venturebeat
The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next

The vector database category is undergoing a shift in response to the needs of agentic AI. The retrieval-augmented generation (RAG)-to-vector database pipeline doesn't cut it anymore; agentic AI requires a different approach that incorporates context. VentureBeat's Q1 2026 Pulse survey underscores this trend: Every standalone vector database is losing adoption share, while hybrid retrieval intent has tripled to 33.3%, the fastest-growing strategic position in the dataset.Vector database pioneer Pinecone recognizes this and is pivoting to meet the specific needs of agentic AI.The company today announced Nexus, which it positions as a knowledge engine rather than an improvement on retrieval. Nexus introduces a context compiler that converts raw enterprise data into persistent, tas [...]

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venturebeat
Six data shifts that will shape enterprise AI in 2026

For decades the data landscape was relatively static. Relational databases (hello, Oracle!) were the default and dominated, organizing information into familiar columns and rows.That stability eroded [...]

Match Score: 135.99

venturebeat
The retrieval rebuild: Why hybrid retrieval intent tripled as enterprise RAG programs hit the scale wall

Something shifted in enterprise RAG in Q1 2026. VB Pulse data spanning January through March tells a consistent story: the market stopped adding retrieval layers and started fixing the ones it already [...]

Match Score: 128.50

venturebeat
Most enterprises can't stop stage-three AI agent threats, VentureBeat survey finds

A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]

Match Score: 125.50

venturebeat
Nvidia's agentic AI stack is the first major platform to ship with security at launch, but governance gaps remain

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 [...]

Match Score: 115.86

venturebeat
Databricks' Instructed Retriever beats traditional RAG data retrieval by 70% — enterprise metadata was the missing link

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used a [...]

Match Score: 110.50

venturebeat
With 91% accuracy, open source Hindsight agentic memory provides 20/20 vision for AI agents stuck on failing RAG

It has become increasingly clear in 2025 that retrieval augmented generation (RAG) isn't enough to meet the growing data requirements for agentic AI.RAG emerged in the last couple of years to bec [...]

Match Score: 109.21

venturebeat
RAG precision tuning can quietly cut retrieval accuracy by 40%, putting agentic pipelines at risk

Enterprise teams that fine-tune their RAG embedding models for better precision may be unintentionally degrading the retrieval quality those pipelines depend on, according to new research from Redis.T [...]

Match Score: 104.38

venturebeat
Amazon’s OpenAI gambit signals a new phase in the cloud wars — one where exclusivity no longer applies

Amazon Web Services on Tuesday launched one of the most consequential enterprise AI plays in the company's 20-year history, simultaneously bringing OpenAI's most powerful models to its Bedro [...]

Match Score: 103.52

venturebeat
Karpathy shares 'LLM Knowledge Base' architecture that bypasses RAG with an evolving markdown library maintained by AI

AI vibe coders have yet another reason to thank Andrej Karpathy, the coiner of the term. The former Director of AI at Tesla and co-founder of OpenAI, now running his own independent AI project, recent [...]

Match Score: 99.15