Competition to bring increasingly capable vehicles to market has never been more intense. Development times are reducing, vehicle complexity is increasing and global market pressures demand that engineering teams make the right decisions earlier than ever. At Lotus Engineering, advanced simulation and objective development methods are combined with decades of vehicle dynamics experience to establish the fundamental character and capability of a vehicle long before the final stages of physical development.

But what happens when the simulation says the car is good? This presentation explores the critical relationship between objective engineering and expert subjective assessment: when the driver enters the development process, what an expert vehicle assessor is actually evaluating, and how subjective observations are translated back into engineering parameters and physical changes. Using the Lotus approach to vehicle dynamics development, John will explore why this human-in-the-loop development remains essential in extracting the last 5% — transforming a technically capable vehicle into one that communicates with its driver, inspires confidence and, ultimately, is engineered For the Drivers.

Artificial intelligence is transforming product development faster than any technology since the introduction of 3D CAD. In just a few years, AI has evolved from answering engineering questions to writing code, generating CAD models, and assisting engineers throughout the design process. But despite the excitement surrounding text-to-CAD, creating geometry is only the first step. Engineering has never been about geometry alone - it is about capturing, understanding, and evolving engineering intent.

This session explores the next generation of AI-driven engineering, where intelligent agents move beyond creating shapes to understanding design intent, manufacturing requirements, simulation results, company standards, and product data. We'll separate hype from reality, examine where AI is delivering measurable value today, and discuss why the future belongs to AI that works within the engineering process - not around it.

Attendees will gain a practical understanding of the technologies driving this transformation, including large language models (LLMs), retrieval-augmented generation (RAG), engineering agents, code generation, and model-aware AI. We'll explore why editable, parametric models remain the foundation of engineering, how AI is becoming a collaborative engineering partner rather than a replacement for designers, and why engineering context is rapidly becoming AI's greatest competitive advantage.

Finally, we'll look ahead to a future where AI doesn't simply generate CAD, rather it creates reusable engineering knowledge, automates complex design tasks, learns from existing products, and accelerates innovation while keeping engineers firmly in control. As AI becomes embedded within cloud-native engineering platforms, organizations will unlock new levels of productivity, collaboration, traceability, and design intelligence that standalone AI tools simply cannot achieve.

Whether you're evaluating today's AI tools or building a long-term digital engineering strategy, you'll leave with a practical framework for understanding where AI creates value today, where it's headed next, and why the future of engineering isn't text-to-product - it's AI accelerating engineers within the engineering system of record.

Attendee Takeaways

• Understand the evolution from text-to-CAD to AI-driven engineering.
• Learn where today's AI delivers real engineering value - and where it falls short.
• Discover how engineering agents, code generation, and model-aware AI are reshaping product development.
• Understand why engineering intent, editable parametric models, and product context are essential for trustworthy AI.
• See why cloud-native engineering platforms are enabling the next generation of AI-powered product development.

Offshore wind is set to become the backbone of Europe's clean energy system, requiring the deployment of thousands of turbines and thousands of kilometres of supporting electrical infrastructure. This unprecedented investment presents a significant opportunity for UK engineering and manufacturing businesses, with UK offshore wind supply chain markets targeted by the UK Offshore Wind Industrial Growth Plan (IGP) expected to be worth £92 billion annually by 2040.

This session will explore the priority areas identified as growth opportunities by UK Government and industry through the IGP, highlighting where support and investment are being targeted across the offshore wind sector. Attendees will gain insight into the guidance, programmes, and resources available to help UK engineering firms position themselves within these strategically important markets. The talk will also examine the technical and commercial realities of developing products for offshore wind applications. From designing large-scale structures and electrical systems capable of operating reliably for decades in some of the world's harshest environments, to understanding how engineering decisions influence customer value, project costs, and competitiveness, success requires much more than technical excellence alone.

Modern engineering systems increasingly face failure modes driven by stochastic physical phenomena that are difficult to detect using conventional signal processing techniques. DC arc faults are a representative example, as their highly variable behaviour, dependence on operating conditions, and transient nature make reliable detection extremely challenging. To address this challenge, we developed a data-driven fault detection framework based on an extensive experimental dataset and machine learning-assisted parameter optimisation, enabling robust identification of arc-fault signatures under realistic operating conditions.

For most of the space age, spacecraft have been designed around a simple assumption: everything must be manufactured, assembled and tested on Earth before surviving launch as a complete system. Emerging capabilities in robotic servicing, in-space assembly and in-space manufacturing are beginning to challenge that assumption, creating new possibilities for how spacecraft and large structures are designed, built and operated.

This presentation will explore three areas where engineering design is beginning to move beyond the constraints of launch. First, how designing spacecraft for in-space servicing could enable repair, upgrade and life extension; second, how designing specifically for robotic assembly could enable structures larger and more adaptable than can be launched conventionally; and finally, how manufacturing directly in space could exploit the space environment and ultimately remove some launch constraints altogether. Drawing on current developments and practical engineering challenges, the talk will consider what engineers need to do differently when launch is no longer the end of the manufacturing process.