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Announcing our 2025 VB Transform Innovation Showcase finalists

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more This year’s VB Innovation Showcase finalists will be at VB Transform, June 24-25, in San Francisco. They will take to the stage as we delve into what’s actually working in enterprise AI, from copilots […]

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more


This year’s VB Innovation Showcase finalists will be at VB Transform, June 24-25, in San Francisco. They will take to the stage as we delve into what’s actually working in enterprise AI, from copilots to agents. 

Seven companies have been selected to showcase their generative AI products or features that are most likely to disrupt the enterprise.

Those selected to present will do so in front of an invite-only audience of 600 industry decision-makers, and receive direct feedback from a panel of VC judges.

The 2025 Innovation Showcase finalists are:

CTGT

Founded in 2024 by a team of Stanford and University of California, San Diego researchers, San Francisco-based CTGT is an AI risk management platform designed to change how enterprises deploy generative AI. Unlike conventional AI pipelines that require periodic offline updates, CTGT’s platform enables continuous real-time monitoring and automated refining of models in production, allowing AI systems to learn and adapt within live environments without ever going offline. This means models improve on the fly, closing the gap between development and deployment and ensuring maximum uptime and reliability for mission-critical AI applications.

The company raised a seed $7.2 million round in February.

Catio

Palo Alto-based Catio is an AI-powered platform designed to assist companies in optimizing their tech stack architecture. The platform is a copilot for technical leaders and teams, providing data-driven insights and recommendations to evaluate, plan and evolve their technology infrastructure. Catio tackles these challenges by providing continuous architecture design, strategic tech stack planning, accurate analytics and evaluation of architectures, and personalized recommendations for each enterprise’s unique needs, all powered by advanced AI models and proprietary data.

In March, Catio announced $3 million in additional funding. This is in addition to the $4 million raised between 2023-2024.

Kumo

Mountain View-based Kumo AI is focused on democratizing AI, particularly in the realm of predictive analytics, by leveraging cutting-edge Graph Neural Networks (GNNs) and Relational Deep Learning (RDL). They aim to make it easier for businesses to build and deploy highly accurate machine learning models directly from their relational data.

Kumo has raised $37 million in funding in two rounds. Their latest round was a $18 million Series B in September 2022.

Solo.io

Cambridge, Mass.-based Solo.io is a cloud-native application networking company that provides solutions for connecting, securing and observing modern applications, particularly those built on Kubernetes and microservices. Founded in 2017, Solo.io aims to simplify the complexities of application networking in dynamic, multi-cloud environments.

A $135 million series C funding round in 2021 brought the company’s total funding to $175 million. The company is valued at $1 billion.

Superduper.io

Tel Aviv-based Superduper.io is an AI company focused on simplifying the integration of AI models and workflows directly within existing databases, eliminating the need for complex data pipelines and separate AI infrastructure. Their core offering is a Python-based open-source framework that allows businesses to build and deploy custom AI applications and agents directly on their data, wherever it resides.

Superduper.io has raised $1.75 million across two seed funding rounds. Notable investors include Hetz Ventures, session.vc and MongoDB. It was also part of the Intel Ignite accelerator program.

Sutro

Oakland-based Sutro is an AI-powered no-code platform that allows users to create full, production-ready mobile and web applications simply by describing their idea in plain text. It aims to democratize software development, making it accessible to individuals and businesses without coding expertise.

Sutro was founded in 2021 and has raised around $6 million across two early funding rounds in 2023-2024.

Qdrant

Berlin-based Qdrant is a high-performance, massive-scale Vector Database and Vector Search Engine designed for the next generation of AI applications. It’s built in Rust, a language known for its safety and performance, making it a reliable choice for demanding AI workloads.

Founded in 2020, Qdrant has raised $37.8 million over three rounds of funding, the latest of which was a $28 million series A in January 2024.

Meet our Judging Panel

Emily Zhao, principal at Salesforce Ventures

Zhao is a principal at Salesforce Ventures focused on AI/ML. She also spends time on developer tooling, cybersecurity, vertical SaaS, and health tech. She joined Salesforce Ventures in the spring of 2022 and recently helped launch its $500 million generative AI fund. She has led several investments in the fund, including Hugging Face, RunwayML, Anthropic, Cohere and others.

Before joining Salesforce Ventures, Zhao was an investor at Avenir Growth Capital, a venture-growth fund based in New York, where she spent most of her time on vertical SaaS, health tech and application software. Before Avenir, Emily was an associate in the Private Equity group at Blackstone and invested in corporate buyout transactions.

Matt Kraning, partner at Menlo Ventures

Kraning is one of Menlo‘s newest partners. He is focused on investing in AI, enterprise SaaS, national defense and cybersecurity.

He’s a deeply technical former founder and a proven company builder with a Ph.D. in electrical engineering, specializing in AI and large-scale computing. Before Menlo, Kraning was the co-founder and CTO of Expanse, where he helped define the AI-driven attack surface management category. He’s also advised and invested in over 50 startups, including unicorns like Peregrine and Astranis, and recently led a $12 million round for Wispr Flow.

Rebecca Li, investment director at Amex Ventures

Li is an Investment Director at Amex Ventures. She joined in 2024 to focus on enterprise software investing, leading early-stage investments in infrastructure software, developer tools, data and AI.

Before joining American Express, Li led fintech and software venture investments at Global Asset Capital. Her prior experience includes business development and partnerships at Credit Karma and technology private equity investing at GIC.

Come see at VB Transform

All of the pitches will occur on June 25 from 4:45 to 5:30 p.m. PT. on the main stage for our in-person attendees.

Presenters will have three minutes for their pitch, followed by two minutes of feedback from the judging panel. Awards will be presented in three categories: 1) most likely to succeed, 2) coolest technology and 3) best presentation style.

Read about the winners from VB Transform 2024: SambaNovaInstabase and Tabnine.

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BW Opal FPSO Arrives at Barossa Field, Commissioning Underway

Australia’s Santos Ltd. said the BW Opal floating production, storage, and offloading (FPSO) vessel arrived at the Barossa gas field. This is a critical milestone on the path to first gas in the third quarter of 2025, Santos said in a media release, adding that the FPSO has been hooked up with final commissioning already in progress. The FPSO is the production centerpiece of Santos’ Barossa liquefied natural gas (LNG) project. Santos said it and joint venture partners SK E&S and JERA Co. Inc. have invested $3.95 billion (AUD6.07 billion at today’s rates) on the Barossa LNG project to date. “The project has come a long way since regulator acceptance of the Offshore Project Proposal in 2018. The project remains on track for first gas in the third quarter of 2025, and within the original cost guidance, which is a remarkable achievement”, Kevin Gallagher, Santos Managing Director and Chief Executive Officer, said. “Barossa is a world-class asset and, together with the Pikka phase one project in Alaska, is expected to deliver a 30 percent increase in production over the next eighteen months or so compared to 2024.  These projects will set the company up with long-term, stable cash flows to underpin compelling shareholder returns”. Furthermore, the Darwin LNG life extension (DLE) project, which will support the Barossa LNG project, is on track to be completed by the start of the third quarter of 2025, with 90 percent of the work now done, Santos said. The DLE project and its associated infrastructure have created 300 construction and maintenance jobs in Darwin, with a total investment of AUD 1 billion. Santos’ operations at Darwin LNG, which employ a 100 percent local workforce, are expected to generate around AUD100 million per year in supply and service opportunities for Northern Territory businesses, Santos said.

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Lakes Blue Energy Secures Funding for Wombat-5 Drilling

Lakes Blue Energy NL has secured AUD6.5 million to fund the proposed drilling of Wombat-5 in Petroleum Retention Lease 2 (PRL 2). The company said in a regulatory filing that it received firm commitments for a placement of 8,663,667 shares, which will also provide sufficient working capital to June 2025. According to Lakes, the placement is subject to its reinstatement to trading on the Australian Securities Exchange Ltd. (ASX). The placement will raise a total of AUD 6,497,750.25 in two tranches. The first tranche will bring in around AUD 6 million, and the second tranche is set to bring in an additional $502,500. The company added its directors intend to participate in the placement in consideration of outstanding amounts due to directors for a total of up to AUD636,024, subject to shareholder approval at its general meeting. Shares in the placement will be issued at AUD 0.75 per unit, a 25 percent discount to the last traded share price of AUD 1.00 on September 30, 2023, before suspension from quotation on October 2, 2023. Morgans Financial Ltd. acted as lead manager. “Lakes is delighted with the market’s response to our placement, and we look forward to utilizing these funds to drill Wombat 5 and hopefully developing a substantial gas field to assist Victoria alleviate its forecast gas shortages”, Roland Sleeman, Chairman of Lakes, said. The company earlier received approval from Lily D’Ambrosio MP, Victoria’s State Minister for Energy and Resources, to drill Wombat-5. Lakes said it had already secured an agreement with Condor Energy Services Ltd. for the supply of their Rig #1 for drilling the proposed lateral well, with spudding expected to start July. To contact the author, email [email protected] What do you think? We’d love to hear from you, join the conversation on the Rigzone Energy Network. The

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Energy Secretary Wright Testifies Before Senate Energy and Natural Resources Committee on FY2026 Budget Request

WASHINGTON— U.S. Secretary of Energy Chris Wright testified today before the U.S. Senate Committee on Energy and Natural Resources on the Department of Energy’s Fiscal Year 2026 budget request. Earlier this month, Secretary Wright testified before the U.S. House Energy Subcommittee to outline the department’s FY2026 request. He also appeared last month before both the U.S. Senate and U.S. House Appropriations Subcommittees on Energy and Water Development to outline department priorities and provide a comprehensive overview of the budget. The FY2026 Budget delivers on President Trump’s directive to restore American energy dominance, unleash every American energy advantage, and bring commonsense back to Washington. It returns non-defense discretionary spending to the most disciplined levels since 2017 and redirects over $15 billion away from the Green New Scam— a reckless Biden-era agenda that drives up costs, weakens reliability, and undermines U.S. energy strength. The department remains committed to being responsible stewards of American taxpayer dollars while protecting the affordable, abundant, and reliable energy our nation depends on. For more details, view the budget toplines here. Secretary Wright’s opening remarks: Thank you, Chairman Lee, Ranking Member Heinrich, and Members of the Committee, it is an honor to appear before you today as Secretary of Energy to discuss the President’s Fiscal Year 2026 Budget request for the Department of Energy. Under President Trump’s leadership, our priorities for the Department are clear—to achieve American energy dominance, bolster our national security, meet our Cold War legacy cleanup commitments and unleash historic innovation, including AI, for our nation and world. We are driven by a bedrock conviction that an affordable, reliable, secure energy supply is the foundation of a strong and prosperous nation. When America leads in energy, we lead in prosperity, security and human flourishing. We are committed to advancing our critical missions while cutting red

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Energy Department Announces New Pathway to Test Advanced Reactors

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Middle East Tensions Keep Oil Volatile

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Groups appeal DOE ‘emergency’ order keeping Michigan plant online

The Department of Energy’s May order directing Consumers Energy to delay retiring a 1,560-MW, coal-fired power plant in Michigan was illegal and based on a nonexistent emergency, Earthjustice and other groups said in a rehearing request filed on Wednesday at DOE. “The order represents an effort to replace the market- and state-led planning process provided by statute with an ill-advised and misinformed exercise in federal command-and-control,” the public interest groups said in their request that DOE rescind its decision. If DOE does not respond to the request within a required 30 days, the groups plan to challenge the 90-day emergency order in court, they said. The Federal Power Act’s section 202(c) gives the DOE secretary the authority to temporarily order power plants to operate during wars and emergencies. In a May 23 order, DOE Secretary Chris Wright said parts of the Midwest faced an “energy emergency” and that Consumers’ J.H. Campbell power plant in West Olive, Michigan, should run until Aug. 21, past its planned May 31 shutdown. DOE cited two reports in finding that an emergency exists in MISO: NERC’s 2025 Summer Reliability Assessment issued on May 14 and the grid operator’s capacity auction results released in late April. Those reports fail to show Michigan faces an emergency that requires the Campbell power plant to keep running, according to the public interest groups. MISO and the Michigan Public Service Commission have said the state and broader Midcontinent system have adequate power supplies this summer, the groups said. Also, MISO and the PSC approved retiring the Campbell power plant, and Consumers acquired replacement power supplies, they noted. “MISO has made clear time and again that the vast region over which it has balancing authority is resource adequate for summer 2025,” the groups said. “This means that MISO is not facing

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Can Intel cut its way to profit with factory layoffs?

Matt Kimball, principal analyst at Moor Insights & Strategy, said, “While I’m sure tariffs have some impact on Intel’s layoffs, this is actually pretty simple — these layoffs are largely due to the financial challenges Intel is facing in terms of declining revenues.” The move, he said, “aligns with what the company had announced some time back, to bring expenses in line with revenues. While it is painful, I am confident that Intel will be able to meet these demands, as being able to produce quality chips in a timely fashion is critical to their comeback in the market.”  Intel, said Kimball, “started its turnaround a few years back when ex-CEO Pat Gelsinger announced its five nodes in four years plan. While this was an impressive vision to articulate, its purpose was to rebuild trust with customers, and to rebuild an execution discipline. I think the company has largely succeeded, but of course the results trail a bit.” Asked if a combination of layoffs and the moving around of jobs will affect the cost of importing chips, Kimball predicted it will likely not have an impact: “Intel (like any responsible company) is extremely focused on cost and supply chain management. They have this down to a science and it is so critical to margins. Also, while I don’t have insights, I would expect Intel is employing AI and/or analytics to help drive supply chain and manufacturing optimization.” The company’s number one job, he said, “is to deliver the highest quality chips to its customers — from the client to the data center. I have every confidence it will not put this mandate at risk as it considers where/how to make the appropriate resourcing decisions. I think everybody who has been through corporate restructuring (I’ve been through too many to count)

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Intel appears stuck between ‘a rock and a hard place’

Intel, said Kimball, “started its turnaround a few years back when ex-CEO Pat Gelsinger announced its five nodes in four years plan. While this was an impressive vision to articulate, its purpose was to rebuild trust with customers, and to rebuild an execution discipline. I think the company has largely succeeded, but of course the results trail a bit.” Asked if a combination of layoffs and the moving around of jobs will affect the cost of importing chips, Kimball predicted it will likely not have an impact: “Intel (like any responsible company) is extremely focused on cost and supply chain management. They have this down to a science and it is so critical to margins. Also, while I don’t have insights, I would expect Intel is employing AI and/or analytics to help drive supply chain and manufacturing optimization.” The company’s number one job, he said, “is to deliver the highest quality chips to its customers — from the client to the data center. I have every confidence it will not put this mandate at risk as it considers where/how to make the appropriate resourcing decisions. I think everybody who has been through corporate restructuring (I’ve been through too many to count) realizes that, when planning for these, ensuring the resilience of these mission critical functions is priority one.”  Added Bickley, “trimming the workforce, delaying construction of the US fab plants, and flattening the decision structure of the organization are prudent moves meant to buy time in the hopes that their new chip designs and foundry processes attract new business.”

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Next-gen AI chips will draw 15,000W each, redefining power, cooling, and data center design

“Dublin imposed a 2023 moratorium on new data centers, Frankfurt has no new capacity expected before 2030, and Singapore has just 7.2 MW available,” said Kasthuri Jagadeesan, Research Director at Everest Group, highlighting the dire situation. Electricity: the new bottleneck in AI RoI As AI modules push infrastructure to its limits, electricity is becoming a critical driver of return on investment. “Electricity has shifted from a line item in operational overhead to the defining factor in AI project feasibility,” Gogia noted. “Electricity costs now constitute between 40–60% of total Opex in modern AI infrastructure, both cloud and on-prem.” Enterprises are now forced to rethink deployment strategies—balancing control, compliance, and location-specific power rates. Cloud hyperscalers may gain further advantage due to better PUE, renewable access, and energy procurement models. “A single 15,000-watt module running continuously can cost up to $20,000 annually in electricity alone, excluding cooling,” said Manish Rawat, analyst at TechInsights. “That cost structure forces enterprises to evaluate location, usage models, and platform efficiency like never before.” The silicon arms race meets the power ceiling AI chip innovation is hitting new milestones, but the cost of that performance is no longer just measured in dollars or FLOPS — it’s in kilowatts. The KAIST TeraLab roadmap demonstrates that power and heat are becoming dominant factors in compute system design. The geography of AI, as several experts warn, is shifting. Power-abundant regions such as the Nordics, the Midwest US, and the Gulf states are becoming magnets for data center investments. Regions with limited grid capacity face a growing risk of becoming “AI deserts.”

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Edge reality check: What we’ve learned about scaling secure, smart infrastructure

Enterprises are pushing cloud resources back to the edge after years of centralization. Even as major incumbents such as Google, Microsoft, and AWS pull more enterprise workloads into massive, centralized hyperscalers, use cases at the edge increasingly require nearby infrastructure—not a long hop to a centralized data center—to take advantage of the torrents of real-time data generated by IoT devices, sensor networks, smart vehicles, and a panoply of newly connected hardware. Not long ago, the enterprise edge was a physical one. The central data center was typically located in or very near the organization’s headquarters. When organizations sought to expand their reach, they wanted to establish secure, speedy connections to other office locations, such as branches, providing them with fast and reliable access to centralized computing resources. Vendors initially sold MPLS, WAN optimization, and SD-WAN as “branch office solutions,” after all. Lesson one: Understand your legacy before locking in your future The networking model that connects centralized cloud resources to the edge via some combination of SD-WAN, MPLS, or 4G reflects a legacy HQ-branch design. However, for use cases such as facial recognition, gaming, or video streaming, old problems are new again. Latency, middle-mile congestion, and the high cost of bandwidth all undermine these real-time edge use cases.

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Cisco capitalizes on Isovalent buy, unveils new load balancer

The customer deploys the Isovalent Load Balancer control plane via automation and configures the desired number of virtual load-balancer appliances, Graf said. “The control plane automatically deploys virtual load-balancing appliances via the virtualization or Kubernetes platform. The load-balancing layer is self-healing and supports auto-scaling, which means that I can replace unhealthy instances and scale out as needed. The load balancer supports powerful L3-L7 load balancing with enterprise capabilities,” he said. Depending on the infrastructure the load balancer is deployed into, the operator will deploy the load balancer using familiar deployment methods. In a data center, this will be done using a standard virtualization automation installation such as Terraform or Ansible. In the public cloud, the load balancer is deployed as a public cloud service. In Kubernetes and OpenShift, the load balancer is deployed as a Kubernetes Deployment/Operator, Graf said.  “In the future, the Isovalent Load Balancer will also be able to run on top of Cisco Nexus smart switches,” Graf said. “This means that the Isovalent Load Balancer can run in any environment, from data center, public cloud, to Kubernetes while providing a consistent load-balancing layer with a frictionless cloud-native developer experience.” Cisco has announced a variety of smart switches over the past couple of months on the vendor’s 4.8T capacity Silicon One chip. But the N9300, where Isovalent would run, includes a built-in programmable data processing unit (DPU) from AMD to offload complex data processing work and free up the switches for AI and large workload processing. For customers, the Isovalent Load Balancer provides consistent load balancing across infrastructure while being aligned with Kubernetes as the future for infrastructure. “A single load-balancing solution that can run in the data center, in public cloud, and modern Kubernetes environments. This removes operational complexity, lowers cost, while modernizing the load-balancing infrastructure in preparation

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Oracle’s struggle with capacity meant they made the difficult but responsible decisions

IDC President Crawford Del Prete agreed, and said that Oracle senior management made the right move, despite how difficult the situation is today. “Oracle is being incredibly responsible here. They don’t want to have a lot of idle capacity. That capacity does have a shelf life,” Del Prete said. CEO Katz “is trying to be extremely precise about how much capacity she puts on.” Del Prete said that, for the moment, Oracle’s capacity situation is unique to the company, and has not been a factor with key rivals AWS, Microsoft, and Google. During the investor call, Katz said that her team “made engineering decisions that were much different from the other hyperscalers and that were better suited to the needs of enterprise customers, resulting in lower costs to them and giving them deployment flexibility.” Oracle management certainly anticipated a flurry of orders, but Katz said that she chose to not pay for expanded capacity until she saw finalized “contracted noncancelable bookings.” She pointed to a huge capex line of $9.1 billion and said, “the vast majority of our capex investments are for revenue generating equipment that is going into data centers and not for land or buildings.”

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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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