{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"AI After Dark ","title":"Matt Robillard from SmartAC","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/8c3e3964\"></iframe>","width":"100%","height":180,"duration":3920,"description":"Matt Robillard from SmartAC joins Alex on AI After Dark to explain why he walked into a company with product-market fit but antiquated tech stack and immediately started rewriting everything with AI at its core. He breaks down the difference between horizontal process automation that Service Titan can eventually replicate versus vertical intelligence modeling the actual thermodynamics of HVAC systems that nobody else can touch, why clean energy is magical thinking constrained by the Shockley-Queisser limit and Betz limit, and how hiring the best AI talent in HVAC meant recruiting from SpaceX, Databricks and Perplexity by selling real-world impact over another CRM with AI slapped on. The conversation reveals why OEMs surprisingly embrace their solution instead of fearing disruption, his controversial take that LLMs are stochastic parrots not true intelligence, and how the marginal cost of code going to zero is pure hype when production systems at scale still require senior engineers who deeply understand customer pain points.Click here to watch a video of this episode.00:00 CES takeaways and hardware semiconductor relationships01:53 Joining SmartAC post product-market fit with legacy tech07:15 Data platform challenges and ML model development12:14 Vertical AI defensibility versus horizontal automation18:26 Alignment with Josh and commercial-product pairing24:17 Replatforming effort and organizational design overhaul29:27 Recruiting top AI talent from SpaceX and Databricks36:03 Development velocity changes and junior engineer growth41:01 AGI possibility and stochastic parrots debate48:21 Controversial clean energy physics constraints opinion56:42 Smart home promises and Tesla-style behavioral nudges01;01;10 VC organizational design mistakes over two years01;05;13 Who else should be on AI After...","thumbnail_url":"https://img.transistorcdn.com/c0HwyU-IZhsvyIYSsSdOUiGAVx9bBJQ8wi3A6OCGZVU/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83NjRl/MjJmNmQyM2Q5OTAy/Y2U4OTIyMWM4ZjMy/NzMzMS5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}