Production Observability: Metrics That Matter for LLM Apps

Hosted by Dr. Aki Wijesundara

Thu, Jan 22, 2026

10:00 PM UTC (30 minutes)

Virtual (Zoom)

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AI Engineering Bootcamp & Certificate
Aki Wijesundara, PhD and Manu Jayawardana
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What you'll learn

What you’ll learn

Learn key metrics for LLM apps, tracing prompts and responses, debugging hallucinations, and cost control strategies.

Who it’s for

AI Engineers | Backend Engineers shipping LLM features

Outcome promise

You’ll know what “production readiness” actually means for AI systems.

Because shipping AI is only the beginning

This observability mindset is baked into how we teach AI engineering.

Why this topic matters

Once your LLM app works, the real problems start. This session shows what experienced teams measure after launch — latency, cost, quality, and failure modes — using observability tools like LangFuse.

You'll learn from

Dr. Aki Wijesundara

AI Founder | Educator | Google AI Accelerator Alum

Aki Wijesundara is an AI researcher, educator, and founder with a PhD in Machine Learning and experience at Google's AI Accelerator, where he contributed to advancing real-world applications of machine learning and large language models. As Co-Founder of Snapdrum, he helps organizations design, build, and deploy applied AI systems that move beyond prototypes to production-scale impact.

Aki has taught over 5,000+ engineers, founders, and product leaders worldwide how to build production-ready AI systems using LangChain, RAG pipelines, and MLOps frameworks.

He serves as AI Advisor to the United Nations, contributing expertise on responsible AI implementation and policy.

His work bridges cutting-edge research and practical implementation across text, voice, and multimodal AI.

Alongside Snapdrum, Aki serves as CTO of Krybe, an AI voice automation startup, and CTO of Tilli, an edtech company redefining how learners engage with AI-powered education.

Previous students from

Google
Meta
NVIDIA
OpenAI
Amazon Web Services

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