Arguments worth
building around.
A small collection of engineering arguments: where to place human judgment, how to contain model failure, and why capable AI makes disciplined systems more important. Read them, question them, and test them against the work.
4 ideas to explore
Engineering for AI Failure
Probabilistic component failure is normal. Silent system failure is an architecture defect. Reliability depends on what happens between a model response and a consequential action.
Read the essayThe AI Transformation Gap
AI usage improves individual work. AI transformation redesigns the system through which work happens. The gap appears in handoffs, decision rights, and the outcomes nobody owns end to end.
Read the essayBoundary-Driven Autonomy
Define the boundaries. Don't dictate the path. An engineering framework for putting human judgment where it can govern an agent's authority, resources, and evidence of success.
Read the frameworkBuild the Machine
Do not only systematize product architecture. Systematize how the product gets built. Capable AI needs durable intent, usable boundaries, and an engineering system that can verify its own work.
Read the frameworkBring AI ambition
into practice.
Keynotes, panels, podcasts, and executive sessions
on building dependable AI and leading the teams behind it.