Reading Time: 2 minutes


What if the biggest bottleneck in America’s clean energy transition isn’t technology… but information? In this episode, we sit down with Nat Bullard, co-founder of Halcyon, to explore how AI and machine learning are revolutionizing the way energy policy data is accessed and used. Nat explains how his lifelong passion for organizing complex systems has led to a career dedicated to decoding the regulatory chaos of U.S. energy markets. You’ll hear how his team tackles the “hairball” of unstructured data locked in outdated state-level systems and makes it useful for developers, utilities, and investors alike.

We also dive into the real-world applications of Halcyon’s tools, from tracking the true cost of natural gas power plants to unlocking opportunities created by surging energy demand from data centers and hyperscalers. Nat shares how Halcyon’s data tools reduce “shoe leather costs,” speed up decision-making, and help navigate a dynamic market. Whether you’re curious about public utility commissions, fascinated by AI in infrastructure, or seeking clarity on energy economics, this episode is packed with insights into where the energy sector is headed.

Listen To The Episode

Never miss an episode by subscribing via Apple Podcasts, Spotify, Amazon Music, or by RSS!

What You’ll Learn in Today’s Episode:

  • How Halcyon uses AI to make energy regulation data useful.
  • Why state-level systems create bottlenecks for developers.
  • What it means to “harmonize” public regulatory data.
  • How legacy systems slow down clean energy deployment.
  • The true cost of natural gas plants vs. industry assumptions.
  • What “shoe leather costs” are and how to reduce them.
  • The rise of large-load electricity customers like data centers.
  • Why some industries are cost-sensitive while others are not.
  • How new demand is reshaping U.S. energy strategy.

Resources In Today’s Episode: