Cost Alongside Quality: Proving the ROI of Your Coding Agents and AI Apps

​Where is your AI budget going, and is it actually improving quality?

​Join us for a practical look at how Arize AX helps you understand and reduce AI spend across the coding agents your team uses and the AI apps you ship.

​You'll learn how to connect cost with quality, uncover the calls driving up your bill, and find opportunities to save without hurting performance.

​Through live demos, we'll show simple ways to cut costs and how an AX managed agent can investigate a spending spike and propose a fix for your team to review.

​This is part one of two. Stay tuned for a follow-up on what's next for unified, organization-wide AI spend visibility.

​What we'll cover (30 min presentation + 15 min Q&A)

• ​How to track AI spend across Claude Code, Cursor, GitHub Copilot, and the apps and agents you ship

• ​How AX breaks down cost by model, token type, span, and trace, including custom and negotiated pricing

• ​How to compare cost with evals and quality metrics using AX dashboards, monitors, and AQL

• ​Where techniques like model routing, prompt caching, and context trimming can reduce spend without hurting quality

• ​How an AX managed agent can investigate a cost spike, rank expensive calls, and draft a fix for review

• ​A first look at what's next for unified, organization-wide AI spend visibility (full deep dive in part two)

​Who this is for
AI engineers, LLM app developers, and platform teams running agentic or high-volume LLM applications on Arize AX who own (or feel) the model bill and need to show ROI on their spend.

​Format
30-minute presentation, 15-minute live Q&A

​Level
Intermediate. Assumes familiarity with LLM apps and basic tracing or evaluation concepts. No prior Arize experience required.