In an uncertain world, you need a forward-thinking recruitment partner

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In an uncertain world, you need a forward-thinking recruitment partner

The energy industry is gripped by uncertainty. Market volatility, energy security, shifting geopolitics and pressure to expand into cleaner energy are forcing companies to rethink their focus. That includes planning for tomorrow’s workforce. About partnership content Some Energy Voice online content is funded by outside parties. The revenue from this helps to sustain our […]

Securing the best talent is critical. Companies can’t afford to be left behind.

Advanced technology represents the latest evolution of recruitment. Its expert use can provide faster, more reliable and broader-reaching recruitment solutions.

For employers and candidates, it pays to work with a recruitment partner at the forefront of technology, who understands the industry and retains its human touch.

How technology is transforming energy recruitment

Technology has reshaped talent acquisition. Artificial intelligence (AI) and machine learning have moved beyond traditional automation to bring measurable improvements to hiring efficiency.

For recruitment companies, these technologies open up the world of talent globally. It means they can access the best people, from contingent workers to executives, regardless of where they are.

This article explores how AI specifically is revolutionising energy recruitment.

Advanced algorithms can assess candidate skills, experience and compatibility, connecting with the right opportunities faster than ever before.

In some cases, that can mean cutting the recruitment cycle from weeks to days or even minutes.

Everybody wants the best people. Being ahead of the competition in the race to secure top talent can be a key boost to your recruitment strategy.

JAB Recruitment leads the technology advance in talent acquisition. It has integrated technologies like artificial intelligence (AI), machine learning (ML) and digital platforms to build the most comprehensive talent pool around.

In an industry where speed and accuracy are essential, JAB Recruitment’s data-driven approach delivers the certainty you need to push ahead with confidence.

Improving contingent workforce management

JAB’s unique mobile app, powered by Moblyze, is an advanced digital platform that enhances contingent workforce management. It matches the right talent to the right opportunities in real-time.

Designed to optimise engagement and streamline placements, it has significantly improved time-to-hire by automating key hiring processes. It improves the user experience and data-driven decision-making, ensuring better engagement for candidates and clients while helping companies anticipate workforce needs.

In one instance, a subsea construction and installation client in the North Sea published a vacancy for an ROV Pilot Technician in the app and filled the role within just five minutes after multiple qualified candidates swiped right.

Traditionally, it would take around one hour to fill this type of role. On average, the response rate to vacancies posted in the JAB app is up 50% on traditional website applications, while the ‘swipe right’ feature has delivered a 5x increase in response speed.

Time to embrace your potential

A historical reliance on traditional hiring techniques has created a gap between early adopters and those reluctant to change.

However, as the demand for talent grows, companies that fail to integrate advanced technology into their strategic workforce planning risk falling behind.

The way ahead

Integrating advanced technology into recruitment planning is just the first step.

Over the next decade, an explosion in real-time talent matching is expected where jobs will find candidates, not the other way round.

An acceleration in predictive workforce planning is also anticipated, with advanced insights empowering companies to accurately assess staffing requirements months or even years away.

A trusted partner

The energy industry has always been about ambition, enthusiasm and adaptation. That should include recruitment planning, too.

In an uncertain market, a forward-thinking recruitment partner can provide clarity and certainty. By integrating advanced technology with 20 years of industry expertise, JAB Recruitment ensures that clients are always the first to know.

Are you ready to seize your future?

Find out more from Jab Recruitment. Or download the JAB App via the Apple Store or Google Play.

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Stay ahead with more perspectives on cutting-edge power, infrastructure, energy, bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

IBM X-Force: Stealthy attacks on the rise, toolkits targeting AI emerge

Last year, X-Force predicted that once AI technologies “establish market dominance—when a single technology approaches 50% market share or when the market consolidates to three or fewer technologies—attackers will be incentivized to invest in attack toolkits” that target AI models and solutions. “Are we there yet? Not quite, but adoption

VMware (quietly) brings back its free ESXi hypervisor

By many accounts, Broadcom’s handling of the VMware acquisition was clumsy and caused many enterprises to reevaluate their relationship with the vendor The move to subscription models was tilted in favor of larger customers and longer, three-year licenses. Because the string of bad publicity and VMware’s competitors pounced, offering migration

CoreWeave offers cloud-based Grace Blackwell GPUs for AI training

Cloud services provider CoreWeave has announced it is offering Nvidia’s GB200 NVL72 systems, otherwise known as “Grace Blackwell,” to customers looking to do intensive AI training. CoreWeave said its portfolio of cloud services are optimized for the GB200 NVL72, including CoreWeave’s Kubernetes Service, Slurm on Kubernetes (SUNK), Mission Control, and

Kyndryl launches private cloud services for enterprise AI deployments

Kyndryl’s AI Private Cloud environment includes services and capabilities around containerization, data science tools, and microservices to deploy and manage AI applications on the private cloud. The service supports AI data foundations and MLOps/LLMOps services, letting customers manage their AI data pipelines and machine learning operation, Kyndryl stated. These tools facilitate

Trump administration moves to curb energy regulation; BLM nominee stands down

The Trump administration issued two policy directives Apr. 10 to curb energy regulations, the same day the president’s choice to lead the Bureau of Land Management (BLM) pulled her nomination. Kathleen Sgamma, former head of Western Energy Alliance (WEA), an oil and gas trade association, withdrew her nomination after a memo was leaked on X that included critical remarks following the Jan. 6, 2021, attack on the US Capitol. In the memo to WEA executives, Sgamma said she was “disgusted” by Trump “spreading misinformation” on Jan. 6 and “dishonoring the vote of the people.” The Senate was to conduct a confirmation hearing Apr. 10. Prior to her withdrawal, industry had praised the choice of Sgamma to head the agency that determines the rules for oil and gas operations on federal lands. Deregulation On the deregulation front, the Interior Department said it would no longer require BLM to prepare environmental impact statements (EIS) for about 3,244 oil and gas leases in seven western states. The move comes in response to two executive orders by President Donald Trump in January to increase US oil and gas production “by reducing regulatory barriers for oil and gas companies” and expediting development permits, Interior noted (OGJ Online, Jan. 21, 2025). Under the policy, BLM would no longer have to prepare an EIS for oil and gas leasing decisions on about 3.5 million acres across Colorado, New Mexico, North Dakota, South Dakota, Utah, and Wyoming. BLM currently manages over 23 million acres of federal land leased for oil and gas development. The agency said it will look for ways to comply with the National Environmental Policy Act (NEPA), a 1970 law that requires federal agencies to assess the potential environmental impacts of their proposed actions. In recent years, courts have increasingly delayed lease sales and projects,

Viva Energy’s ULSG project at Geelong refinery to startup by yearend

In its 2024 annual report, Viva Energy confirmed it will complete the project at a final cost of $350 million (Aus.), $200 million of which is dedicated to Australian procurement and construction contracts mostly awarded to businesses in the Geelong region. The budget increase follows the federal government’s December 2023 announcement that fuel quality and noxious vehicle emissions standards would come into effect from December 2025 to ensure Australia’s fuel quality aligns more closely with international standards. In compliance with the regulatory timeline, Viva Energy confirmed expanding the ULSG project to certify that—in addition to all of Geelong’s ULSG conforms to 10 ppm sulfur content—aromatics limits of the refinery’s RON95 mid-grade gasoline production conforms to the pending legislation’s stricter requirement of less than 35%. Both the ULSG and aromatics upgrades are part of Viva Energy’s ongoing transformation of the Geelong refinery into a modern energy hub that supports Australia’s energy security while also playing an important role its energy transition, the operator said. Future refining plans In its 2024 annual report, Viva Energy said it was continuing to explore options to replace crude oil with biogenic and waste feedstocks at the Geelong refinery, with potential biofeedstock and waste processing projects for the site slated for development throughout 2025. After confirming in its 2024 half-year results presentation undertaking of engineering design for infrastructure to store and co-process biogenic feedstocks at Geelong, Viva Energy said in its latest annual report that, by yearend 2024, it had completed a first investment in infrastructure to support co-processing at Geelong involving the injection of used cooking oil and soft-plastics pyrolysis oil into processing activities to produce recycled polyproylene and biopolymers. Additionally, the operator said work remained under way on the scope and phasing of co-processing biofeedstocks at the refinery to produce renewable diesel, with the

Trump FTC could revisit final conditions of two recent oil mergers

The companies petitioned the new FTC to set aside its consent orders barring Hess chief executive officer John B. Hess from Chevron’s board and Pioneer chief executive officer Scott Sheffield from Exxon’s board or offering any advisory services to the company. In a rare move, the FTC on Apr. 11 said it would seek public comments on the petition for 30 days, until May 12, after which it “will vote to determine how to resolve” the issue. A deeply divided FTC granted final approval for Exxon Mobil Corp.’s $64.5 billion purchase of Pioneer Natural Resources and Chevron Corp.’s $53 billion acquisition of Hess Corp. on Jan. 17, 2025, 3 days before Trump’s inauguration.

Insights: Developing next generation geothermal – an interview with GreenFire Energy

Venture Global begins commercial operations at Calcasieu Pass

Venture Global LNG has started commercial operations at its 10-million tonne/year (tpy) Calcasieu Pass LNG plant in Cameron Parish, La., and with startup, has commenced the sale of US LNG to its long-term customers. The move comes about 68 months from its final investment decision and 38 months after production start (OGJ Online, Aug. 21, 2019; Feb. 7, 2022). The project, consisting of mid-scale, modular liquefaction trains and process infrastructure, began exporting cargoes in March 2022 and was producing at capacity by September that same year, but contracted deliveries had not been delivered to certain long-term customers due to what Venture Global called technical problems at the plant (OGJ Online, Feb. 17, 2025). In a release Apr. 15, Venture Global said the company has overcome “significant unforeseen challenges, including a global pandemic, two hurricanes, and a force majeure event that arose due to major manufacturing issues with the facility’s power island.” Continuing, the company said the plant has undergone “a multi-year rectification and remediation of key components of the facility that underpin the redundancy features inherent in the project’s design,” and that “Calcasieu Pass is now ready to operate safely and reliably.” In February, Venture Global completed repair work on the final heat recovery steam generator in its power island and in early March it completed the final work on the third pre-treatment train, the company noted in its fourth-quarter 2024 report dated Mar 6, 2025. Arbitration ongoing In its Apr. 15 release, the company did not disclose what impact the start of the commercial operations and sale to long-term customers would have on arbitration cases against it by contract customers (OGJ Online, Oct. 16, 2024). In its fouth-quarter earnings presentation, in noting the then-anticipated commercial operations start at Calcasieu Pass of Apr. 15, the company said the various customer

Unlocking Ultra-Deepwater Heavy Crude

@import url(‘/fonts/fira_sans.css’); a { color: #134e85; } .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: “Fira Sans”, Arial, sans-serif; } body { letter-spacing: 0.025em; font-family: “Fira Sans”, Arial, sans-serif; } button, .ebm-button-wrapper { font-family: “Fira Sans”, Arial, sans-serif; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #212529 !important; border-color: #212529 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #212529 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #212529 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #212529 !important; border-color: #212529 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #212529 !important; border-color: #212529 !important; background-color: undefined !important; } © Endeavor Business Media <!–> –> Producing the world’s heaviest deepwater crudes is a complicated process that many majors walked away from—but Brava Energia stepped up. Atlanta field represents a breakthrough in ultradeepwater oil production, proving that independent operators can drive innovation in complex reservoirs. This Oil & Gas Journal supplement explores: Overcoming technical challenges to produce ultra-heavy crude from a deepwater, unconsolidated post-salt reservoir. Subsea innovations and artificial lift solutions that enable production in 1,550 m of water. Evolution from Early Production System (EPS) to Full Field Development (FFD) and key operational learnings. FPSO conversion and flow assurance strategies tailored for high-viscosity crude. A new standard in supplier collaboration: taking the steering committee concept to the next level. Dealing with partners’ turnover, a global pandemic, and a race against time—an independent operator takes on the risk to develop a deepwater field alone. What Atlanta’s development means for the future of deepwater oil production in Brazil. With exclusive insights from Brava Energia’s technical leadership, this issue delivers essential knowledge for industry professionals working in deepwater exploration, drilling, and production.

Intel sells off majority stake in its FPGA business

Altera will continue offering field-programmable gate array (FPGA) products across a wide range of use cases, including automotive, communications, data centers, embedded systems, industrial, and aerospace. “People were a bit surprised at Intel’s sale of the majority stake in Altera, but they shouldn’t have been. Lip-Bu indicated that shoring up Intel’s balance sheet was important,” said Jim McGregor, chief analyst with Tirias Research. The Altera has been in the works for a while and is a relic of past mistakes by Intel to try to acquire its way into AI, whether it was through FPGAs or other accelerators like Habana or Nervana, note Anshel Sag, principal analyst with Moor Insight and Research. “Ultimately, the 50% haircut on the valuation of Altera is unfortunate, but again is a demonstration of Intel’s past mistakes. I do believe that finishing the process of spinning it out does give Intel back some capital and narrows the company’s focus,” he said. So where did it go wrong? It wasn’t with FPGAs because AMD is making a good run of it with its Xilinx acquisition. The fault, analysts say, lies with Intel, which has a terrible track record when it comes to acquisitions. “Altera could have been a great asset to Intel, just as Xilinx has become a valuable asset to AMD. However, like most of its acquisitions, Intel did not manage Altera well,” said McGregor.

Intelligence at the edge opens up more risks: how unified SASE can solve it

In an increasingly mobile and modern workforce, smart technologies such as AI-driven edge solutions and the Internet of Things (IoT) can help enterprises improve productivity and efficiency—whether to address operational roadblocks or respond faster to market demands. However, new solutions also come with new challenges, mainly in cybersecurity. The decentralized nature of edge computing—where data is processed, transmitted, and secured closer to the source rather than in a data center—has presented new risks for businesses and their everyday operations. This shift to the edge increases the number of exposed endpoints and creates new vulnerabilities as the attack surface expands. Enterprises will need to ensure their security is watertight in today’s threat landscape if they want to reap the full benefits of smart technologies at the edge. Bypassing the limitations of traditional network security For the longest time, enterprises have relied on traditional network security approaches to protect their edge solutions. However, these methods are becoming increasingly insufficient as they typically rely on static rules and assumptions, making them inflexible and predictable for malicious actors to circumvent. While effective in centralized infrastructures like data centers, traditional network security models fall short when applied to the distributed nature of edge computing. Instead, organizations need to adopt more adaptive, decentralized, and intelligent security frameworks built with edge deployments in mind. Traditional network security typically focuses on keeping out external threats. But today’s threat landscape has evolved significantly, with threat actors leveraging AI to launch advanced attacks such as genAI-driven phishing, sophisticated social engineering attacks, and malicious GPTs. Combined with the lack of visibility with traditional network security, a cybersecurity breach could remain undetected until it’s too late, resulting in consequences extending far beyond IT infrastructures. Next generation of enterprise security with SASE As organizations look into implementing new technologies to spearhead their business, they

Keysight tools tackle data center deployment efficiency

Test and performance measurement vendor Keysight Technologies has developed Keysight Artificial Intelligence (KAI) to identify performance inhibitors affecting large GPU deployments. It emulates workload profiles, rather than using actual resources, to pinpoint performance bottlenecks. Scaling AI data centers requires testing throughout the design and build process – every chip, cable, interconnect, switch, server, and GPU needs to be validated, Keysight says. From the physical layer through the application layer, KAI is designed to identify weak links that degrade the performance of AI data centers, and it validates and optimizes system-level performance for optimal scaling and throughput. AI providers, semiconductor fabricators, and network equipment manufacturers can use KAI to accelerate design, development, deployment, and operations by pinpointing performance issues before deploying in production.

U.S. Advances AI Data Center Push with RFI for Infrastructure on DOE Lands

ORNL is also the home of the Center for Artificial Intelligence Security Research (CAISER), which Edmon Begoli, CAISER founding director, described as being in place to build the security necessary by defining a new field of AI research targeted at fighting future AI security risks. Also, at the end of 2024, Google partner Kairos Power started construction of their Hermes demonstration SMR in Oak Ridge. Hermes is a high-temperature gas-cooled reactor (HTGR) that uses triso-fueled pebbles and a molten fluoride salt coolant (specifically Flibe, a mix of lithium fluoride and beryllium fluoride). This demonstration reactor is expected to be online by 2027, with a production level system becoming available in the 2030 timeframe. Also located in a remote area of Oak Ridge is the Tennessee Valley Clinch River project, where the TVA announced a signed agreement with GE-Hitachi to plan and license a BWRX-300 small modular reactor (SMR). On Integrating AI and Energy Production The foregoing are just examples of ongoing projects at the sites named by the DOE’s RFI. Presuming that additional industry power, utility, and data center providers get on board with these locations, any of the 16 could be the future home of AI data centers and on-site power generation. The RFI marks a pivotal step in the U.S. government’s strategy to solidify its global dominance in AI development and energy innovation. By leveraging the vast resources and infrastructure of its national labs and research sites, the DOE is positioning the country to meet the enormous power and security demands of next-generation AI technologies. The selected locations, already home to critical energy research and cutting-edge supercomputing, present a compelling opportunity for industry stakeholders to collaborate on building integrated, sustainable AI data centers with dedicated energy production capabilities. With projects like Oak Ridge’s pioneering SMRs and advanced AI security

Generac Sharpens Focus on Data Center Power with Scalable Diesel and Natural Gas Generators

In a digital economy defined by constant uptime and explosive compute demand, power reliability is more than a design criterion—it’s a strategic imperative. In response to such demand, Generac Power Systems, a company long associated with residential backup and industrial emergency power, is making an assertive move into the heart of the digital infrastructure sector with a new portfolio of high-capacity generators engineered for the data center market. Unveiled this week, Generac’s new lineup includes five generators ranging from 2.25 MW to 3.25 MW. These units are available in both diesel and natural gas configurations, and form part of a broader suite of multi-asset energy systems tailored to hyperscale, colocation, enterprise, and edge environments. The product introductions expand Generac’s commercial and industrial capabilities, building on decades of experience with mission-critical power in hospitals, telecom, and manufacturing, now optimized for the scale and complexity of modern data centers. “Coupled with our expertise in designing generators specific to a wide variety of industries and uses, this new line of generators is designed to meet the most rigorous standards for performance, packaging, and after-treatment specific to the data center market,” said Ricardo Navarro, SVP & GM, Global Telecom and Data Centers, Generac. Engineering for the Demands of Digital Infrastructure Each of the five new generators is designed for seamless integration into complex energy ecosystems. Generac is emphasizing modularity, emissions compliance, and high-ambient operability as central to the offering, reflecting a deep understanding of the real-world challenges facing data center operators today. The systems are built around the Baudouin M55 engine platform, which is engineered for fast transient response and high operating temperatures—key for data center loads that swing sharply under AI and cloud workloads. The M55’s high-pressure common rail fuel system supports low NOx emissions and Tier 4 readiness, aligning with the most

CoolIT and Accelsius Push Data Center Liquid Cooling Limits Amid Soaring Rack Densities

The CHx1500’s construction reflects CoolIT’s 24 years of DLC experience, using stainless-steel piping and high-grade wetted materials to meet the rigors of enterprise and hyperscale data centers. It’s also designed to scale: not just for today’s most power-hungry processors, but for future platforms expected to surpass today’s limits. Now available for global orders, CoolIT is offering full lifecycle support in over 75 countries, including system design, installation, CDU-to-server certification, and maintenance services—critical ingredients as liquid cooling shifts from high-performance niche to a requirement for AI infrastructure at scale. Capex Follows Thermals: Dell’Oro Forecast Signals Surge In Cooling and Rack Power Infrastructure Between Accelsius and CoolIT, the message is clear: direct liquid cooling is stepping into its maturity phase, with products engineered not just for performance, but for mass deployment. Still, technology alone doesn’t determine the pace of adoption. The surge in thermal innovation from Accelsius and CoolIT isn’t happening in a vacuum. As the capital demands of AI infrastructure rise, the industry is turning a sharper eye toward how data center operators account for, prioritize, and report their AI-driven investments. To wit: According to new market data from Dell’Oro Group, the transition toward high-power, high-density AI racks is now translating into long-term investment shifts across the data center physical layer. Dell’Oro has raised its forecast for the Data Center Physical Infrastructure (DCPI) market, predicting a 14% CAGR through 2029, with total revenue reaching $61 billion. That revision stems from stronger-than-expected 2024 results, particularly in the adoption of accelerated computing by both Tier 1 and Tier 2 cloud service providers. The research firm cited three catalysts for the upward adjustment: Accelerated server shipments outpaced expectations. Demand for high-power infrastructure is spreading to smaller hyperscalers and regional clouds. Governments and Tier 1 telecoms are joining the buildout effort, reinforcing AI as a

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

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs). In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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

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

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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