Webinar Recording
The CAFE(S) framework: Improving AI agent effectiveness through better context (EMEA/US)
As AI agents become more capable, context quality is increasingly becoming the limiting factor in their performance. DX hosted an early look at CAFE(S), a new framework for evaluating whether AI agents have the context they need to do their jobs well. The session introduced the five dimensions of CAFE(S) and demonstrated how engineering organizations can use them to understand how context quality influences agent performance, developer productivity, operating costs, and scalability. This panel discussion includes Distinguished Scientist Brian Houck (DX) and fellow CAFE(S) authors Max Kanat-Alexander (Capital One), Eirini Kalliamvakou (Github) and Margaret-Anne Storey (University of Victoria).
The session covers the following:
- A practical framework for evaluating the quality of AI agent context.
- A shared vocabulary for diagnosing common context failures before they become production problems.
- Guidance for individuals, teams and organizations to improve context quality.
Watch the recording
Speakers
-
Brian Houck
Distinguished Scientist, DX
-
Eirini Kalliamvakou
Research Advisor, GitHub
-
Max Kanat-Alexander
Executive Distinguished Engineer, Capital One
-
Margaret-Anne Storey
Professor of Computer Science, University of Victoria
Powering the world's top companies
