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LJC Meet-ups is a series of events, aimed at giving all Community members an opportunity to present at an LJC event.

Join us on 1st October 2026 for a London Java Community meetup hosted at Engine by Starling.

Speakers:
Chris Davies, Staff Software Engineer, Engine by Starling

Title:
No Magic, Until It's Worth It: Improving Our Logs with MDC

Abstract:
Good logs should let you answer many questions. Relying on the raw message alone isn't enough. This is the story of how we tried to get there on a platform of 100+ microservices at Engine by Starling — and the "no magic" rule we ended up bending to do it.

Expect a tour through the trade offs of production logging: raw strings, structuring context with Java's MDC, preventing leaks, and why we broke our own rules and reached for a divisive mechanism - Aspect Oriented Programming.

Speaker bio:
Chris Davies is a Staff Software Engineer at Engine by Starling, working in the Payment Card domain to ensure Engine's platform can cope with new payment schemes and global regions. He also leads efforts on Engine's AI tooling, to help developers get the most out of it.

He's spent the better part of a decade in FinTech writing Java and JVM languages (with some TypeScript and Python along the way) and working with AWS serverless technologies. Outside of work, he enjoys attending conferences/meetups, and picking up the odd bit of teaching and technical reviewing when the opportunity arises.

Trisha Gee, Engineer, author, keynote speaker and developer champion

Title:
Shiny New Tools Won't Fix Your Problem

Abstract:
Generative AI can help us produce code faster than ever before, but faster code generation does not automatically translate into faster or safer delivery. In practice, AI acts as an amplifier: teams with strong engineering fundamentals improve, while teams with existing bottlenecks and weak software development practices feel those problems more acutely.

Writing code is cheaper. Testing, troubleshooting, building, deploying, understanding and changing it is not.

In this talk, we’ll look past the hype and focus on what actually drives productivity in an AI-accelerated world. We’ll explore why shiny new tools don’t fix broken systems, why optimising individual steps rarely improves end-to-end flow, and why software engineering fundamentals matter more — not less — when code is easy to generate.

We’ll also look at how observability and measurement help teams understand where time is really being spent, and why accelerating feedback is essential if AI is going to help rather than hurt.

You’ll leave with a clear understanding of:

  • Which engineering practices consistently improve outcomes in an AI world and provide vital safety nets
  • Why good design and readable code still matter
  • What to measure to understand whether AI is really making your team more productive

This is not an anti-AI talk. It’s a reminder that the hard parts of software didn’t get easier, and that fundamentals determine whether AI makes us faster, or breaks us faster.

Speaker bio:
Trisha Gee is a Java Champion, author, speaker, and technology strategist with over 20 years of software engineering experience. She helps organisations make better decisions about technical products: what to build, who for, how developers will use it, and how to communicate its value.

Her career spans software engineering, developer advocacy, product strategy, developer experience, and technical leadership. She has a particular interest in the messy space where technology meets the real world: developer tools, open source, AI systems, and the practices that help engineering organisations build and operate software successfully at scale.

Known for making complex technical ideas understandable, Trisha has spent much of her career acting as a bridge between engineers, product teams, business leaders, and the wider developer community.

She is the co-author of Head First Java and author of Getting to Know IntelliJ IDEA, a regular presenter on the Modern Software Engineering YouTube channel, and one of the few recipients of the Java Community Lifetime Achievement Award.

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