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With necessary infrastructure now being developed for agentic commerce, enterprises must determine how to participate in this new form of buying and selling. But it remains a fragmented Wild West, with competing payment protocols, and it's unclear what enterprises need to do to prepare. More cloud providers and AI model companies are beginning to provide the tools enterprises need to begin...
As AI, cloud, and other technology investments soar, organizations have to make investment decisions with increased speed and clarity. Practices like FinOps, IT financial management (ITFM), and strategic portfolio management (SPM) help stakeholders evaluate opportunities and trade-offs for maximum value. But they depend on unified, reliable data. And that’s often where the challenge begins.AI can...
Hybrid cloud security was built before the current era of automated, machine-based cyberattacks that take just milliseconds to execute and minutes to deliver devastating impacts to infrastructure. The architectures and tech stacks every enterprise depends on, from batch-based detection to siloed tools to 15-minute response windows, stood a better chance of defending against attackers moving at...
Enterprises are investing billions of dollars in AI agents and infrastructure to transform business processes. However, we are seeing limited success in real-world applications, often due to the inability of agents to truly understand business data, policies and processes. While we manage the integrations well with technologies like API management, model context protocol (MCP) and others, having...
As AI systems enter production, reliability and governance can’t depend on wishful thinking. Here’s how observability turns large language models (LLMs) into auditable, trustworthy enterprise systems.Why observability secures the future of enterprise AIThe enterprise race to deploy LLM systems mirrors the early days of cloud adoption. Executives love the promise; compliance demands accountability...
Agent memory remains a problem that enterprises want to fix, as agents forget some instructions or conversations the longer they run. Anthropic believes it has solved this issue for its Claude Agent SDK, developing a two-fold solution that allows an agent to work across different context windows.“The core challenge of long-running agents is that they must work in discrete sessions, and each new...
Hello, dear readers. Happy belated Thanksgiving and Black Friday!This year has felt like living inside a permanent DevDay. Every week, some lab drops a new model, a new agent framework, or a new “this changes everything” demo. It’s overwhelming. But it’s also the first year I’ve felt like AI is finally diversifying — not just one or two frontier models in the cloud, but a whole ecosystem: open...
Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks beyond well-defined problems such as math and coding. Their framework, Agent-R1, is compatible with popular RL algorithms and shows considerable improvement on reasoning tasks that require multiple...
VentureBeat recently sat down (virtually) with Itamar Golan, co-founder and CEO of Prompt Security, to chat through the GenAI security challenges organizations of all sizes face. We talked about shadow AI sprawl, the strategic decisions that led Golan to pursue building a market-leading platform versus competing on features, and a real-world incident that crystallized why protecting AI...
This weekend, Andrej Karpathy, the former director of AI at Tesla and a founding member of OpenAI, decided he wanted to read a book. But he did not want to read it alone. He wanted to read it accompanied by a committee of artificial intelligences, each offering its own perspective, critiquing the others, and eventually synthesizing a final answer under the guidance of a "Chairman."To make this...