AnalysisOpinion / analysisAgents & Tool Use · Applications · Evaluation & Benchmarks1 source · Oct 11, 2026

Let Your Agent Cook: Using Skills to Evaluate and Improve Your App — Ankur Duggal, Arize AI

A financial agent invents answers, repeats tool calls and produces summaries that its own evaluations flag as wrong.

Proof1 independent outlet

Key points

  • Ankur Duggal connects those failures to a coding agent through Arize's CLI and skills, then asks it to investigate traces, change the application and run experiments.
  • Questions cover local experiment execution, judge models, evaluation costs, sampling and the risk that a coding agent spends its effort on linting instead of the actual defect.
  • 1:58 - Traces reveal an agent's actual decisions
  • 7:27 - CLI and skills as the interface

Sources (1)

Extractive summary: sentences quoted from the sources.

Before this

  1. Oct 11, 2026openai/openai-python v3.29.0
  2. Oct 11, 2026Agent Speedrun — Elizabeth Fuentes Leone & Sandhya Subramani, AWS
  3. Oct 9, 2026openai/codex rust-v0.162.1: 0.162.1
  4. Oct 8, 2026openai/codex rust-v0.162.0: 0.162.0
  5. Oct 8, 2026Understanding Jev, the new model everyone is talking about
  6. Oct 7, 2026[AINews] Claude Haiku 5.5 — better than GPT-6 Luna at the same pricing

Related