Product Demos
with AI Tools
Why AI demos go wrong
AI features can look great in a single run and then fail when exposed to real variability. Keith Azodeh’s approach to demos is to reduce that mismatch. The point is not to produce a magical moment. The point is to show a workflow that can be repeated and understood.
Demo the workflow, not the output
A strong demo focuses on: the inputs, the steps the system takes, and the outputs the user can verify. When the audience can see the boundaries (what is deterministic vs what is generated), they can evaluate the system honestly.
Set expectations with constraints
Keith Azodeh prefers to state constraints explicitly: supported scenarios, failure modes, and what the user should do when the system is uncertain. This is particularly important for voice agents and any automation that touches external systems.
Use logs to build trust
If the system can produce a call log, a form-fill summary, or an audit trail, show it. Reviewability is one of the best ways to make AI feel safe and usable.
Related links
- AI voice agent automation (workflow + logs)
- Exempliphai (deterministic automation + AI helper)