Name: JSNation US 2026
Start: 2026-11-16T13:00:00.000Z
End: 2026-11-19T22:59:00.000Z

HT Sahin

Vitor Barbosa

Sanketh Kumar

Basseydou OUATTARA

Jonathan Kemp

Fathima Fasna

Ellis Antaya

Chris Yates

Yakovlev Eugen

Erin Murphy

Ivan Orekhov

Jacob Rasmuson

Varun

Michael Chiche

Hugo Blanchard

Ivan Almasi

El Mehdi Aarab

Veranika Kasparevych

Iandra Bedin

Keertivaas S

Martin Jensen

Aleena Harold Peter

Daniele Macannuco

Erik

Alexandra Domareski

Bob Clingan

Andrés Campuzano

Ray Adeniyi 

Ethel Cofresi

Sulagna Ghosh

React Summit attendee

Matt Priour

Matthew Malone

Vanessa Aristizabal 

AI is writing more code every day. The skill that won't get automated is knowing what to build and the system design thinking to make it happen at scale. In this full-day workshop, you will develop the judgment that sits upstream and downstream of implementation: how to validate a problem before you commit to a solution, how to understand the users you are actually building for (not the ones you imagine), how to prioritize ruthlessly when everything feels urgent, and how to establish feedback loops that keep you building the right things after you ship. These are not PM skills. They are the technical judgment that the best engineers have always had, and that becomes the defining skill as implementation gets faster and cheaper. What you will learn:- Validate before you build: surface real user pain, not solution-shaped stories- Understand users in context: close the gap between your mental model and theirs- Prioritize what deserves to exist: apply the Kano model and know what to cut- Translate decisions for stakeholders: navigate contested requirements productively- Close the loop: establish post-ship feedback habits that drive continuous improvement Who it's for: Software engineers with professional experience. No specific stack required. PMs and designers welcome.

Build the Right Thing: Product Engineering for Software Developers

Kent C. Dodds

JavaScript Framework authors face a brutal tradeoff when it comes to observability, either ship "blind" code and rely on 3rd parties to brittlely monkey-patch your API, or bloat your bundle with heavy observability dependencies. Both options hurt developer experience and performance.Tracing Channels changed this. A native, zero-dependency pattern that allows frameworks to emit events that are contextualized, and execution-correlated end to end.In this session, I'll show how tracing channels enable open observability APIs that progressively enhance with newer Node.js versions and gracefully degrade with zero overhead. We will also take a look at how popular libraries and frameworks that we use today implement their tracing channels and the patterns that allows them to benefit users and APM providers.Stop paying the instrumentation tax. Learn how to build observable frameworks by default, giving your users control without the cost.

Instrumentation Without the Tax: Native Tracing Channels in Node.js

Abdelrahman Awad

In this workshop we'll dive into the latest advancements in React and best practices for building modern React apps. We'll take a look at modern NextJS and React Router 7 Framework along with React's "React Server Components". We'll also talk about improving the data-fetching strategies of your SPAs along with options for migrating your SPA to modern React Router.

Modern React Architecture

Brad Westfall

What happens when AI tools meet the realities of a 130-year-old organisation with legacy systems, complex processes, and high expectations for reliability? In this talk, I’ll share practical lessons from introducing AI-assisted software development in a traditional environment: where it genuinely accelerates delivery, where it fails, and how teams can use it responsibly. Expect real examples, workflows, and honest insights on using AI beyond the hype.

Using AI to Write Software at a 130-Year-Old Organisation

Rumen

AI systems have a new class of vulnerabilities that most developers aren't thinking about yet. This talk covers how they work, what's been exploited in the wild, and where the field is headed.

The Vulnerabilities Hiding in Your AI Workflow

Aviv Keller

Stop prompting. Start orchestrating. In four intense hours you'll go from using Claude Code like a faster autocomplete to commanding it like a senior engineer commands a team: engineering its context, deploying fleets of subagents, locking it down with hooks, and turning it loose on work that runs without you.Every Claude Code user hits a ceiling where the easy wins run out. The agent handles small stuff beautifully, then loses the thread on anything real. The difference between that ceiling and real mastery isn't better prompts. It's control. This workshop is about control.You'll spend the whole four hours inside CLASH, a real full-stack application, handed to you fully built so nothing stands between you and the hard parts. A serious codebase is the point: it's the only place agentic engineering shows you whether it actually holds up.The throughline is context. Treated carelessly, the context window fills with noise until the agent drifts. Treated as a resource you engineer, it becomes the biggest lever you have. From there the toolkit opens up. Repeatable work becomes a reusable Skill. Noisy, exploratory work goes to subagents that run in their own isolated context, several at once when the job allows. Hard rules become hooks the agent cannot cross. Your own systems come into reach through MCP.Then you let go of the wheel, carefully. The same agent that pairs with you can run headless in a pipeline, drive a long task to a defined finish on its own, or live inside your software through the Agent SDK. We close by setting two greenfield methodologies, Spec Kit and BMAD, side by side, so you leave knowing not just how to drive the agent but which approach fits which problem.Two ideas hold it together: context is king, and you push it, you own it. This was never about generating code faster. It's about staying in command while the agent does more.This is an advanced session for engineers, tech leads, and architects who already use Claude Code every day and want to reach the top of the curve. We move fast, and we start in the deep end.

Claude Code: Black Belt

Pawel Sawicki

Python's scientific and data ecosystem rests on one library: NumPy. Pandas, scikit-learn, SciPy, and most ML tooling are built on top of it. JavaScript has never had a real equivalent, and that gap is a big reason serious numeric and data work still defaults to Python. The hard part about bringing NumPy to JS? Performance.numpy-ts is a complete NumPy for TypeScript and JavaScript, and this talk is the story of making it fast. The first version was 15x slower than native NumPy. The obvious move, rewriting hot paths in WASM, got it to roughly 2x slower and then stalled, for reasons that turned out to have nothing to do with FFI overhead. The fix was architectural: changing where the array data lives.We'll trace that journey across 7,159 benchmarks, from 15x slower to faster than native, and the copy tax hiding inside most WASM-accelerated JS libraries along the way.

Who Owns the Bytes? Making numpy-ts as Fast as Native

Nicolas Dupont

AI coding assistants are evolving from simple autocomplete to autonomous agents that can interact with external systems. But how do you teach an agent to follow your workflows and use the right tools at the right time?In this hands-on workshop, you'll discover:<ul><li>What MCP (Model Context Protocol) is and how it standardizes tool integration for LLMs</li><li>How Agent Skills package domain-specific knowledge and workflows for AI agents</li><li>The key differences between MCP servers and Skills, and when to use each</li><li>How to create a custom Skill that orchestrates multiple MCP tools into a cohesive workflow</li></ul>By the end of this session, you'll build your own AI Skill that uses MCP tools — a Matrix-themed Neo fighting skill.Who should attend: This workshop is ideal for software developers who use AI coding assistants (Claude Code, Cursor, or similar) and want to extend their capabilities with custom integrations and workflows. No prior MCP or Skills experience required — just bring your curiosity and a laptop.

Let’s Teach Neo Kung-Fu: Building an Agentic Skill with MCP Tools

Misha Kazakov

Join the Nation`s space program! The conference to get updates from the authors and core teams presenting on the West largest dome screen.

JSNation US

I’m attending the main #JavaScript conference in the US. Join me and 10k other JS engineers. Follow this link to receive a free remote ticket. The theme of the year is AI for coding and the future of #WebDev.

#JSNation

JSNation US 2026

FocusReactive

CKEditor

Hygraph

Bloomberg

FusionAuth

CodeRabbit

Algorand

ButterCMS

Firebase

Arcjet

AWS (Kiro)

CKEditor is a modern, feature-rich JavaScript text editor with clean UI and perfect UX

With 10,000+ front-end apps + one of the world’s largest JavaScript/TypeScript codebases, @TechAtBloomberg is deeply committed to using JS/TS in building the world's most trusted information network for finance pros.

Any Language. Any Platform. Any Technology.

Cut code review time & bugs in half, instantly

Algorand is an energy-efficient, quantum-secure, single-layer blockchain with instant finality, consistently high throughput, and low fees.

Make your app the best it can be with Firebase and generative AI

Kiro helps you do your best work by bringing structure to AI coding with spec-driven development.

FocusReactive is an&nbsp;<meta charset="utf-8" id="isPasted">engineering-led <a href="https://focusreactive.com/services/headless-cms-expert-agency/">Headless CMS Agency</a>&nbsp;and&nbsp;<a href="https://focusreactive.com/next-js-expert-agency/">NextJS&nbsp;development experts</a>. Independent partners of Payload CMS, Sanity, Storyblok, Vercel and Shopify. Delivering&nbsp;<meta charset="utf-8" id="isPasted">Composable content platforms built for AI SEO, growing teams, and marketing velocity.