Three hours. Two tracks. Zero fluff. The AI summit for the people who build it and the people who have to decide on it. On November 5, we bring together two audiences that usually get separate events: engineers and decision-makers. Meet speakers from Google, Cursor and emagine through 6 sessions - each one delivered by a practitioner who has shipped the thing they are talking about.
Most AI events pick a side. They either go deep on architecture and lose the business, or stay at strategy level and lose the engineers. This one runs both at once. The technical track is for the people writing the code and designing the systems. The business track is for the people who have to fund it, govern it, and get an organisation to actually use it. Shared opening, shared close, and everything in between running in parallel, so you can send your engineers to one and your leadership team to the other.
Nobody is here to sell you a platform. Six sessions, six arguments, and the reasoning behind them — with time to push back in the Q&A.
One event, one link, two audiences served properly. Move between the tracks freely on the night.
Online, free, and over in an evening. No flights, no budget approval, no week out of the office.
Both tracks run in parallel. The opening and the closing are shared by all attendees, and there are five minutes between sessions so you can switch tracks.
Opening: setting the AI agenda for 2026/27
Technical track: Chouaieb Nemri, Google Cloud : AI Writes the Code. What’s Left for the Engineer? / Business Track: Christian Pedersen, emagine: Why Owning Your Intelligence and AI Becomes a Strategic Imperative
Technical Track: How Cursor's agents ship most of our code: From 1 in 10 to more than Half. / Business Track: From Silent Efficiencies to Proven KPIs
Technical Track: Marian Rams, emagine: Architecting Agentic AI Platforms Without Lock-In / Business Track: Julie Marie Porskjær, emagine: AI Is New. The Challenges Are Not.
Closing: Q&A and wrap-up
Generative AI Blackbelt, Google Cloud
Chouaieb Nemri is a Generative AI Blackbelt at Google Cloud, where he helps enterprises take AI from ambition to production. He works with engineering teams on the systems that carry it — agentic frameworks, LLM applications, retrieval architecture and MLOps — and on the gap between a promising prototype and something an organisation can actually run. He holds Google Cloud and Kubernetes credentials, and master’s degrees from Georgia Tech and INP Toulouse (ENSEEIHT). He speaks and mentors widely on applied AI, and works to open technology careers to people with disabilities.
Chief AI Officer, emagine
Christian Pedersen is a technology leader at emagine who turns AI innovation into real business value. He built the company’s technology organisation from the ground up: 40+ people, globally distributed and remote-first, overseeing everything from infrastructure to AI engineering. He leads with a product-centric mindset, aligning technology decisions with C-suite objectives. He speaks on AI ownership, architecture and adoption, most recently at the CyberAI Expo in Munich in June 2026.
Field Engineer, Cursor
Emil Nildersen is a Field Engineer at Cursor, helping engineering teams across the Nordics adopt AI-assisted development from technical discovery and proof of concept through to production rollout. A builder at heart with a background as a Solutions Architect focused on GenAI and RAG architectures, he brings a hands-on approach to working with engineering leaders, architects and developers.
Session Details
For fifty years, being an engineer has meant translating human intent into instructions a machine will follow, and that translation layer is now the part being automated. This session traces how the role shifts as AI absorbs more of the development lifecycle: less typing, and more specifying, reviewing, verifying and deciding what should exist at all. Looking five and ten years ahead, it asks where the engineer’s centre of gravity moves when machines draft faster than we can read, which rungs of the career ladder quietly disappear, and how anyone becomes senior when the practice they would have learned on is automated. All of which leads to the question the session sets out to answer: if the craft can be delegated, what is an engineer for? Speaker: Chouaieb Nemri, Generative AI Blackbelt, Google Cloud
In December, cloud agents wrote about 10% of the PRs merged at Cursor. By July it was 56%. The model barely changed. The environment did. This talk walks through what made that jump possible: giving agents their own cloud computers, a repo they can read, end-to-end verification so changes can merge without anyone checking them out locally, and automations that keep the setup healthy. You'll leave with a practical checklist for making your own codebase agent-ready.
There is a strong pull towards quick wins in AI right now: something you can buy, switch on and show. It is an understandable instinct, and it keeps the conversation on tools. The harder conversation is about foundations: what an organisation genuinely knows, how much of that its systems can actually reach, and whose stack it all runs on. That one is easier to postpone, and it is where the difference between real intelligence and surface-level AI work tends to show up. This keynote steps back from the tooling and asks why ownership of intelligence and AI is becoming a strategic question rather than a technical one: where the pressure is coming from, why it is building now, and why ownership belongs on the same list as the other things an organisation owns deliberately. Speaker: Christian Pedersen, Chief AI Officer, emagine
Most organisations don’t lack AI technology. They lack adoption, and adoption stalls when the business case can’t be proven. Efficiency gains are the usual justification, but they are quiet: spread thin, hard to attribute, easy to question. Growth is different. Revenue and new opportunity show up in numbers the business already tracks, which is why a mindset focused on growth, not savings, is what moves AI from pilot to practice. Florian shows this in sales, a deeply traditional discipline. He rebuilt his sales process, client outreach and pipeline building with AI, following one rule: dare to do, start small, prove it, then scale. The session walks through what he changed, the KPIs that proved it, and what it takes for a team to adopt a new way of working once the numbers are in.
Director AI & Digital Monetization at Malvern Panalytical
Florian Hoffstaedter is a business and AI executive with more than 15 years of experience driving growth, digital monetization and business transformation across industries including media, software, deep tech, e-commerce and industrial technology. As Director AI & Digital Monetization at Malvern Panalytical, he focuses on translating AI, data and software into measurable business value, new revenue streams and scalable digital capabilities. His career spans publicly listed companies, private-equity-backed businesses, corporate spin-offs and founder-led ventures. Starting as a founder and later serving as CEO of Dyrisk, the cyber risk intelligence venture of Munich Re, he has built teams, led business model innovation and helped organisations turn emerging technologies into sustainable growth and commercial impact. Known for his pragmatic and entrepreneurial approach, Florian focuses on proving value quickly, scaling what works and turning innovation into measurable business outcomes.
Head of AI Solutions, emagine
Marian Rams is emagine’s Head of AI Solutions, leading the design and delivery of agentic AI platforms from architecture through to client delivery. His background in distributed systems and cloud-native architecture shapes his approach: reliable foundations first, intelligence layered on top. He also builds and leads the teams that bring these platforms to life.
Senior Management, emagine
Julie Marie Porskjær is a senior management consultant at emagine with over 20 years of experience driving large-scale organisational transformation and closing the gap between strategy and execution. An organisational psychologist by background, she works at the hard intersection of business strategy, operating model design and technology. Having led major transformation initiatives across global enterprises, including work at Accenture Strategy, Novo Nordisk, LEGO and Danfoss, Julie is recognised for her ability to cut through organisational complexity, build genuine executive alignment, and ensure that operating model and technology shifts deliver real, lasting value.
Most AI platforms are built under time pressure, and the decisions that matter get made before anyone calls them decisions. Which database. Which model. Which cloud. Each looks small at the time. Together they decide how much of the platform can still be changed a year later. This session makes the case for treating lock-in as an architectural concern rather than a procurement one. Dependencies belong behind a layer of their own, so a database or a model can be replaced without rewriting the application. Infrastructure should stay a choice you can revisit. Components should be replaceable, as long as the next part still gets what it expects. And whatever is built for one client should sit apart from the platform everyone else runs on. The same thinking applies to how the work is run. Prototype the hardest problem before promising anything. Take the data seriously enough to understand what it actually describes. Automate environment setup, so it stops being a source of drift. None of this is exotic. It is the difference between a platform that ages well and one that has to be rebuilt — the case for reliable foundations first, intelligence on top. Speaker: Marian Rams, Head of AI Solutions, emagine
There is no shortage of excitement around AI, and no shortage of visions of what comes next. The complication is that almost no organisation is starting from a blank page. Two decades of digitalisation produced hard-won lessons about transformation, value creation and organisational change — and as AI reaches the boardroom, much of that experience risks being set aside as though this were an entirely new problem. This session asks what AI leaders should carry forward from the successes, failures and unintended consequences of digital transformation: which lessons still hold, which assumptions need challenging, and where AI genuinely does require a different approach. Because while the technology is new, the organisations adopting it are largely the same: the structures, incentives and leadership choices that shaped earlier transformations have not gone anywhere. Which makes the real question less about how to implement AI, and more about how organisations adapt the way they create value and sustain advantage when intelligence itself becomes part of the equation. Speaker: Julie Marie Porskjær, Senior Management, emagine