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Land and Expand: The Gigawatt Credibility Test

The midsummer wave of U.S. data center development is not defined by a single market, developer or technology company. It stretches from the Georgia coast to West Texas, from the industrial Midwest to the Mississippi River. What links the projects announced since early June is not just their scale, it is the realization that scale […]

The midsummer wave of U.S. data center development is not defined by a single market, developer or technology company. It stretches from the Georgia coast to West Texas, from the industrial Midwest to the Mississippi River. What links the projects announced since early June is not just their scale, it is the realization that scale alone is not enough.

Developers are still announcing multibillion-dollar campuses and gigawatt power requirements, but the language surrounding those announcements has changed. Companies are emphasizing who will pay for new generation and transmission, how cooling systems will limit water consumption, what communities will receive beyond temporary construction employment, and when contracted customers will begin occupying capacity. In several cases, the announcement is less about acquiring land than proving that a project has become commercially and electrically credible.  As we have seen progressing through the industry, the latest announcements point toward campuses that combine compute, power, financing and community agreements in one development package.

OpenAI Goes Direct in Georgia

OpenAI, on July 22 disclosed Project Camellia, a long-term data center development in Effingham County, Georgia. OpenAI said it is designing and developing the campus itself and has contracted with Georgia Power for 3.2 gigawatts of electricity, to be delivered in phases from 2028 through 2032. The project has been reported as a roughly $20 billion investment on approximately 1,400 acres, making it one of the largest individual data center proposals currently moving through the U.S. pipeline.

Project Camellia is notable not only for its size but for OpenAI’s more direct role. The company has traditionally secured capacity through cloud providers and infrastructure partners. By taking responsibility for designing and developing the Georgia campus, OpenAI is signaling that control over power, schedule and facility design has become strategically important as AI companies compete for increasingly scarce large-scale capacity. The project remains early in development, with infrastructure, phasing, financing and operating details still to be completed.

OpenAI paired the announcement with a detailed community compact framework. It pledged to pay the full cost of infrastructure and electric service, use a closed-loop cooling system, provide $80 million in community benefits, make as much as $71 million in Codex credits available to eligible Georgia students, and commission an annual independent audit of its commitments. It also said the campus would be designed to reduce power consumption during periods of high grid demand before residential customers are affected.

The package treats community engagement as part of the infrastructure stack rather than a public-relations exercise begun after zoning approval.

Microsoft Pairs 2 Gigawatts of Capacity With Dedicated West Texas Power

Microsoft delivered another defining announcement on June 22, unveiling a new data center campus in Pecos, Texas, that would add approximately 2 gigawatts to its global capacity. The company described the project as one of the largest single capacity additions in its history and said the multibillion-dollar investment would unfold over five to seven years, supporting more than 6,000 construction jobs at peak and hundreds of permanent operating positions.

The central feature of the Pecos plan is its power arrangement. Microsoft said the campus would initially operate with a co-located natural-gas generation facility behind the meter, allowing the site to receive dedicated electricity without drawing its opening load from the existing public grid. Chevron separately announced a 20-year power agreement with Microsoft for the West Texas facility. Microsoft said it would fund the new generation and supporting infrastructure, while the power plant and campus could eventually connect to the broader regional grid.

Microsoft also emphasized water conservation. The campus is planned around closed-loop cooling that requires an initial water charge but little additional water during steady-state operation, and the company said it would use non-potable water where possible. In an arid West Texas market, those design choices are not secondary sustainability features; they are fundamental to whether the development can maintain local support.

PowerPlay AI Adds 400 Megawatts to the Abilene Power-First Corridor

The concentration of behind-the-meter development in West Texas expanded again on July 20, when PowerPlay AI announced plans for an initial 400-megawatt AI data center development in the greater Abilene area. The project is being advanced through a joint venture with an unidentified Nasdaq-listed neocloud company and is targeting delivery of its first 400 megawatts of power in 2028.

PowerPlay AI said the joint venture has completed site-feasibility work, infrastructure assessments, land assembly and property acquisition. The partners are now progressing natural-gas service agreements and completing a request-for-proposals process to select an independent power producer. The planned generation would operate behind the meter, supplying electricity directly to the data center rather than depending initially on a conventional utility interconnection.

The company has not disclosed the joint venture partner, the project’s anticipated capital cost, the precise location of the site or whether the initial 400 megawatts represents utility capacity or fully deliverable critical IT load. The announcement should therefore be viewed as an early development milestone rather than a final construction commitment. Nevertheless, PowerPlay AI said the site already benefits from installed natural-gas infrastructure, nearby fiber, assembled land and a location outside an incorporated municipality where conventional municipal zoning restrictions would not apply.

PowerPlay AI’s model also represents another variation of the emerging power-secured development platform. The company is not presenting itself solely as a data center operator. Instead, it aims to transform undeveloped land into energized, construction-ready campuses that can be leased, sold or jointly developed with hyperscalers, neocloud providers and other large computing customers.

The Abilene project joins Microsoft’s Pecos campus in demonstrating how West Texas is becoming a testing ground for gas-powered, behind-the-meter AI infrastructure. The approach may accelerate delivery, but it will also bring greater scrutiny of emissions, fuel-price exposure and the long-term relationship between privately supplied generation and the regional electric grid.

Hut 8 Turns a Texas Campus Into a Contracted Infrastructure Asset

Three days before OpenAI’s Georgia announcement, Hut 8 reported that it had fully commercialized its 1-gigawatt Beacon Point AI data center campus in Nueces County, Texas. The company signed a second 15-year lease covering 352 megawatts of IT capacity, doubling the unnamed investment-grade tenant’s commitment to 704 megawatts. Hut 8 valued the new lease at $9.8 billion over its base term and placed total base-term contract value for the campus at $19.6 billion.

Beacon Point demonstrates how AI campuses are increasingly being underwritten before delivery. Hut 8 said its contracted AI portfolio now totals 949 megawatts of IT capacity supported by 1,330 megawatts of utility capacity, with aggregate base-term contract value of $26.6 billion.

The company expects the first Phase 2 data hall at Beacon Point to be delivered in the second quarter of 2028. That timetable reinforces another pattern in the latest announcements: customers are reserving capacity years before delivery. AI infrastructure demand is being translated into long-duration leases that allow developers to finance construction, electrical equipment and site work well ahead of occupancy.

Kansas City Emerges as a Multi-Gigawatt Market

Digital Realty’s June 22 acquisition of roughly 1,440 acres at Astra Enterprise Park in De Soto, Kansas, marked another major expansion beyond the traditional primary markets. Digital Realty acquired the site for approximately $475 million in cash and common units in its operating partnership and entered into a utility agreement that could provide 600 megawatts by early 2028, rising to 2 gigawatts at full delivery.

The first phase, Astra North, is expected to cover about 280 acres and accommodate nine data center buildings totaling approximately 3 million square feet. Digital Realty estimates that the initial phase could employ more than 1,000 workers at peak construction, while the completed campus could support approximately 250 full-time jobs. The broader site includes the former Sunflower Army Ammunition Plant property, an industrial tract already undergoing redevelopment.

Amazon Builds a New Missouri Cluster and Spends Another $3 Billion in Mississippi

On June 15, Amazon announced a $10 billion data center campus in Montgomery City, Missouri. State officials said the project would create approximately 400 direct jobs, thousands of construction jobs and hundreds of millions of dollars in property-tax revenue over 25 years. Amazon also committed more than $7 million to community programs and infrastructure.

The power arrangement was again a central part of the announcement. Amazon and Ameren Missouri said the company would pay 100% of the cost of providing electric service to the campus, including the infrastructure required to connect it to the grid, without incentives or discounted electric rates. Missouri’s large-load tariff framework is designed to prevent data center costs from being shifted to residential and commercial customers.

Amazon also plans to build water infrastructure and transfer the completed system to the local water district. Its related water-efficiency program with Arable Labs is expected to help farmers reduce groundwater withdrawals by 100 million gallons annually. These commitments reflect the new competitive landscape among states: winning a hyperscale campus increasingly requires not only incentives and available land, but credible rules governing utility cost allocation and resource use.

The Missouri project follows Amazon’s Nov. 20, 2025 commitment to invest at least $3 billion in a new Warren County, Mississippi, data center campus serving AI and cloud workloads. Amazon estimated that the project would create at least 200 direct data center jobs, support more than 300 additional full-time-equivalent positions in the region and sustain thousands of construction and supply-chain jobs across the state.

The Warren County campus builds on Amazon’s previously announced $10 billion investment in two Madison County data center campuses. Together, the projects are creating a substantial Mississippi footprint supported by state development programs, regional power infrastructure and a growing construction and operations workforce. Amazon described the Warren County project as the largest private investment in the county’s history and launched a $150,000 community fund supporting STEM education and other local priorities.

The Development Boom Meets Its Limits?

The past 45 days also supplied a warning about projects that fail to maintain political and legal support. On July 2, Blackstone-owned QTS terminated its portion of the Prince William Digital Gateway project in Virginia and withdrew related filings after years of litigation and local opposition. Compass Datacenters had already exited its portion in April. The court fight centered on the county’s rezoning process and public-notice requirements.

The Digital Gateway collapse matters because it occurred in Northern Virginia, the country’s most established data center region. It demonstrates that market demand, capital and proximity to fiber cannot overcome every entitlement failure. Developers now have to treat community consent, procedural compliance and environmental review as schedule-critical inputs alongside substations, transformers and generators.

That reality explains a focus of these announcements. OpenAI’s community compact, Amazon’s ratepayer protections, Microsoft’s behind-the-meter power strategy and the long-term leases signed by Hut 8 are all responses to the same question: what makes a giant project believable?

The gigawatt era has arrived, but the projects most likely to survive it will be those that can prove, from the beginning, exactly who will power them, who will pay for them and who will benefit when they are built.

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Türkiye signs partnership deal with bp for Kirkuk oil field redevelopment

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Polish data center plans to send its waste heat to the neighbors

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The Data Center Industry’s Permission to Build

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NVIDIA’s Reported $50B Lease and the Nuclear-Powered AI Factory

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Data Center Jobs: Engineering, Construction, Commissioning, Sales, Field Service and Facility Tech Jobs Available in Major Data Center Hotspots

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Navigating Virginia’s Data Center Boom: Policy Shifts, Local Projects, and Future Challenges

Virginia’s newest high profile data center story is no longer the announcement of the next generation AI data center campus, it is now how the state is beginning to set the trend for legislative process to protect its communities while still encouraging the data center industry development. On August 3, state Senators Richard Stuart, a Republican, and Russet Perry, a Democrat, called on Gov. Abigail Spanberger to convene a special legislative session to address groundwater strain. Their request followed a state study warning that eastern Virginia’s groundwater supply is constrained and that large new industrial withdrawals may be difficult to sustain. The debate has expanded into calls for a broader pause: Senator Glen Sturtevant has asked for an immediate statewide moratorium on new data center development, while Senate President Pro Tempore Louise Lucas has said such a moratorium deserves serious consideration. Those proposals are not yet law, but they are the clearest indication that Virginia’s policy discussion has moved beyond incremental regulation. The Commonwealth spent years treating data centers primarily as an economic-development and tax-base success. It is now evaluating them simultaneously as power, water, land-use, air-quality and ratepayer issues. That shift is especially important for projects outside Northern Virginia, where developers are increasingly pursuing large sites in communities with less experience reviewing hyperscale infrastructure. The calls for a special session arrive only weeks after a significant package of data center laws and budget provisions took effect July 1. Virginia’s new budget established what the administration describes as a first-of-its-kind electricity consumption tax on data centers. The charge is 1.1 cents per kilowatt-hour, began July 1 and is capped at $600 million in annual collections, with excess revenue refunded to data center taxpayers. The compromise preserved Virginia’s sales-and-use-tax exemption for qualifying data center equipment, avoiding the abrupt repeal sought by

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Land and Expand: The Gigawatt Credibility Test

The midsummer wave of U.S. data center development is not defined by a single market, developer or technology company. It stretches from the Georgia coast to West Texas, from the industrial Midwest to the Mississippi River. What links the projects announced since early June is not just their scale, it is the realization that scale alone is not enough. Developers are still announcing multibillion-dollar campuses and gigawatt power requirements, but the language surrounding those announcements has changed. Companies are emphasizing who will pay for new generation and transmission, how cooling systems will limit water consumption, what communities will receive beyond temporary construction employment, and when contracted customers will begin occupying capacity. In several cases, the announcement is less about acquiring land than proving that a project has become commercially and electrically credible.  As we have seen progressing through the industry, the latest announcements point toward campuses that combine compute, power, financing and community agreements in one development package. OpenAI Goes Direct in Georgia OpenAI, on July 22 disclosed Project Camellia, a long-term data center development in Effingham County, Georgia. OpenAI said it is designing and developing the campus itself and has contracted with Georgia Power for 3.2 gigawatts of electricity, to be delivered in phases from 2028 through 2032. The project has been reported as a roughly $20 billion investment on approximately 1,400 acres, making it one of the largest individual data center proposals currently moving through the U.S. pipeline. Project Camellia is notable not only for its size but for OpenAI’s more direct role. The company has traditionally secured capacity through cloud providers and infrastructure partners. By taking responsibility for designing and developing the Georgia campus, OpenAI is signaling that control over power, schedule and facility design has become strategically important as AI companies compete for increasingly scarce large-scale

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Microsoft will invest $80B in AI data centers in fiscal 2025

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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