aligning expectations, putting first things first, and keeping a record of the work.
Run through the task, document as you go, then review and iterate based on results. A process should record actions and help you succeed the next time.
A practical path distilled from building a learning-assistance Skill: goal definition, reference analysis, staged handoffs, independent review, and preflight checks.
From model capability to real delivery: delegation, verification, workflow redesign, and human judgment.
From personal tools to organizational infrastructure: long-running tasks, feedback loops, memory, and reusable experience.
As knowledge and execution become more accessible, reconsider judgment, ownership of learning, control, and the value of participation.
A framework spanning project ownership, business interviews, SOP mapping, system building, pilots, and organization-wide adoption.
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Career opportunities, project collaboration, or a conversation about bringing AI into real work.