Inevitable

Varun Sivaram is Founder and CEO of Emerald AI, a company building software that makes AI data centers power flexible. As AI data centers become one of the fastest-growing sources of electricity demand, grid constraints are emerging as a critical bottleneck for compute deployment.
In this episode, the conversation focuses on why power availability — not GPUs — is increasingly the limiting factor for AI. Data centers concentrate massive electrical loads in specific locations, creating grid stress, long interconnection delays, and rising electricity costs for surrounding communities. Traditional grid expansion alone is too slow to meet near-term AI demand.
Emerald AI’s response is to treat AI data centers as flexible loads rather than fixed ones. Its software coordinates compute with grid conditions by shifting workloads across time, geography, and on-site energy resources like batteries. The episode walks through real-world demonstrations, including a published field trial showing a 25% power reduction during grid stress without breaking compute performance. The discussion frames flexible load as one of the fastest ways to unlock power for AI while improving grid stability.
Episode recorded on Feb 2, 2026 (Published on Feb 10, 2026)
In this episode, we cover:
(0:00) Intro
(1:36) What Emerald AI is and how it works
(6:41) Varun’s background and why he founded Emerald
(10:59) Emerald’s software for power-flexible data centers
(19:04) The three types of flexibility: temporal, spatial, and resource
(23:29) How much control customers give Emerald
(28:20) Coordinating compute with on-site energy like batteries
(31:27) Off-grid vs. grid-connected data centers
(35:39) Why exiting the grid creates political and systemic risk
(37:12) Emerald AI’s open roles
Links:
Varun Sivaram on LinkedIn: https://www.linkedin.com/in/varunsivaram
Emerald AI: https://www.emeraldai.co/
AI data centers as grid-interactive assets paper

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*Editing and post-production work for this episode was provided by The Podcast Consultant

Eugene Kirpichov is Co-Founder and Executive Director of Work on Climate, a global community helping professionals take action on climate across industries and disciplines. Originally created to help people transition into climate-related careers, the organization is now evolving toward a deeper goal: empowering individuals to become climate leaders—people who transform their companies, sectors, and communities from within.
In this episode of Inevitable, Kirpichov shares why the “get a climate job” model is no longer enough, and why systemic change depends on how professionals use their power. The conversation explores the concept of regenerative economics, the breakdown of siloed climate thinking, and the need for new economic architectures that support resilience, not extraction. We also dive into what it means to build bottom-up leadership, how Work on Climate is shifting its model, and why now is a critical moment to invest in alternatives that go beyond federal policy.
Episode recorded on Jan 22, 2026 (Published on Feb 3, 2026)
In this episode, we cover:
(0:00) Intro
(2:40) Climate as one piece of a larger systemic crisis
(7:19) An overview of Work on Climate
(11:28) Why the climate job market isn’t enough
(17:08) The shift from jobs to leadership and power
(24:49) What a regenerative economy actually means
(32:00) Building new economic operating systems
(37:00) The Work on Climate member experience 
(46:49) Final thoughts on reclaiming power
Links:
Eugene Kirpichov on LinkedIn: https://www.linkedin.com/in/eugenekirpichov
Work on Climate: https://workonclimate.org/

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*Editing and post-production work for this episode was provided by The Podcast Consultant

Stu Landesberg is Co-founder and CEO of Seneca, a company developing autonomous aerial systems to detect and suppress wildfires before they grow out of control. Designed for rapid initial response, Seneca’s technology deploys robotic aircraft that launch within minutes, helping protect homes, infrastructure, and communities in fire-prone regions.
In this episode of Inevitable, Landesberg shares why he left Grove—his first company focused on sustainable consumer goods—to tackle what he sees as a civilization-level challenge: early wildfire intervention. The conversation explores how climate conditions, outdated fire cycles, and insurance market failures have converged to threaten life in the American West. Landesberg walks through Seneca’s approach to changing that trajectory: distributed strike teams of large autonomous suppression copters, built in the U.S., designed to reach fires faster than any existing response method. He also unpacks the product’s potential for mop-up operations, prescribed burns, and utility asset protection.
In this episode, we cover:
(2:40) Wildfire as a threat to housing and the economy
(10:07) The urgent need for faster fire response
(15:12) Why helicopters aren’t a scalable solution
(20:03) New use cases beyond initial attack
(28:25) What autonomy looks like in practice
(33:11) Why Seneca isn’t just another drone company
(38:21) Wildfire as a climate and national security risk
(46:18) Seneca’s first deployments and what’s next
Links:
Stuart Landesberg on LinkedIn: https://www.linkedin.com/in/stuartlandesberg
Seneca: https://seneca.com/

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*Editing and post-production work for this episode was provided by The Podcast Consultant

Augustus Doricko is Founder and CEO at Rainmaker, a company using cloud seeding, drones, and radar to increase rain and snow as water scarcity and drought intensify across the West. In this episode of Inevitable, the conversation focuses on why cloud seeding—often misunderstood as science fiction or geoengineering—has existed for decades and why it has only recently become possible to prove it actually works.
The discussion centers on the industry’s core constraint: attribution. For years, operators couldn’t measure whether precipitation would have occurred anyway. Doricko explains how advances in dual-polarization radar and targeted flight paths now make it possible to identify human-caused snowfall, unlocking a path to scale.
Doricko also walks through Rainmaker’s vertically integrated approach, from weather-resistant drones and proprietary radar to software and validation systems, and why the company focuses on snowpack as a bankable water source. The episode also addresses public scrutiny, regulatory bans, and what it takes to build water infrastructure in a category that’s easy to misunderstand but increasingly necessary.
Episode recorded on Dec 16, 2025 (Published on Jan 20, 2026)
In this episode, we cover: 
[1:53] Cloud seeding vs geoengineering 
[3:27] How cloud seeding works and its history
[9:14] When and how it became commercially deployable 
[15:28] Advantages of using drones vs manned aircraft 
[18:34] The limits of today’s validation methods 
[24:54] Why Rainmaker focuses on snowpack first 
[27:34] Rainmaker’s go to market
[29:34] Acquiring legacy operators to scale faster
[32:40] Why Rainmaker sells services, not water
[38:25] State bans, politics, and public backlash
[40:39] Chemtrails and Texas flood controversies
[47:15] The future of cloud seeding in the US and abroad

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*Editing and post-production work for this episode was provided by The Podcast Consultant

Philip Johnston is co-founder and CEO of Starcloud, a company building data centers in space to solve AI's power crisis. Starcloud has already launched the first NVIDIA H100 GPU into orbit and is partnering with cloud providers like Crusoe to scale orbital computing infrastructure.
As AI demand accelerates, data centers are running into a new bottleneck: access to reliable, affordable power. Grid congestion, interconnection delays, and cooling requirements are slowing the deployment of new AI data centers, even as compute demand continues to surge. Traditional data centers face 5-10 year lead times for new power projects due to permitting, interconnection queues, and grid capacity constraints.
In this episode, Philip explains why Starcloud is building data centers in orbit, where continuous solar power is available and heat can be rejected directly into the vacuum of space. He walks through Starcloud’s first on-orbit GPU deployment, the realities of cooling and radiation in space, and how orbital data centers could relieve pressure on terrestrial power systems as AI infrastructure scales.
Episode recorded on Dec 11, 2025 (Published on Jan 13, 2026)
In this episode, we cover: 
[04:59] What Starcloud's orbital data centers look like (and how they differ from terrestrial facilities)
[06:37] How SpaceX Starship's reusable launch vehicles change space economics
[10:45] The $500/kg breakeven point for space-based solar vs. Earth 
[14:15] Why space solar panels produce 8x more energy than ground-based arrays 
[21:19] Thermal management: Cooling NVIDIA GPUs in a vacuum using radiators 
[25:57] Edge computing in orbit: Real-time inference on satellite imagery 
[29:22] The Crusoe partnership: Selling power-as-a-service in space 
[31:21] Starcloud's business model: Power, cooling, and connectivity 
[34:18] Addressing critics: What could prevent orbital data centers from working
Key Takeaways:
Starcloud launched the first NVIDIA H100 GPU into orbit in November 2024 
Space solar produces 8x more energy per square meter than terrestrial solar 
Breakeven launch cost for orbital data centers: $500/kg 
Current customers: DOD and commercial Earth observation satellites needing real-time inference 
Target: 10 gigawatts of orbital computing capacity by early 2030s

Enjoyed this episode? Please leave us a review! Share feedback or suggest future topics and guests at [email protected].
Connect with MCJ:
Cody Simms on LinkedIn
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*Editing and post-production work for this episode was provided by The Podcast Consultant