Hi Dupa,
AI has moved from experiments to always-on systems that run core business operations. As adoption grows, the hard part is no longer just building models. It is running AI systems reliably at scale, under real traffic, with infrastructure that was not always designed for machine-driven workloads.
On June 23rd, InfoQ will host a 60-minute live roundtable and Q&A on “The Infrastructure Challenge Behind Production AI”. We’ll dig into how production AI is changing infrastructure design, where existing systems are starting to break down, and what teams need to rethink as AI becomes a permanent part of modern software systems.
Topics include:
- Identifying where AI-driven workloads will put pressure on existing systems before they fail
- Designing infrastructure that can handle always-on AI systems at scale
- Understanding what separates teams that scale gracefully from those facing outages
- Rethinking data systems, cloud platforms, and production databases for machine-driven demand
- Learning what patterns are emerging from practitioners already running AI in production
Join the InfoQ Live Roundtable for a practical discussion on what is working, what is breaking, and what engineering leaders need to prepare for as AI adoption grows:
