Episode
3 years after ChatGPT, vibes meet grid realities
- Podcast
- Open Circuit
- Published
- Dec 5, 2025
- Duration seconds
- 3097
- Processing state
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Summary
Three years after ChatGPT ignited the AI race, the assumptions driving the trillion-dollar data-center boom are starting to shift. The belief that endlessly scaling large language models will unlock AGI — and justify unprecedented growth in electricity demand — is now being questioned by some of the field’s most influential voices. At the same time, utilities are planning roughly a trillion dollars in grid upgrades, much of it based on speculative data-center proposals and a still-evolving understanding of real load. In this episode, Stephen Lacey unpacks the growing tension between an AI industry defined by rapid iteration and a power system built on decades-long investment cycles. What does that mismatch mean for forecasting, financing, and resource planning? We then feature two conversations from Transition-AI Boston. Former FERC commissioner Allison Clements and Generate Capital’s Peter Nulsen explain why traditional planning signals no longer offer the certainty they once did. How do load uncertainty, short-term contracts, and sequencing challenges reshape the risk profile for new energy projects? In the second discussion, Mike Kramer of Constellation, Dawn Owens of Fervo Energy, and Sam Simmons of Form Energy explore whether AI-driven load will create meaningful demand signals for clean, firm technologies like geothermal, advanced nuclear, and multi-day storage. What will determine if they gain a real foothold? We will soon be opening registration for Transition-AI 2026 in San Francisco. More details here. Nextracker is now Nextpower. As electricity demand surges with AI, data centers and electrified infrastructure, solar is the only power source that can scale fast enough to meet this moment. Nextpower is the technology platform built for this future, delivering…