Construction Technology Podcast - Episode 010 - with Andriy from Nomic.ai

This episode covers Nomic's pivot to verticalized AI for construction, and the broader question of how to build useful AI products in AEC. The conversation works through two paths: training custom models, or harnessing foundational ones. We get into Rich Sutton's Bitter Lesson, why the harness around the model does most of the heavy lifting in construction use cases, how to benchmark the full harness, the change management work that determines whether a rollout sticks, and why outcome-based billing becomes more plausible as these systems embed deeper into preconstruction workflows.TakeawaysDomain-specific harnesses drive most of the performance gains in verticalized AIBenchmarks should measure the full harness, including retrieval, prompting, and tool useChange management is typically the binding constraint on AI adoption in constructionOutcome-based pricing becomes viable once AI owns the deliverable end to endThe biggest win for estimators and PMs is reduced mental load on repetitive review workChapters00:00 Introduction and pivot to AEC04:58 Debate on LLMs in construction10:50 Building custom models15:57 Harnessing foundational models21:01 Rich Sutton's Bitter Lesson26:01 Scaling compute and harnesses31:56 Why the harness matters41:50 Efficiency and time savings56:28 Impact on professional workflows