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Saudis Cut Main Oil Price to 5-Year Low

Saudi Arabia cut the price of its flagship crude grade to the lowest level in five years, amid persistent signs of a surplus in global oil markets. State producer Saudi Aramco will reduce the price of its Arab Light grade for Asian customers to a 60-cent premium to the regional benchmark for January, according to […]

Saudi Arabia cut the price of its flagship crude grade to the lowest level in five years, amid persistent signs of a surplus in global oil markets.

State producer Saudi Aramco will reduce the price of its Arab Light grade for Asian customers to a 60-cent premium to the regional benchmark for January, according to a price list seen by Bloomberg. It’s the lowest since January 2021 and a drop that was largely in-line with a survey of refiners and traders.

The Organization of the Petroleum Exporting Countries and its allies affirmed over the weekend a previous decision to pause production increases in the first quarter of next year, citing a period of weaker seasonal demand during winter months across much of Asia, Europe and North America.

Crude prices are down about 16% this year as booming supply from the Americas, in tandem with hikes from the OPEC+ grouping itself, exceeded subdued demand growth. The International Energy Agency has predicted a record glut in 2026, while Wall Street banks including Goldman Sachs Group Inc. see futures heading lower. 

Aramco cut all of its prices to Asian buyers, with its Arab Medium crude flipping to a discount for the first time since late-2020.

Global benchmark Brent futures erased an earlier gain to trade little changed after the prices were released.



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Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

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OPEC Receives Updated Compensation Plans

A statement posted on OPEC’s website this week announced that the OPEC Secretariat has received updated compensation plans from Iraq, the United Arab Emirates (UAE), Kazakhstan, and Oman. A table accompanying this statement showed that these compensation plans amount to a total of 221,000 barrels per day in November, 272,000

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LogicMonitor closes Catchpoint buy, targets AI observability

The acquisition combines LogicMonitor’s observability platform with Catchpoint’s internet-level intelligence, which monitors performance from thousands of global vantage points. Once integrated, Catchpoint’s synthetic monitoring, network data, and real-user monitoring will feed directly into Edwin AI, LogicMonitor’s intelligence engine. The goal is to let enterprise customers shift from reactive alerting to

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Akamai acquires Fermyon for edge computing as WebAssembly comes of age

Spin handles compilation from source to WebAssembly bytecode and manages execution on target platforms. The runtime abstracts the underlying technology while preserving WebAssembly’s performance and security characteristics. This bet on WebAssembly standards has paid off as the technology matured.  WebAssembly has evolved significantly beyond its initial browser-focused design to support

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Winners and losers in the latest Top500 supercomputer list

Winner: Slingshot-11 Slingshot-11 is a 200G proprietary interconnect developed by HPE and its Cray supercomputer subsidiary. As the number of Cray systems increases on the list, so goes the number of Slingshot-11 based systems. The total number of Slingshot-11 systems jumped from 37 and 2024 to 52 this year. Loser:

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Saudis Cut Main Oil Price to 5-Year Low

Saudi Arabia cut the price of its flagship crude grade to the lowest level in five years, amid persistent signs of a surplus in global oil markets. State producer Saudi Aramco will reduce the price of its Arab Light grade for Asian customers to a 60-cent premium to the regional benchmark for January, according to a price list seen by Bloomberg. It’s the lowest since January 2021 and a drop that was largely in-line with a survey of refiners and traders. The Organization of the Petroleum Exporting Countries and its allies affirmed over the weekend a previous decision to pause production increases in the first quarter of next year, citing a period of weaker seasonal demand during winter months across much of Asia, Europe and North America. Crude prices are down about 16% this year as booming supply from the Americas, in tandem with hikes from the OPEC+ grouping itself, exceeded subdued demand growth. The International Energy Agency has predicted a record glut in 2026, while Wall Street banks including Goldman Sachs Group Inc. see futures heading lower.  Aramco cut all of its prices to Asian buyers, with its Arab Medium crude flipping to a discount for the first time since late-2020. Global benchmark Brent futures erased an earlier gain to trade little changed after the prices were released. WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

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$5 Psychological Threshold Still a Relevant Driver for NatGas

In an EBW Analytics Group report sent to Rigzone by the EBW team on Thursday, Eli Rubin, an energy analyst at the company, outlined that the “$5.00 [per million British thermal units (MMBtu)] psychological threshold” is “still a relevant market driver” for natural gas. “The January natural gas contract traded as high as $5.039 [per MMBtu] yesterday before closing at $4.995,” Rubin said in the report. “Technicals appear supportive of further upside, physical prices strong, and very cold forecasts intact,” he added. “DTN’s forecast for Weeks 2 and 3 added another 4 gHDDs in the past 24 hours, and the Week 4 forecast highlights enduring cold risks into Christmas. If frigid late-December forecasts roll forward, it could present further tailwinds for NYMEX upside,” he continued. Rubin highlighted in the report that consensus projections for this morning’s U.S. Energy Information Administration (EIA) weekly natural gas storage report are for a 14 to 18 billion cubic foot draw. “The subsequent four EIA weeks, however, may total 218 Bcf (7.8 Bcfpd) tighter than the five-year average,” he said. “LNG remains up 5.1 Bcfpd and November production upside seems to be stalling. Our most likely storage projection for the end of March dipped below 1,600 Bcf,” he added. “While winter 2025/26 storage appears adequate, concerns over rebuilding storage next year have led the 2026 injection season contracts to add 16.3 cents since Friday – even outpacing January contract gains (+14.5 cents) week to date,” he continued. The EBW report outlined that the January natural gas contract’s Wednesday close of $4.995 per MMBtu marked a 15.5 cent, or 3.2 percent, increase from Tuesday’s close. In the report, EBW predicted a “test higher and relent” trend for the NYMEX front-month natural gas contract price over the next 7-10 days and a “volatile path higher” trend over

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Analysts See ‘5-10 Years of Decent Growth’ for Oil Demand

In a report sent to Rigzone by the Morningstar team this week, Morningstar analysts said they believe oil demand “still has five to 10 years of decent growth before plateauing in the early 2030s”. “Demand doesn’t start declining until the late 2030s,” the analysts said in the report, which is titled The Future of Oil to 2050. “We project oil demand to grow from 104 million barrels per day in 2024 to a peak of 108 million barrels per day in 2032, then decline to 96 million barrels per day in 2050,” they added. The analysts highlighted in the report that the 2050 projection represents a cumulative eight percent drop versus 2024, “or 0.3 percent annually”. The Morningstar analysts stated in the report that, as a result of their demand outlook, they’ve recently upgraded their midcycle oil price to $65 per barrel from $60. “Over 2025 to 2034, they expect Brent oil prices to average $65 per barrel in inflation-adjusted terms,” the analysts said in the report. “This is close to the current Brent price at $63 as of November 2025, and a bit below the 2015-24 average real Brent price of $76,” they added. “We use this 10-year average through 2034 as our midcycle price. By the 2040s, we project oil prices to surge over $100 per barrel in real terms,” they continued. Morningstar analysts highlighted that The Future of Oil to 2050 report is an update to the company’s 2021 report, The Future of Oil Demand. “Our bullish thesis on oil demand remains essentially unchanged from that earlier report,” the analysts added. “New in this year’s report is a price forecast through 2050, derived by combining our in-house demand view with Rystad’s supply-side projections,” they added. The analysts pointed out in the report that Morningstar’s methodology includes a

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Chevron Expects 2026 Budget To Be on Lower End of Guidance

Chevron Corp said Wednesday it expects organic capital spending for consolidated subsidiaries to be $18-19 billion next year, at the lower end of its annual capex guidance of $18-21 billion through 2030. On investor day on November 12 Chevron set a “structural cost reductions” goal of $3-4 billion by the end of 2026. It expects the United States to account for $10.5 billion of next year’s projected capex, more than half of the total figure. “Nearly $6 billion is expected for U.S. shale and tight assets that include Permian, DJ and Bakken, underpinning anticipated U.S. production of more than two million barrels of oil equivalent per day”, Chevron said in an online statement Wednesday. U.S. upstream capex is projected to be $8.9-9.2 billion. “Spend related to the power business [is] expected to be primarily incorporated into U.S. upstream segment, pending final commercial agreements”, Chevron noted. “Global offshore capex is expected to be approximately $7 billion, primarily supporting growth in Guyana, Eastern Mediterranean and Gulf of America”, it said. Upstream capex for 2026 is pegged at $17 billion. “Included in upstream spend is about $0.4 billion in capitalized interest, primarily related to Guyana assets”, Chevron said. On September 23 operator Exxon Mobil Corp announced a positive final investment decision on the Hammerhead field in the Stabroek block offshore Guyana after receiving regulatory approvals, earmarking $6.8 billion for the 150,000 barrels per day (bpd) development. Hammerhead represents the first project approved in Stabroek with Chevron as a partner. ExxonMobil and China National Offshore Oil Corp had tried to prevent Chevron’s entry into Stabroek by initiating arbitration, asserting their preemption rights. Preemption would have prevented Hess Corp from selling its stake to Chevron as part of Chevron’s acquisition of Hess. The arbitration ruling favored Chevron, as confirmed separately by Chevron and ExxonMobil in July.

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Macquarie Places 20-Year Order from Texas LNG

Macquarie Energy LLC, part of trading and financial services multinational Macquarie Group Ltd, has signed a definitive agreement to buy 0.5 million metric tons per annum (MMtpa) of liquefied natural gas (LNG) for 20 years from Glenfarne Group LLC’s Texas LNG project. “This agreement, along with the three previously announced Texas LNG offtake agreements, brings Texas LNG one step closer to a final investment decision”, said a joint statement Wednesday. Earlier this year Glenfarne secured a 20-year contract to supply 0.5 MMtpa of LNG to Gunvor Group Ltd from Texas LNG. Supply under the agreement, which converted a heads-of-agreement document announced last year, will be delivered to the commodities trader’s Singapore subsidiary on a free-on-board basis, said a joint statement September 10. Last year Glenfarne signed with EQT Corp a 20-year tolling agreement for natural gas liquefaction services for two MMtpa of LNG from Texas LNG. “The agreement solidifies the two heads of agreement signed by Texas LNG and EQT” earlier in 2024, Glenfarne said in a press release July 23, 2024. In August the Federal Energy Regulatory Commission (FERC) upheld its approval for Texas LNG, acting on a second court remand. FERC also granted Glenfarne’s request to extend the deadline for the start of operations from November 2024 to November 2029. In July FERC issued a final supplemental environmental impact statement for the project in response to the second remand by the Court of Appeals for the District of Columbia Circuit in August 2024. In the August 2024 order, the court vacated FERC’s authorization issued April 2023 because the Commission had not issued a supplemental environmental impact statement. In March 2025 the court modified its August 2024 order and issued a remand without vacatur. “The Commission affirms its earlier determinations that the Texas LNG Project is not inconsistent with the public interest”,

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400+ Bilfinger Workers Support Strike Action

UK union Unite announced, in a statement sent to Rigzone this week, that over 400 offshore members employed by Bilfinger UK Limited “have supported taking strike action in an escalating dispute over pensions”. “A majority of Bilfinger workers have emphatically backed strike action in a fight to secure a fairer pension deal,” Unite said in the statement. “Unite members are demanding that Bilfinger move to a gross earnings pension scheme like many other private sector and offshore companies because workers are losing out on thousands of pounds in pension contributions due to their pattern of pay being weekly,” it added. Unite noted in the statement that the majority of Bilfinger workers are enrolled in a statutory minimum workplace pension scheme “where the company pays a maximum three percent of ‘qualifying earnings’ contribution”. “The qualifying earnings income is between GBP 6,240 [$8,322] and GBP 50,270 [$67,060]. Anything above or below that does not factor in pension contributions. It means Bilfinger’s annual pension contribution is capped at GBP 1,320.90 [$1,762.10] per year irrespective of income,” Unite said. The union estimated in the statement that around GBP 2,254 [$3,006] is being lost every year in employer pension contributions when compared with a gross salary pension scheme for a worker earning GBP 59,580.36 [$79,486.58]. “If Bilfinger fails to act on the pensions issue then strikes will be called in the coming weeks”, Unite warned in the statement, which highlighted that “a number of oil and gas operators are set to be hit by any industrial action involving Bilfinger offshore members including BP, CNR, Ineos, Ithaca, and TAQA”. According to the statement, the following assets would be impacted by industrial action: Operator Asset BP Andrew BP Clair BP Clair Ridge BP ETAP BP Glen Lyon BP Mungo CNR Ninian Central CNR Ninian South CNR Tiffany

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With AI Factories, AWS aims to help enterprises scale AI while respecting data sovereignty

“The AWS AI Factory seeks to resolve the tension between cloud-native innovation velocity and sovereign control. Historically, these objectives lived in opposition. CIOs faced an unsustainable dilemma: choose between on-premises security or public cloud cost and speed benefits,” he said. “This is arguably AWS’s most significant move in the sovereign AI landscape.” On premises GPUs are already a thing AI Factories isn’t the first attempt to put cloud-managed AI accelerators in customers’ data centers. Oracle introduced Nvidia processors to its Cloud@Customer managed on-premises offering in March, while Microsoft announced last month that it will add Nvidia processors to its Azure Local service. Google Distributed Cloud also includes a GPU offering, and even AWS offers lower-powered Nvidia processors in its AWS Outposts. AWS’ AI Factories is also likely to square off against from a range of similar products, such as Nvidia’s AI Factory, Dell’s AI Factory stack, and HPE’s Private Cloud for AI — each tightly coupled with Nvidia GPUs, networking, or software, and all vying to become the default on-premises AI platform. But, said Sopko, AWS will have an advantage over rivals due to its hardware-software integration and operational maturity: “The secret sauce is the software, not the infrastructure,” he said. Omdia principal analyst Alexander Harrowell expects AWS’s AI Factories to combine the on-premises control of Outposts with the flexibility and ability to run a wider variety of services offered by AWS Local Zones, which puts small data centers close to large population centers to reduce service latency. Sopko cautioned that enterprises are likely to face high commitment costs, drawing a parallel with Oracle’s OCI Dedicated Region, one of its Cloud@Customer offerings.

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HPE loads up AI networking portfolio, strengthens Nvidia, AMD partnerships

On the hardware front, HPE is targeting the AI data center edge with a new MX router and the scale-out networking delivery with a new QFX switch. Juniper’s MX series is its flagship routing family aimed at carriers, large-scale enterprise data center and WAN customers, while the QFX line services data center customers anchoring spine/leaf networks as well as top-of-rack systems. The new 1U, 1.6Tbps MX301 multiservice edge router, available now, is aimed at bringing AI inferencing closer to the source of data generation and can be positioned in metro, mobile backhaul, and enterprise routing applications, Rahim said. It includes high-density support for 16 x 1/1025/50GbE, 10 x 100Gb and 4 x 400Gb interfaces. “The MX301 is essentially the on-ramp to provide high speed, secure connections from distributed inference cluster users, devices and agents from the edge all the way to the AI data center,” Rami said. “The requirements here are typically around high performance, but also very high logical skills and integrated security.” In the QFX arena, the new QFX5250 switch, available in 1Q 2026, is a fully liquid-cooled box aimed at tying together Nvidia Rubin and/or AMD MI400 GPUs for AI consumption across the data center. It is built on Broadcom Tomahawk 6 silicon and supports up to 102.4Tbps Ethernet bandwidth, Rahim said.  “The QFX5250 combines HPE liquid cooling technology with Juniper networking software (Junos) and integrated AIops intelligence to deliver a high-performance, power-efficient and simplified operations for next-generation AI inference,” Rami said. Partnership expansions Also key to HPE/Juniper’s AI networking plans are its partnerships with Nvidia and AMD. The company announced its relationship with Nvidia now includes HPE Juniper edge onramp and long-haul data center interconnect (DCI) support in its Nvidia AI Computing by HPE portfolio. This extension uses the MX and Junipers PTX hyperscaler routers to support high-scale, secure

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What is co-packaged optics? A solution for surging capacity in AI data center networks

When it announced its CPO-capable switches, Nvidia said they would improve resiliency by 10 times at scale compared to previous switch generations. Several factors contribute to this claim, including the fact that the optical switches require four times fewer lasers, Shainer says. Whereas the laser source was previously part of the transceiver, the optical engine is now incorporated onto the ASIC, allowing multiple optical channels to share a single laser. Additionally, in Nvidia’s implementation, the laser source is located outside of the switch. “We want to keep the ability to replace a laser source in case it has failed and needs to be replaced,” he says. “They are completely hot-swappable, so you don’t need to shut down the switch.” Nonetheless, you may often hear that when something fails in a CPO box, you need to replace the entire box. That may be true if it’s the photonics engine embedded in silicon inside the box. “But they shouldn’t fail that often. There are not a lot of moving parts in there,” Wilkinson says. While he understands the argument around failures, he doesn’t expect it to pan out as CPO gets deployed. “It’s a fallacy,” he says. There’s also a simple workaround to the resiliency issue, which hyperscalers are already talking about, Karavalas says: overbuild. “Have 10% more ports than you need or 5%,” he says. “If you lose a port because the optic goes bad, you just move it and plug it in somewhere else.” Which vendors are backing co-packaged optics? In terms of vendors that have or plan to have CPO offerings, the list is not long, unless you include various component players like TSMC. But in terms of major switch vendors, here’s a rundown: Broadcom has been making steady progress on CPO since 2021. It is now shipping “to

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Nvidia’s $2B Synopsys stake tests independence of open AI interconnect standard

But the concern for enterprise IT leaders is whether Nvidia’s financial stakes in UALink consortium members could influence the development of an open standard specifically designed to compete with Nvidia’s proprietary technology and to give enterprises more choices in the datacenter. Organizations planning major AI infrastructure investments view such open standards as critical to avoiding vendor lock-in and maintaining competitive pricing. “This does put more pressure on UALink since Intel is also a member and also took investment from Nvidia,” Sag said. UALink and Synopsys’s critical role UALink represents the industry’s most significant effort to prevent vendor lock-in for AI infrastructure. The consortium ratified its UALink 200G 1.0 Specification in April, defining an open standard for connecting up to 1,024 AI accelerators within computing pods at 200 Gbps per lane — directly competing with Nvidia’s NVLink for scale-up applications. Synopsys plays a critical role. The company joined UALink’s board in January and in December announced the industry’s first UALink design components, enabling chip designers to build UALink-compatible accelerators. Analysts flag governance concerns Gaurav Gupta, VP analyst at Gartner, acknowledged the tension. “The Nvidia-Synopsys deal does raise questions around the future of UALink as Synopsys is a key partner of the consortium and holds critical IP for UALink, which competes with Nvidia’s proprietary NVLink,” he said. Sanchit Vir Gogia, chief analyst at Greyhound Research, sees deeper structural concerns. “Synopsys is not a peripheral player in this standard; it is the primary supplier of UALink IP and a board member within the UALink Consortium,” he said. “Nvidia’s entry into Synopsys’ shareholder structure risks contaminating that neutrality.”

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Cooling crisis at CME: A wakeup call for modern infrastructure governance

Organizations should reassess redundancy However, he pointed out, “the deeper concern is that CME had a secondary data center ready to take the load, yet the failover threshold was set too high, and the activation sequence remained manually gated. The decision to wait for the cooling issue to self-correct rather than trigger the backup site immediately revealed a governance model that had not evolved to keep pace with the operational tempo of modern markets.” Thermal failures, he said, “do not unfold on the timelines assumed in traditional disaster recovery playbooks. They escalate within minutes and demand automated responses that do not depend on human certainty about whether a facility will recover in time.” Matt Kimball, VP and principal analyst at Moor Insights & Strategy, said that to some degree what happened in Aurora highlights an issue that may arise on occasion: “the communications gap that can exist between IT executives and data center operators. Think of ‘rack in versus rack out’ mindsets.” Often, he said, the operational elements of that data center environment, such as cooling, power, fire hazards, physical security, and so forth, fall outside the realm of an IT executive focused on delivering IT services to the business. “And even if they don’t fall outside the realm, these elements are certainly not a primary focus,” he noted. “This was certainly true when I was living in the IT world.” Additionally, said Kimball, “this highlights the need for organizations to reassess redundancy and resilience in a new light. Again, in IT, we tend to focus on resilience and redundancy at the app, server, and workload layers. Maybe even cluster level. But as we continue to place more and more of a premium on data, and the terms ‘business critical’ or ‘mission critical’ have real relevance, we have to zoom out

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Microsoft loses two senior AI infrastructure leaders as data center pressures mount

Microsoft did not immediately respond to a request for comment. Microsoft’s constraints Analysts say the twin departures mark a significant setback for Microsoft at a critical moment in the AI data center race, with pressure mounting from both OpenAI’s model demands and Google’s infrastructure scale. “Losing some of the best professionals working on this challenge could set Microsoft back,” said Neil Shah, partner and co-founder at Counterpoint Research. “Solving the energy wall is not trivial, and there may have been friction or strategic differences that contributed to their decision to move on, especially if they saw an opportunity to make a broader impact and do so more lucratively at a company like Nvidia.” Even so, Microsoft has the depth and ecosystem strength to continue doubling down on AI data centers, said Prabhu Ram, VP for industry research at Cybermedia Research. According to Sanchit Gogia, chief analyst at Greyhound Research, the departures come at a sensitive moment because Microsoft is trying to expand its AI infrastructure faster than physical constraints allow. “The executives who have left were central to GPU cluster design, data center engineering, energy procurement, and the experimental power and cooling approaches Microsoft has been pursuing to support dense AI workloads,” Gogia said. “Their exit coincides with pressures the company has already acknowledged publicly. GPUs are arriving faster than the company can energize the facilities that will house them, and power availability has overtaken chip availability as the real bottleneck.”

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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.

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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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