TanStack Start, AI, and Performance: Rethinking Full-Stack Architecture (with Tanner Linsley)

Full-stack development is moving fast. TanStack Start is changing how we handle data fetching, routing, and server-client boundaries. AI tools like Claude are speeding up how we build and test these systems. But when it’s time for production, one question matters: how do you scale CPU-bound workloads like SSR without losing performance? Luca Maraschi and Matteo Collina sit down with Tanner Linsley, creator of TanStack, to dig into the core principles behind the TanStack ecosystem and what happens when those ideas hit real infrastructure. We share recent benchmarks of TanStack Start running on Watt under heavy load, showing exactly how architecture choices affect throughput, latency, and reliability. In this episode, we cover: ✅ The core principles behind TanStack and why they resonate with modern developer workflows ✅ What happens when TanStack Start hits production workloads, including SSR and CPU-bound bottlenecks ✅ Insights from benchmarking at 1000 req/sec on Kubernetes and what they reveal about real-world performance ✅ Why kernel-level load balancing and multi-worker architectures improve tail latency without adding overhead If you’re building or leading teams on modern full-stack apps, this episode is for you. We break down how framework design, AI tools, and runtime architecture combine to power the next wave of scalable web systems.