If you have built an LLM application beyond a demo, you have probably had a moment where retrieval became the weak link. Early on, traditional retrieval augmented generation feels almost magical. You embed your documents, wire up a vector database, and suddenly the model can answer questions it was never trained on. For a while, that works surprisingly well. Problems usually start once the system grows ...

Enterprises are racing to adopt agentic AI. These systems promise to automate workflows, make decisions at speed, and unlock efficiencies humans can only imagine. But as organizations integrate AI agents into their applications, one question is often overlooked: how safe are the APIs that connect these agents to the rest of the business? ...

AI investment is growing 52% year-over-year, yet progress is bumpy given data challenges and a skills gap that is holding businesses back. While developers are excited about the next model release, the reality is 99% of enterprises face AI project disruptions that are often not related to model choices that organizations often stress over. AI innovation hype is outpacing enterprise readiness, leaving developers with a tough choice: move fast on AI and risk failure, or move cautiously and watch competitors pull ahead. But what if there's a third option — one that requires no compromise? ...

In late July, the White House published "America's AI Action Plan," a 28-page document outlining the administration's goals for the creation and use of artificial intelligence in the United States ... This plan is not a comprehensive prescription for a set of practices, so why worry about it now? Many of the recommendations in this document will be the basis for regulation and legislation over the next 12-to-18 months ...

As organizations deploy increasingly sophisticated Artificial Intelligent (AI) agents and autonomous systems, a critical architectural challenge is emerging: the need to seamlessly handle both continuous data streams and separate task execution within the same infrastructure ...

Gartner Inc. predicts that organizations will develop 80% of Generative AI (GenAI) business applications on their existing data management platforms by 2028 ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

The idea of embedding security into DevOps isn't new, and it's fair to say it's never been fully realized, but API security presents a particular challenge for DevOps that requires consideration ... Wallarm recently completed our annual API ThreatStats report for 2025. The findings reveal a sharp increase in both AI and API-related vulnerabilities ...

With the increased prevalence of generative AI, there's a desire to have the same ability to inspect the AI models. Most generative AI models are black boxes, so some vendors are using the term "open source" to set their offerings apart. But what does "open source AI" mean? There's no generally-accepted definition ...

Vultr and S&P Global Market Intelligence recently released a report titled The New Battleground: Unlocking the Power of AI Maturity/MultiModel AI. The research charts the paths mature AI organizations have taken as a guide for those still in the earlier stages.Here are a few of the key findings ...

AI's widespread adoption is predicted to accelerate the pace of workforce transformation across industries, with estimates that half of today's work activities could be automated between 2030 and 2060, a decade earlier than previous estimates. To keep pace with this growing industry, software development will be central to the efforts of many businesses ...