Databricks Open-Sources Omnigent: A Meta-Harness That Composes, Governs, and Shares AI Agents Across Claude Code, Codex, and Pi

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First came vector databases, then RAG. Now, the next frontier in enterprise AI is taking shape: context layers that give autonomous agents a shared understanding of the business, a vision Databricks is advancing with Genie Ontology. Currently in preview, Genie Ontology automatically extracts business context from enterprise data, dashboards, queries, pipelines, documents, and applications and organizes it into a living graph that AI agents can use to understand how an organization operates. Showcased at the company’s Data + AI Summit, Genie Ontology uses a ranking system inspired by Google’s PageRank to identify the most authoritative business definitions within an organization. Rather than treating all sources equally, it weighs factors including who created the information, how widely it is used, its links to certified datasets and assets, and how recently it was updated before determining which answer an AI agent should rely on, Databricks CEO Ali Ghodsi said during his keynote late

Databricks' rapid AI-driven growth highlights the tension between scaling innovation and maintaining profitability, impacting future investment strategies. The post Databricks sales growth tops 80% as margins shrink from AI costs appeared first on Crypto Briefing.

The report highlights AI's growing role in execution, yet underscores the enduring necessity of human expertise for strategic planning. The post Anthropic releases economic research on Claude Code usage, reveals humans still do most of the thinking appeared first on Crypto Briefing.

As enterprises rush to build AI agents that can reason over business data and take action, Databricks argues that the long-standing practice of separating operational and analytical data systems is turning into a liability. That separation, the cloud-based data warehouse provider says, is becoming increasingly strained as AI agents require simultaneous access to live operational data and historical context to make decisions and take actions in real time, unlike humans, who traditionally can work with data that is minutes or hours old. At its annual Data + AI Summit, the data warehouse provider introduced Lake Transactional and Analytical Processing (LTAP), a new architecture designed to unify transactional and analytical data on a single storage layer. The new approach, according to Databricks, differs from traditional online transaction processing (OLTP) and online analytical processing (OLAP) architectures, which typically store operational and analytical data in separate systems. Tr

PI reclaims $0.13 as buyers return. How high can it go? PI Network (PI) Price Predictions: Analysis Key support levels: $0.13 Key resistance levels: $0.16, $0.20 PI Finds a Local Bottom At the time of this post, PI appears to have found a local bottom at $0.13 and is holding well above this level. As […]

Many AI agent systems become economically unsustainable long before they become technically impressive. Teams usually focus on model choice, prompt design, tool calling, and orchestration. Those things matter, but they are only part of the system setup. The deeper issue is that coding agents, such as Claude Code, Codex, and Jules, make agent workflows easier […]

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