Building Self-Learning Loops for Your Agent — Fuad Ali, Arize AI
A shopping assistant confidently returns products outside a user's budget because its price filter is broken.
Proof1 independent outlet
Key points
- Fuad Ali uses the Wonder Toys assistant to show how a production failure can become a complete improvement loop: collect the trace, investigate the code, propose a fix and test it against the cases that failed.
- The example starts with an application built on the OpenAI Agents SDK and instrumented with Arize.
- Arize skills provide a more direct route from a coding agent to traces, datasets and evaluators.
- Agent experiments replay failure datasets against a deployed development endpoint and compare quality, latency and cost before a change ships.
Sources (1)
- [1]Building Self-Learning Loops for Your Agent — Fuad Ali, Arize AIAI Engineer (YouTube) · Oct 11, 03:30 PM
A shopping assistant confidently returns products outside a user's budget because its price filter is broken.
Fuad Ali uses the Wonder Toys assistant to show how a production failure can become a complete improvement loop: collect the trace, investigate the code, propose a fix and test it against the cases that failed.
Extractive summary: sentences quoted from the sources.
Before this
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