XConf Europe 2026 | London
About this Event
What is XConf?
XConf is a two-track tech conference presented entirely by Thoughtworks engineering teams. It is a space for developers, architects and technical leaders to focus on implementation depth, architectural choices and what it takes to run systems in production. With its relaxed atmosphere, the event focuses on open knowledge-sharing, practical lessons from real client projects and connecting with peers across the industry.
Why you should attend?
- Actionable insights grounded in production reality: XConf is built on Thoughtworks’ and our clients’ years of experience tackling complex problems. You won’t get idealized theories here; you’ll leave with practical, battle-tested insights you can actually use.
- The reality of AI-First Engineering: In 2025, the industry talked about what AI could do. At XConf London 2026, we’re focusing on how to actually engineer it safely, scale it and keep it from breaking. For over 30 years, Thoughtworks has pioneered the tech industry. Once again, we’re looking past the initial hype to deliver the engineering rigor required for the AI era.
- A diverse, cutting-edge lineup: We believe great engineering thrives on different perspectives. We are proud that our 2026 lineup currently features 50% women and gender-diverse speakers, delivering a dynamic mix of topics.
✨ You can view our current and growing agenda below. Our exclusive keynote will be announced next month! So stay tuned ✨
Tickets are limited to venue capacity, so get your Early Bird spot today and lock in your 40% discount.
Agenda
From NPCs to LLMs: Using game dev logic to build efficient code agents
Host: Caius Eugene
Info: Current LLM agents are drowning in "token bloat." Shoveling entire repositories into a prompt doesn’t just burn budgets, it destroys reasoning. But what if we stopped treating code as a text block and started treating it as a navigable world?
Join me as I demonstrate how I’ve applied high-performance patterns from AAA Game Development to solve the context crisis. I’ll show you how I've replaced bloated prompts with Graph Traversals to prune data, Behavior Trees for reactive NPC-style decision-making, and Level of Detail (LOD) logic to balance abstraction with fidelity.
Through a live, interactive "code-world" simulation, we’ll explore how these game-engine tactics transform agents from passive readers into agile Pathfinders. Come learn how to build leaner, smarter autonomous systems that master repository-scale engineering without losing their mind.
AI Assistants are easy - until compliance shows up: Lessons in healthcare
Host: Lorisa Perdoci
Info: Prototyping an AI assistant is easy. Shipping one into a regulated environment is not. In this talk, I'll share lessons from building a production-ready agentic AI assistant for a health science project, where compliance, safety, and trust were as critical as model performance.
We'll go beyond the demo to explore the real challenges: grounding agents in reliable data, enforcing regulatory and ethical guardrails, ensuring auditability, and designing for meaningful human oversight. I'll walk through the key architectural decisions, trade-offs, and failure modes encountered along the way.
Attendees will leave with practical insights on building agentic AI that holds up under real-world constraints, relevant to anyone working in regulated domains, or anywhere the stakes are too high for "it works in the notebook."
Scaling ETL migrations to 300x with AI & engineering
Host: Carolina Allende & Aakash Jain
Info: Enterprises have been running critical data pipelines on aging platforms for decades and migrating them to GCP is genuinely hard.In this talk, we will share what actually happened when we combined engineering expertise with AI-assisted code translation on a large-scale migration. We built a human-in-the-loop workflow — not because it sounded good, but because full automation kept breaking things that mattered. The result: The first iteration we achieved 60x faster migration the goal was to ran 200–300× faster. The tradeoffs were real too. We’ll cover: What made the legacy platform so difficult to migrate ∙ How we designed the AI-assisted workflow and where we drew the human line ∙ What failed, what we fixed, and what we’d do differently ∙ What teams planning similar work should watch out for No vendor pitch. No cherry-picked metrics. Just delivery experience.
Clarity-First method: Vibe-coding products without tech debt
Host: Maria Jose Lalama
Info: Product Managers are becoming Product Builders. Vibe-coding and shipping AI-generated products fast is no longer an experiment, it's a core skill. PMs who can validate ideas quickly and reduce feedback loops become force multipliers for engineering teams. But the engineering concern is valid: will this ship with technical debt?. Join me to answer the question with Vivian, a women's health app shipped in 48 hours using AI orchestration with structured product thinking. The result: zero technical debt, dedicated security sprints, and real users validating faster than ever. Built following the Clarity-First Method, that separates hastily-built prototypes from production-ready products.
Learn about Specification as Architecture to define constraints before AI builds, through research, PRD, system design, Master Prompts and Prompt Stories. Context-Aware Consistency to maintain quality across builds through token governance, security sprints, and human-in-the-loop decisions.
Evals over Guesswork: Deploying an AI defect analysis system with confidence
Host: Fabian Nonnenmacher
Info: Moving an AI defect analysis tool from a "cool prototype" to a reliable production system takes more than just tweaking prompts. It requires a serious commitment to Evaluations (Eval). We’ll walk you through the real-world deployment of our system, treating evaluation as the equivalent of traditional software testing for AI applications.
Using our application as a live case study, we’ll dive into how we evaluated critical features like summarization, data extraction, and duplicate detection. We’ll demonstrate how an evaluation-driven development cycle turns the application's performance into a measurable, repeatable process rather than a guessing game. Finally, we’ll bridge the gap between the lab and the real world by showing how to combine offline benchmarks with live feedback. Our goal is to prove that running evaluations isn't a daunting academic exercise - It’s a necessity that brings the discipline of standard engineering to the world of AI.
Using AI to make legacy systems legible: Navigating systems we can’t afford to
Host: Prachi Tyagi
Info: Legacy systems are easy to dismiss as old technology, but in many organizations they are still the systems the business depends on every day. They carry years of decisions, exceptions, workarounds, integrations, and operational history. The difficult part is that this complexity is rarely visible in one place, which makes even small changes feel slower and riskier than they should.
This talk looks at AI through that legacy lens: not as a replacement for engineers, and not simply as a way to generate more code, but as a practical aid for making complex systems easier to navigate and safer to work with.
The session will offer a grounded way to think about where AI helps, where human judgment remains essential, and how teams can use both to evolve systems they cannot afford to break.
AI-first software maintenance & AI-first software delivery
Host: Vitória Regina Ragazzon Toebe, Amy Pellegrini
Info: Most conversations about AI in software engineering focus on shipping features faster. But in a fast-moving environment, the real bottleneck often lives on the other side: the time between a reported issue and a confident resolution.
We'll share how a maintenance team and a delivery team — working on a core service with multiple consumers, spread across internal and external teams, investigating issues across multiple data sources — operate as one connected AI-first system. With workflows designed around AI strengths: triage, data correlation, supporting cross-team communication, and handling context cleanly between maintenance and delivery.
You'll leave with concrete patterns for AI-first incident management, a model for maintenance-delivery collaboration that scales, and an honest view of where AI helps — and where it still gets in the way.
What agents do when you’re not looking: Lessons from building and watching age
Host: Matias Vizcaino
Info: Coding agents have evolved fast: from chat assistants, to copilots, to increasingly autonomous systems that can plan, delegate and act. That shift is exciting, but it also creates a new engineering problem: what are these systems actually doing when we are not watching closely? In this talk, I’ll trace that evolution, starting with war stories from the industry that make the risks feel real and familiar. Then I’ll share what I’ve learned from building and observing my own agent teams in Claude: the funny moments, the unexpected interactions, and the patterns that only become visible when you look at traces and behaviour instead of demos. I’ll close with the emerging practitioner playbook for this space: how teams are starting to observe, evaluate and govern agents so we can use them with more confidence in real-world delivery.
Building sovereignty: Where your AI runs matters
Host: Jens Peveling
Info: European organizations and governments racing to leverage AI and large-scale data analytics face an uncomfortable truth: the platforms they run their critical services on, train AI models on, the pipelines they feed sensitive data into, and the infrastructure governing their data residency are controlled by hyperscalers — architecturally unfit for true sovereignty. This talk is based on first-hand experience building a sovereign cloud from bare metal for the European energy sector. I present core concepts for building a platform designed for running critical workloads and data-intensive operations under full jurisdictional control — no hyperscaler dependencies, no shared-responsibility illusions. I examine why sovereign infrastructure is becoming a strategic necessity, not a niche concern: how data gravity, AI model training locality, and regulatory frameworks force a rethinking of where and how we build cloud platforms.
Where is it happening?
Event Location & Nearby Stays:
GBP 149.00 to GBP 249.00
