The modern customer has just one need that matters: Getting the thing they want when they want it. The old standard RAG model embed+retrieve+LLM misunderstands intent, overloads context and misses freshness, repeatedly sending customers down the wrong paths. Instead, intent-first architecture uses a lightweight language model to parse the query for intent and context, before delivering to the most relevant content sources (documents, APIs, people).Enterprise AI is a speeding train headed for a cliff. Organizations are deploying LLM-powered search applications at a record pace, while a fundamental architectural issue is setting most up for failure.A recent Coveo study revealed that 72% of enterprise search queries fail to deliver meaningful results on the first attempt, while Gartner also p [...]
Microsoft assigned CVE-2026-21520, a CVSS 7.5 indirect prompt injection vulnerability, to Copilot Studio. Capsule Security discovered the flaw, coordinated disclosure with Microsoft, and the patch was [...]
For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as [...]
A rogue AI agent at Meta took action without approval and exposed sensitive company and user data to employees who were not authorized to access it. Meta confirmed the incident to The Information on M [...]
Most discussions about vibe coding usually position generative AI as a backup singer rather than the frontman: Helpful as a performer to jump-start ideas, sketch early code structures and explore new [...]
Last week, one of our product managers (PMs) built and shipped a feature. Not spec'd it. Not filed a ticket for it. Built it, tested it, and shipped it to production. In a day.A few days earlier, [...]