A JUG for Everyone Meetup

## Details

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Book your ticket at the AJE Eventbrite event page
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Join us for an evening of tech talks, community networking, and good conversations at our next AJE Community Meetup!
Whether you're a backend dev, full-stack engineer, or just getting started in tech, this event is a great opportunity to:

• Hear insightful talks from fellow engineers
• Share ideas and challenges
• Connect with others working in the London tech scene

Our goal is to create a friendly and supportive space where technologists can learn from each other — and have some fun along the way. And if you think that public speaking is fun and can enhance your professional growth, why not to submit your talk at our Call for Papers page

Talk 1: Technical Debt Is Business Debt
Andrea Laforgia (Lead Consulting Engineer at Armakuni)
Technical debt is often seen as a purely engineering issue—but that’s a dangerous misconception. In this talk, we’ll explore how technical debt is not just "technical": it carries real business risk, impacting speed, flexibility, and long-term value. Yet not all technical debt is bad; in agile environments, it's a natural consequence of moving fast and learning continuously. Through real-world examples, we’ll reframe technical debt as business debt—something that must be managed strategically. We'll also show how engineers can better communicate the trade-offs of technical decisions, helping the business make smarter, more informed choices.

Talk2: Modernising Code reviews with AI
Sergei Nasibian (Quantitative Strategist at Rothesay)
As systems grow more complex, managing interdependent computations at scale becomes a key challenge. In this session, Sergei Nasibian will introduce a graph-based computation paradigm, where computations are modeled as nodes in a directed graph. This allows for efficient partial recomputation, dependency tracing, and optimized execution pipelines. Sergei will provide practical examples from the financial industry, showing how these principles can be applied to real-time scenario analysis, large-scale simulations, and dynamic analytics systems. This session will help attendees understand how graph-based models can streamline the management of complex data flows, improve performance, and enhance traceability in real-time applications—particularly relevant for Data Engineers and Data Scientists working with scalable systems and real-time data.