Recently, Superhuman (formerly Grammarly) launched Superhuman Go, an AI assistant that works alongside you on every platform. To build it, we needed a scalable solution that supports an unlimited number of agents that dynamically shapes the user interface and looks similar across all supported desktop and mobile platforms. Join me to find out how we discovered solutions for this innovative new product.

This talk is about taming AI: the journey from a simple Plan Mode in Cursor/Claude to structured specification systems. We'll break down why GitHub Spec Kit turned out to be too heavyweight, how ADR (Architecture Decision Records) helps agents retain context across sessions, and why OpenSpec by Y Combinator (Fission-AI, W26) became our sweet spot. The central thesis: code quality on output equals specification quality on input. Together we'll reflect on the transformation of the developer's role — from "coder" to "spec architect."

What if an engineer receives not a task, but a ready PR with context and a proposed solution? At Wix, we’re building remote agents — autonomous agents triggered by external events (Jira, Slack) that execute tasks in the background without human involvement and return results as context for developers. In this talk, I’ll cover: what remote agents are, how they’re architected, and how to integrate one into your own system. I’ll share real numbers — success and failure cases from our experience. Beyond that, the non-obvious parts: where agents break, why a spec-driven approach is critical for them to work, and what changes in team processes when part of the work is done by an agent. This talk is for those already working with AI tooling and thinking about the next step — from copilot to autonomy.

Ten years ago, we pulled libraries and frameworks into our projects not because we wanted to — but because we had to. It was the only way to survive the “browser wars” era and avoid drowning in spaghetti code. Frameworks became our спасіння, and we got used to them. Since then, the web has evolved — but our habits haven’t. HTML, CSS, and JavaScript have made huge leaps forward, yet we still automatically pull in megabytes of abstractions just to render a simple product list — and proudly call it a “modern stack.” It’s time to ask ourselves some uncomfortable questions: • What problems do frameworks actually solve today — beyond our fear of being left alone with plain JavaScript? • Where is the line where “developer comfort” turns into unnecessary weight for the product? • Have frameworks become just a convenient shield — hiding our reluctance to truly understand the platform? I’m not saying we should delete React tomorrow (although…). But I do want to explore this: do frameworks still solve real technical problems — or are we just building another “Hello World” in React because we’ve forgotten how to do it any other way?

Talking about something abstract is easy and fun — you can sound smart, and no one can really verify your claims because, well, it’s abstract. In a world where every other person is now an “AI visionary,” I want to speak about AI in a максимально concrete way, using my own work at GitLab as the example. It’s a perfect case. While many people describe a world of pink ponies — greenfield projects built from scratch — I want to share the hardcore brownfield reality: what actually happens when you introduce AI into a project that has existed for years. Here’s what we’ll cover: - How AI and JavaScript get along (or, more accurately, don’t) - My setup and “secret sauce” for agentic development - What I’ve achieved together with Opus (my favorite model) - How much JavaScript code I still write by hand - What prevents us from reaching the mythical 10x productivity — and what I’m doing about it My goal is simple: after this case study, everyone should walk away with a clear understanding of what they can implement in their own project to make life better — starting now.

In the age of AI, anyone can generate code — even your team lead or the baker next door. But who ensures its quality? This talk will show why TDD is more relevant than ever, how to tell a good test from a bad one, make AI write proper code from the start, and why discipline and architectural thinking save both your nerves and your projects.

This talk will show how to boost developer productivity with AI tools in Cursor — from automated code reading and writing to building custom AI teammates and end-to-end feature pipelines.

How can you thrive in an industry transformed by AI? This talk covers research and hands-on demos to help secure your career and leverage AI for productivity and growth.

JavaScript and Golang are two different worlds that often intersect in modern projects: the first dominates frontend development and rapid prototyping, while the second excels in high-load services and microservice architectures. In this talk, I will share my personal experience of moving from JS to Go, comparing approaches to asynchronous programming, application architecture, working with databases, and tooling. We’ll explore not only the differences but also the similarities that help developers adapt more easily between these ecosystems.

In many projects, hooks have become a reflex: they’re added automatically, even where they aren’t needed. But every unnecessary hook adds extra complexity—often without any benefit. In this talk, we’ll explore when hooks are unnecessary and how to write simpler, more readable code without redundant use*.