The Morning Download: Databricks Goes All-In On AI Agents

Good morning. Data science powerhouse Databricks is launching a set of AI agents that will make it easier for companies to extract insights from their storehouses of information.

The San Francisco-based company, which is valued at $134 billion, calls its new offering Genie One, or an “agentic co-worker” that helps business teams—from finance to marketing and sales—get answers and make decisions based on their corporate data. The WSJ Leadership Institute’s Belle Lin takes an exclusive look at where Databricks sees its future in a market that is increasingly defined by AI and AI agents.

When Databricks first launched its natural language interface Genie Spaces a few years ago, the idea was that data scientists could more easily extract insights from their data without writing complex queries, co-founder and CEO Ali Ghodsi told Belle. But the company quickly discovered that customers were sharing this capability with their marketing departments and with finance and senior executives.

"They really pushed us and said, 'Hey, this is really magical, but Databricks is not built for these departments. Can you build something that's completely simpler? You just have a very simple interface where you can just ask business questions," Ghodsi said.

That led to the creation of the new Genie agents, which aim to solve that customer need.

Pressure to keep up. Databricks was established back in 2013, well before the launch of OpenAI’s ChatGPT kicked off the modern era of AI as we know it today. For all of its size and strength, it faces pressure to keep up. Data companies such as rival Snowflake are starting to cement their place as providers of enterprise AI. In late May, Snowflake’s stock shot up following strong earnings and increased demand for its AI tools.

Like Snowflake, Databricks provides the underlying layer for storing and organizing data in the cloud. Since the start of the AI boom, data companies have said that they can help businesses make use of AI by providing the data context that the technology needs.

Growth, in a crowded market. Ghodsi said the company is generating a more-than $1.7 billion revenue run rate from its AI products. That is an increase from the over $1 billion revenue run rate the company said it was generating from its AI products last September.

The foundation of the new AI agents is a data context layer called Genie Ontology—essentially a graph of all knowledge in an organization, including data, content, apps, documents and people that is updated in real-time. Having that context leads to more accurate and faster responses from AI, as well as lower token costs, Ghodsi said.

Also on Tuesday, Databricks is announcing Genie Agents and Genie App Builder, products targeted at business users who want to vibe-code their own AI agents and applications. The company has a separate AI agent for developers called Genie Code.

With these releases, Databricks enters a crowded space of providers offering coding agents and general AI agents for knowledge work. Ghodsi said the Databricks agents are meant to be used alongside agents like Anthropic’s Claude Code, though he expects all agents to eventually be tailored for specific areas of work.

Arcade.dev raises $60 million to secure AI agents. I've been following Arcade.dev since last year, given this early stage San Francisco-based startup’s focus on one of the biggest challenges facing the future of AI agents. That's the problem of how to securely authorize models to access apps, APIs, databases and other so-called tools. The company has come up with a standardized approach to that dilemma. And in tech, the arrival of a broadly embraced standard can be a precursor to growth and adoption.

Arcade told me it has raised $60 million as it tackles the problem of securely managing which actions AI agents are authorized to take in enterprise apps, databases and tools. SYN Ventures led the Series A funding, with participation by Morgan Stanley and Wipro.

“Verifying identity is simple, but controlling exactly what an agent can access or modify is the real hurdle,” co-founder and CEO Alex Salazar, a former product leader at Okta, told me. You can read the full column here.

Arcade’s approach underscores how tightly interwoven technology and security and compliance can be. “If the tech layer isn’t there to enforce the policy, the policy is just a document," Salazar told me.

• Those elements must be combined with a sound user experience. “Most policy is designed to say ‘no’. So even if the tech is there, people will actively try to work around it if it gets in the way,” he said. “The durable approach is to make the right thing easier than the wrong thing. To enable.”
• Salazar launched Arcade in 2024 with Chief Technology Officer Sam Partee. Their original intention was to create an agent that could detect why a server or a database wasn’t operating properly. Along the way, they separated the model, or reasoning layer, from the action layer that interacts with tools. That required managing agent authorization.

“We rolled this out and made it work, and nobody was really that excited about our agent,” Salazar said. “But anyone who knew AI really well was like, ‘Oh, my God, like, [the AI agent authorization] is really powerful.’”

The key, Salazar said, was a new consistency of the agent’s action and the ability of the agent to access sensitive systems on a user’s behalf without directly giving the agent the human user’s credentials and, implicitly, without giving them a full level of user access.

Arcade dropped the agent to focus on its AI agent authorization technology.

Arcade is closely tied to MCP, a protocol that Anthropic launched in 2025 as a standard for connecting AI models to so-called tools such as email, APIs and other systems. It also works with similar protocols such as Google’s A2A. Arcade builds MCP servers for business systems with a built-in, standardized approach to agent authorization, policy enforcement and audits.

Jay Leek, founder and managing partner of SYN Ventures, said he viewed agent authorization as “the number one biggest emerging problem in AI today.”

What is your company’s experience deploying AI agents? Tell me about it.

• SpaceX said it would acquire coding-agent startup Cursor for $60 billion, striking a massive deal days after SpaceX's own public offering valued it at more than $2 trillion. Cursor makes a coding tool that allows developers to toggle between different AI models

• China’s DeepSeek became the country’s most valuable AI startup after raising more than $7.4 billion in its first round of fundraising, the WSJ reports. Investors valued the company at more than $50 billion, people familiar with the matter said.

• Talks between Anthropic and Trump administration officials continued Monday without a deal to resolve the security concerns that pushed the White House to restrict access to the artificial-intelligence company’s latest model, increasing urgency on both sides to find a resolution.

• A California federal judge dismissed xAI's lawsuit accusing OpenAI of stealing trade secrets, ruling that xAI failed to show OpenAI had recruited a former engineer to extract confidential information about its Grok chatbot. The judge barred xAI from continuing to pursue the case.

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Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute's new Executive Resilience series, where she's profiling America's top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here's his LinkedIn.