Most of what defines a design never makes it into CAD. Decisions live in chat threads, meeting notes, and email chains ... and then vanish. This session explores how to capture that intent in real time and turn it into structured engineering data that both people and machines can use.
We’ll show practical ways to extract, categorize, and permission contextual data from collaboration tools to automatically generate reports, update project timelines, and speed design handovers. In the near term, this saves hours on reporting, project management, and compliance.
In the long term, it becomes a foundation for more intelligent design automation. We will specifically demonstrate how generative design platforms can use this captured intent, converting unstructured inputs into richer parameter sets, so algorithms can design better, not just faster. Together, we’ll outline how large language models can bridge the gap between messy human context and machine-driven optimization.
Learning Objectives:
How to capture hidden design knowledge: Practical methods to extract and structure engineering intent from unstructured data like chat, email, and meeting notes without changing team behavior.
Immediate operational benefits: How captured intent can automate everyday tasks such as TDP drafting, reporting, and live project updates, improving traceability and speed right now.
Preparing for intent-aware generative design: Why linking human rationale to design parameters will unlock the next wave of generative tools, enabling AI to optimize with context, not just constraints.
