Trace. Eval. Ship: Running AI Agents in production
Anyone can demo an AI agent. Running one in production — where it's traced, evaluated, and trusted at scale — is a different discipline entirely. Join ClickHouse and Women in Tech SG, hosted at the PayPal office in Singapore, for an evening built for the engineers doing exactly that.
We'll dig into the unglamorous work that makes agentic systems shippable: tracing every step an agent takes, building evals that catch regressions before your users do, and the real-time data infrastructure that keeps observability fast when traces hit the billions.
What to expect:
🎤 Yisam Lee (Senior Support Engineer @ ClickHouse) — Trace. Eval. Ship.: observability and evals for LLM agents in production, and how ClickHouse powers the data layer behind tools like Langfuse at scale
💬 Q&A + open discussion — bring your hardest questions on agent debugging, eval strategy, and scaling LLM infrastructure
🍕 Food, drinks, and networking with Singapore's AI, data, and platform engineering community
Who should come: This one's pitched at a senior audience — AI/ML engineers, data and platform engineers, and technical leads shipping (or scaling) LLM-powered systems in production. If you're past the tutorial stage and deep in the "why did my agent do that" stage, this evening is for you.
📍 Venue: PayPal Office, Singapore
🗓️ Date: Thursday, September 25, 2026
🕕 Doors open: 6:00 p.m. SGT
🗓️ AGENDA:
6:00 PM: Registration, Food & Chitchat
7:00 PM: Welcome and Introductions
7:10 PM: Talk - Trace. Eval. Ship: Running AI Agents in production by Yisam Lee, Senior Support Engineer @ ClickHouse
8:00 PM: Wrap-up and Networking
🎤 Session Details: Trace. Eval. Ship: Running AI Agents in production
Every AI agent in production generates a flood of questions: which prompt version caused that regression? Why did the agent pick the wrong tool? Is the new model actually better, or just different? Yisam tackles these head-on, showing how end-to-end tracing turns agent behavior from a black box into queryable data, how eval pipelines built on real production traces replace gut feel with hard signal, and why the storage layer matters more than most teams expect — with a look at how platforms like Langfuse lean on ClickHouse to keep tracing and evals fast at billions of spans. Expect concrete patterns, real war stories from the support trenches, and a workflow you can apply to your own agents the next morning.
Speaker: Yisam Lee, Senior Support Engineer @ ClickHouse
Seats are limited — register now to lock in your spot. 🚀