The enterprise technology ecosystem is caught in a costly cycle. Over the past two years, millions of dollars have been funneled into generative AI pilots, yet many of these initiatives stall out before ever reaching a live production environment. When a project fails, the immediate instinct of technical leadership is often to blame the model: …
The cleanup trap: Stop asking RAG to fix bad data Read More »
Intuit was an early pioneer in the usage of agentic AI, but its path to success has hardly been a straight line. At VB Transform 2026, Intuit VP of AI Nhung Ho described how the company rebuilt its agent architecture twice in the span of about four months, first moving from a fleet of specialist …
Capital One on Thursday released VulnHunter, an open-source, agentic AI security tool that scans source code for exploitable vulnerabilities, maps out how an attacker would reach them, and proposes targeted fixes — all before a single line ships to production. The tool, built internally and now available on GitHub under an Apache 2.0 license, is …
Legacy infrastructure, not the models themselves, is what’s actually slowing AI agents down. That was the shared conclusion of three infrastructure leaders — from LinkedIn, Walmart, and Zendesk — at VB Transform 2026. The panel brought together Animesh Singh, senior director of AI platform and infrastructure at LinkedIn, Desiree Gosby, SVP of corporate technology services …
OpenClaw has become one of the most widely adopted agentic frameworks, but it has yet to prove itself at enterprise scale. Agents need real credentials — API keys, OAuth tokens, service accounts — to work effectively, and Brex found that traditional guardrails couldn’t contain what those agents were doing with them. Brex set out to …
Moonshot AI, the Beijing-based artificial intelligence startup backed by Alibaba, on Thursday released Kimi K3 — a 2.8-trillion-parameter model that the company says is now the largest open-source AI model in the world, and one that benchmarks show performs neck-and-neck with the most powerful proprietary systems from Anthropic and OpenAI. The release, timed to land …
Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and …
Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model-provider APIs, yet the next dollar is aimed at specialized compute almost none of them use today; a majority intend to switch or add …
Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce …
Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that evaluations do …