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Arize Builders Meetup - NYC - Boosting Claude Code performance with prompt learning

Date
Thursday, March 12, 2026
Time
Venue
Betaworks
Format
Format not listed
Access
Paid

View original listing at luma.com

About this event

Your CLAUDE.md file is more powerful than you think. In this talk, we'll walk through how we applied Prompt Learning — an RL-inspired prompt optimization technique — to improve Claude Code's performance on SWE-Bench Lite by up to 11%, purely by optimizing the system prompt instructions. No fine-tuning, no new tools, no architecture changes. Just better prompts, driven by real performance data and LLM-as-a-judge feedback. We'll cover the full optimization loop (rollouts → LLM evals → meta-prompting), show results for both general coding improvement and repo-specific specialization, and share practical takeaways you can apply to your own coding agent workflows today. Agenda 6:00 - 6:30 PM | Check-in & Networking6:30 - 7:00 PM | Laurie Voss, Arize AI - Boosting Claude Code performance with prompt learning7:00 - 7:20 PM | Aydrian Howard, Auth0 - Trust, but Verify: Identity and Observability for AI Agents: AI agents that take real actions (reading email, making purchases, querying private documents) need more than a system prompt to be safe. In this session, we'll look at how identity management and observability tooling work together to make AI agents trustworthy: ensuring agents only act within authorized boundaries, and giving you full visibility into every decision they make.7:20 - 7:50 PM | Paul Butler, Modal AI - Sandboxes Hot Takes: Paul will discuss some of the surprising take-aways from four years of working on agent sandboxes.7:50 - 8:30 PM | Networking Food and drinks will be provided. Space is limited—register soon to secure your spot!