Live Webinar
November 18th, 2025 @ 14:00 GMT / 9:00 EDT
Can AI Make a Good Engineer?
Benchmarking how leading LLMs perform on real engineering tasks using Monolith
AI is rapidly entering the world of engineering — but how capable are today’s large language models when faced with real physics, real data, and real design challenges?
In this exclusive webinar, Monolith reveals insights from our latest LLM Benchmarking Study, where we tested models such as Claude 4, Grok 4, Gemini 2.5 Pro, and ChatGPT o3 across real engineering workflows in the Monolith platform.
Join us to uncover which models show genuine engineering reasoning, which struggle with complex analysis, and what these results tell us about current and future capabilities of AI in engineering.
Webinar Highlights
- How we benchmarked today’s top AIs: Inside Monolith’s MCP framework, testing LLMs on realistic engineering scenarios.
- How effectively LLMs understand engineering problems: From feature selection and model training to reasoning through physics-based constraints.
- Where current models fall short — and where they excel: Insights into performance, repeatability, and engineering intuition.
- How AI is lowering the barrier to engineering analysis: Making advanced problem-solving faster, easier, and accessible to more engineers.
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Who Should Watch?
This session is for engineers and technical leaders who want to stay ahead as AI reshapes engineering workflows:
- Engineers curious about Advanced AI in Engineering and how they could be applied in real R&D and testing contexts.
- Professionals who want to stay ahead of the curve and see how new AI standards like MCPs are shaping engineering.
- Early adopters in R&D and testing who are eager to explore practical, cutting-edge applications before they become mainstream.
If you’ve been hearing about Agentic AI, LLMs, and MCP and wondering “what does this mean for my work?” — this webinar is for you.
Meet our Speakers
Dan Mount
Senior Product Manager
Dan Mount is a Senior Product Manager at Monolith with experience at PwC and Airbus in consulting, aerospace engineering, and project management. He holds an MEng in Aerospace Engineering from the University of Liverpool.
At Monolith, Dan leads AI solutions across engineering sectors, working with cross-functional teams to deliver new features while exploring cutting-edge technologies for integration into engineering and client workflows.
Joel Henry
Lead Principal Engineer
Dr Joël Henry is our Lead Principal Engineer and has worked with the majority of our clients across automotive and battery testing to create lasting value for them.
He has won the Imperial College Award for the best PhD thesis and has previously worked on improving test and simulation methods in the aerospace industry
Simon Daigneault
Product Marketing Engineer
Simon holds an MEng in Mechanical Engineering from Imperial College London, specialising in battery testing. He also spent time at a battery energy storage startup, supporting pack design, testing, and system integration.
At Monolith, Simon interfaces with product, engineering, and commercial teams to translate advances in AI into practical insights for battery development.