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The Node (and more) Banter

Platformatic

The Node (and more) Banter is your weekly dose of unfiltered, unscripted conversations between Luca Maraschi and Matteo Collina.

We explore the edge cases, the anti-patterns, and the things no one puts in the docs. From distributed architecture to platform pitfalls and how enterprises tackle modern development—nothing’s off-limits. It’s not just Node.js®—it’s everything around it, wrapped in sharp banter, war stories, and real-world insight.

The sky’s the limit.

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  • 22 episodes
  • weekly
  • Avg 32 min
  • English

Episodes 22

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  • S2 · E14
    April 15 · 50 min

    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.

  • S2 · E12
    April 8 · 43 min

    Skills, Agents & the Setup That Actually Works for AI-assisted JS Development

    Most developers let their AI assistant guess how to write Node.js. No context, no constraints, no history, just vibes and generic output. The result is code that ignores the event loop, skips proper error handling, and looks nothing like how senior engineers actually build. The question is: can you actually teach your AI to code like you? In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina dive into the emerging AI toolchain for Node.js development, from Agent Skills to coding agents like OpenClaw and Pi. Matteo shares his own personal skills repository (mcollina/skills), a collection of battle-tested Node.js, Fastify, and TypeScript best practices that any AI coding assistant can load and apply out of the box. In this episode, we cover: ✅ What Agent Skills are and why the open standard changes how AI-assisted development works ✅ Why Matteo got frustrated with AI slop and built his own skills repo — and what's inside it ✅ How to install and use mcollina/skills with Claude Code, GitHub Copilot, OpenAI Codex, and more ✅ What OpenClaw and Pi are, and how they fit into the Node.js AI toolchain ✅ The practical question: what should a JavaScript developer actually install today to code with AI effectively? ✅ The difference between prompting from scratch every time vs. encoding your expertise once and reusing it everywhere The takeaway? AI-assisted development isn't just about which model you use, it's about the context you give it. Skills are how you stop training your AI from zero on every project and start shipping faster, with fewer corrections. If you're building with Node.js and you're not using skills yet, this episode will change how you set up your workflow.

Showing 21–22 of 22 episodes