​18:00 - Mingling 🎉, SWAG 🎁, pizza 🍕, and beers 🍻
18:30 - lectures

AI Agentic Development Feedback (Ralph) Loop

​by Neriya (Neri) Rosner, Senior Full-Stack Engineer, DoorLoop

​What if your AI didn’t just write code, but reviewed, tested, deployed, and fixed it on its own?

​Most AI workflows stop at generation. A developer writes a prompt, reviews the output, finds bugs or architectural issues, rewrites the prompt, and repeats, generating wasted iterations and unused code along the way.

​We built a different loop: AI that checks itself end-to-end.

​In this talk, we’ll show how our agent starts with fast static feedback using ESLint and TypeScript, validating its code instantly. It runs unit, integration, API, and third-party contract tests, executes real user flows via Playwright MCP, inspects logs during development with Sentry SpotlightJS, commits and pushes to GitHub, and deploys through Vercel, and solves CI issues.

​Finally, we’ll show how, using Ralph Loop — built on a Research → Plan → Execute → Review framework — the agent can iterate overnight and continuously develop.

​You’ll leave with a practical blueprint for building fully agentic, self-correcting Node.js workflows.

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Exactly once processing is a lie : Building Bulletproof Idempotency in Node.js by Achiya Haviv | Full Stack Developer at Bilton

​"Exactly once" delivery is a great marketing promise, but in real distributed systems, it's an engineering myth. From dropped networks to a personal double-charged bank account, message duplicates are inevitable. In this session, we’ll explore the underlying failure modes of queues like SQS and Kafka, and walk through practical Node.js patterns to build bulletproof, idempotent consumers. Learn how to stop trusting your infrastructure blindly and handle duplicates by design.

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​​DX Guardrails for AI

​​by Kiril Reznik, Software Engineer, Aternus | Master Builder

​Get shivers down your spine when you see a PR with 1k+ lines of code changed?

​With Agentic dev workflows it's easier than ever to get yourself burned out in code reviews.

​Sure we could just "ship fast and break stuff", perhaps ask the agent to implement a feature flag, but who's going to operate it when production breaks and an angry customer call wakes you up in the middle of the night?

​Join me to learn about the guardrails that keep code reviews scalable and DX great.

​Together we'll explore how SDLC has evolved over the past 2 years and you'll leave with practical tools to keep your sanity and reduce risk of surprises while working with AI.

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​Kindly be informed that attendance at the meetup is on a first-come, first-served basis until capacity is reached. Although a place has been reserved for you (after click on attend button), please note that it does not guarantee your spot.