The scaffolding layer that developers once needed to ship LLM applications — indexing layers, query engines, retrieval pipelines, carefully orchestrated agent loops — is collapsing. And according to Jerry Liu, co-founder and CEO of LlamaIndex, that's not a problem. It's the point.“As a result, there's less of a need for frameworks to actually help users compose these deterministic workflows in a light and shallow manner,” Jerry Liu, co-founder and CEO of LlamaIndex, explains in a new VentureBeat Beyond the Pilot podcast. Context is becoming the moatLiu’s LlamaIndex is one of the foremost retrieval-augmented generation (RAG) frameworks connecting private, custom, and domain-specific data to LLMs. But even he acknowledges that these types of frameworks are becoming [...]
Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]
For the first time on a major AI platform release, security shipped at launch — not bolted on 18 months later. At Nvidia GTC this week, five security vendors announced protection for Nvidia's a [...]
An enterprise AI agent answers with total confidence, but the number is wrong. Nobody catches it until someone traces it back to a stale metric definition or a document the retrieval system never pull [...]
New VB Pulse data shows Microsoft and OpenAI leading enterprise agent orchestration, but Anthropic’s first measurable foothold points to a larger fight over who controls the infrastructure where AI [...]
Just two months ago, researchers at the Data Intelligence Lab at the University of Hong Kong introduced CLI-Anything, a new state-of-the-art tool that analyzes any repo’s source code and generates a [...]
Enterprise AI is facing an ROI paradox. While throwing more compute at the strongest foundation model works well in product experiments, the costs become unbearable when the product is deployed in pro [...]
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 sourc [...]
A company builds a governed context layer specifically to stop its AI agents from confidently giving wrong answers. Once that layer is live, the company is more than twice as likely to report the fail [...]
As enterprise AI agents take on increasingly complex, long-horizon tasks, their performance is often restricted by their harness, the software scaffolding that connects the backbone LLM to its environ [...]