The hard questions
underneath AI.
AI engineering talks for audiences that want more than another trends presentation. Where should an agent have authority? What happens when a model is wrong? What must change in the system through which work gets done?
Authority. Failure. The system of work.
Current proposals
Where agents should have authority, and how systems should behave when models are wrong.
Stop Telling Your Agents What to Do
Boundary-Driven Autonomy
Define the boundaries. Don't dictate the path.
- Agentic Autonomy
- Human-Centered AI Leadership
For: AI engineers, software architects, and AI engineering leaders designing agents with consequential tool access
Stop Trying to Make AI Safe
Engineer for failure before it reaches the outcome
Model failure should be expected. System failure should not.
- Reliability, Safety & Resilience
For: AI engineers, architects, and technical leaders accountable for AI systems that can affect people, money, or production operations
The broader repertoire
The engineering system AI works inside, and the organizational changes required to use it well.
Stop Building Faster. Build the Machine.
Engineering the system that builds the product
Don't just use AI to build the product. Engineer the system that knows how products get built.
- AI-Native Organizations
- Human-Centered AI Leadership
For: AI engineering leaders, software architects, and teams designing agent-assisted software delivery
Confusing AI Usage with AI Transformation
Redesigning the system through which work happens
Giving everyone AI tools does not make an organization AI-native.
- AI-Native Organizations
- Human-Centered AI Leadership
For: Executives, operating leaders, and AI engineering leaders responsible for changing how work moves across an organization
An argument to examine.
A room to work it through.
The format follows the problem.
Start with the decision your audience needs to make.
Keynotes
One defensible thesis, the architecture behind it, and the consequences for how your audience builds AI systems.
Executive sessions
Examine the gap between buying AI tools and changing how work happens: authority, governance, handoffs, and organizational constraints.
Panels & podcasts
Work through the tensions in production AI: useful autonomy, imperfect models, engineering discipline, and human judgment.
What should the room reconsider?
Tell me who will be in the room, what they are responsible for, and which AI engineering decision deserves a better argument.
Discuss your event- 01
Tell me about the event
A few details about your audience, timing, and goals.
- 02
Shape the conversation
Align on the topic, format, and practical takeaways.
- 03
Confirm the details
Agree on scope and logistics before a date is reserved.
Bring AI ambition
into practice.
Keynotes, panels, podcasts, and executive sessions
on building dependable AI and leading the teams behind it.