Troubleshooting Kubernetes: From Alert to Root Cause
Join experts who have launched AI applications in production as they share practical lessons on architecture, AI costs, reliability, and avoiding common pitfalls.
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How to set your AI project up for production success with the right architecture and infrastructure.
Control AI costs through smarter model selection, token management, and infrastructure decisions.
Keep AI applications running reliably with practical approaches to evaluation, observability, debugging, and maintenance.
Launching an AI project is about far more than choosing a model. Success depends on making the right decisions around architecture, infrastructure, cost, reliability, evaluation, and day-to-day operations.
Join experts who have successfully taken AI applications from idea to production as they share practical lessons learned along the way. Discover common pitfalls, how teams balance performance with cost, and what it takes to build and operate AI applications that are ready for real users.