Episode 158 of the Data Center Go-to-Market Podcast features an interview with Daniel Lawrence, CEO and Co-Founder at OBM.
Host:
Joshua Feinberg, CEO
DCSMI
Special Guest:
Daniel Lawrence, CEO and Co-Founder
OBM
Daniel Lawrence, CEO and co-founder of OBM, discusses the company's mission to unlock energy agility through load flexibility. OBM started as a Bitcoin mining operation, evolving into a software platform for remote management and load flexibility. The platform now manages over 8 gigawatts of power for Bitcoin mining globally. Lawrence emphasizes the importance of load flexibility for data centers and AI factories, highlighting the need for industries to adapt to grid requirements. OBM's software enables dynamic power management, optimizing energy consumption and generating revenue. The company aims to expand its flexible load management solutions across various industries.
In this episode of the Data Center Go-to-Market Podcast, Joshua Feinberg interviews Dan Lawrence, CEO and co-founder of OBM, about the intersection of Bitcoin mining, AI factories, and grid-level energy flexibility. You’ll see how a side project in crypto mining evolved into a platform that enables some of the world’s largest power users to turn energy flexibility into a strategic, revenue-generating advantage.
You’ll discover how OBM evolved from a small, side Bitcoin mining project into a global energy-flexibility software platform. Dan explains how frustrating, late-night trips to reboot miners pushed him and his co-founder Jake to build remote management tools that eventually grew into an enterprise-grade platform. You’ll also trace OBM’s journey from serving Reddit hobbyists to landing one of the world’s largest publicly traded Bitcoin miners as a customer, validating the product and accelerating growth.
You’ll understand why data centers themselves aren’t the core problem for the grid -- and how inflexible loads actually create much of the strain. Dan examines how crypto mining and generative AI workloads are converging around similar power, infrastructure, and siting challenges. You’ll learn to differentiate between traditional, flat-load data centers and “AI factories” with spiky, bursty power profiles, and analyze how colocating Bitcoin miners with AI workloads can flatten overall load profiles to better support grid stability.
You’ll evaluate the pros and cons of multiple deployment models, from fully self-owned sites to hosting arrangements and “powered land plus shell” developments for hyperscalers. Dan shows why leading operators now treat energy costs as a dynamic revenue lever rather than just a fixed operating expense. You’ll investigate how behind-the-meter projects at wind assets can turn otherwise unprofitable or curtailed generation into profitable, highly flexible loads, and assess how ERCOT’s controllable load resource (CLR) model is pioneering new ways to manage pricing, reliability, and flexibility.
You’ll see how “pauseless” AI curtailment can dramatically reduce GPU power consumption—often by 75–80%—without fully stopping training jobs or forcing constant checkpointing. Dan helps you identify the growing regulatory and public-relations pressures that are pushing AI data centers toward more flexible energy use, especially as they face criticism similar to what crypto miners have experienced. You’ll connect the dots between Bitcoin miners’ margin pressures and the emerging strategies AI operators can use to control energy risk and remain competitive as markets mature.
You’ll appreciate the real-world job creation and community revitalization that can happen when new digital infrastructure reuses stranded industrial power assets. Dan pinpoints the skills gap many organizations have around understanding grids, energy markets, and demand response—even among sophisticated data center and crypto teams. You’ll learn practical ways newcomers can self-educate on the power grid through newsletters, webinars, podcasts, and industry content instead of waiting for academia to catch up. You’ll also observe how leading operators are reframing their narrative for regulators, utilities, activists, and local communities to proactively shape the conversation.
You’ll contrast European data center models that lean heavily into heat reuse—warming buildings, pools, or greenhouses—with U.S. approaches that are far more driven by pure power-cost economics. Finally, you’ll envision a future where the most competitive data centers and AI factories win not just on uptime and scale, but by embracing deep automation, load flexibility, and creative byproduct use across multiple industries.
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