Snowflake Summit Day 2: Is It Magic or Trusted Data Agents?

Parallels can be drawn between the Snowflake Summit 26 and 2001: A Space Odyssey, the 1968 sci-fi novel and film co-created by Sir Arthur C. Clarke. In Sir Arthur’s classic, astronauts are sent into deep space on a mysterious mission, entirely dependent on HAL 9000 – a sentient shipboard computer that makes decisions on behalf of humans.

But where HAL famously went rogue, casting its crew into the vacuum of space, Snowflake’s vision for 2026 offers a more promising outlook.

The summit’s keynotes – spread across 1 and 2 June – highlighted a new era of autonomous AI agents, but instead of operating in a black box, these agents are grounded by trusted enterprise data. It is automated decision-making built for good, designed to elevate human potential rather than maroon it.

Snowflake’s EVP of Product Christian Kleinerman leaned into this sci-fi reality by channelling Sir Arthur himself. 

“Any sufficiently advanced technology is indistinguishable from magic,” he said.

“I’ve been saying this for years because when we see a great product, it feels magical – and we all live in a time where this proves true almost every single week.”

“We love building technology to help all of you more productive and help your organisations be more successful. We do hundreds of launches every quarter and we keep picking up speed.”

Meet CoCo and CoWork

According to Christian, two Snowflake products have stood out in the last 12 months: Snowflake Cortex Code and Snowflake Intelligence. 

“They help everyone in your organisation to be more productive,” he said.

Cortex Code launched in February 2026. It is an AI-powered coding assistant built specifically for data engineers and developers working with data that translates a single prompt into production ready pipelines and apps.

It is the firm’s fastest ever growing product with more than 7,100 users, most of which affectionately nickname it as CoCo. 

Due to this, Christian announced the product will be rebranded as Snowflake CoCo. 

Additionally, Snowflake Intelligence – the conversational assistant that sits on top of company data so employees can ‘talk’ to their data, build AI agents for specific teams and ensure that data is protected without extra security set up – will now be known as Snowflake CoWork.

The new names represent how Snowflake has aligned the two products with its broader Cortex AI portfolio, including Cortex Agents that lets users build agents that retrieve, reason over and act on governed enterprise data. 

“Coco is truly changing how we think about Snowflake, the surface area and how you’re more productive and agile to get things done,” Christian said. 

Expanding Cortex AI: Anthropic and Snowflake

Enterprises are increasingly adopting Anthropic Claude in Snowflake Cortex AI. Due to this, Sridhar Ramaswamy, CEO of Snowflake, highlighted during his keynote how the two firms will work together to help customers move from AI experimentation to production faster. 

The two firms expanded their partnership in December 2025 by integrating Claude models directly into Cortex AI across all major cloud platforms. They also established a joint go-to-market strategy to deploy AI agents across customer data.

Anthropic provides the Claude model, while Snowflake integrates it directly into customers’ existing secure data and governance environments. 

Through Cortex AI, customers can securely run Claude models and deploy AI agents directly within Snowflake, ensuring sensitive data never leaves their existing environment.

Shifting into the agentic era

Also at the summit, Benoit Dageville, Co-Founder and President of Product at Snowflake, emphasised the concept of the AI Enterprise, where there’s a need for a unified platform for AI and data to be integrated with one another.

“We have now entered the era of the agentic enterprise and to survive in this new era, you really need two things: first, the foundation – AI agents must be powered by the world-best data platform,” Benoit said.

“Second, you need a unified architecture. Both AI and data must be on a single integrated platform. Building an isolated AI stack will lead to sales silos, forgetting governance, and driving up cost and complexity.”

Snowflake’s foundation principles are simple: to unify all data (structured and unstructured), decoupling compute from storage for scalability and offering a zero-maintenance, fully managed platform. 

“The art of the possible is changing,” Christian said. “I want you to know that Snowflake will help you empower everyone in your organisation to leverage AI, be more productive with the context of your company and with peace of mind.”

Inside Christian’s keynote: a four-act framework for modern data 

Christian structured his keynote like a theatrical production, dividing Snowflake’s vision and latest advancements into four distinct acts. 

Together, these acts paint a complete picture of how modern enterprises are transitioning into the era of AI. 

The journey begins with simplification. Christian’s first act focused on removing the traditional friction from data management, turning complex architectures into user-friendly systems.

A prime example of this act in action is Under Armour. Five years ago, the company transitioned its relationship with Snowflake from a transactional partnership into a deep, functional data ecosystem centred on a trusted, accessible foundational layer. 

By using Snowflake’s architecture – including hybrid and dynamic tables – Under Armour has successfully democratised its data, moving away from slow, traditional IT reporting.

Once data is simplified, the next critical hurdle is security and visibility, especially as automated tools enter the workforce. 

Under this act, Christian pointed to a new concept of agent identity – one where people can tell when activity is happening under an agent context.

“For example, in a masking policy, you can say if it is an agent context, maybe you give it less visibility or maybe you give it more, whatever you want to do, but we want to give you that control over what agents are doing,” he said.

But trust and security aren’t just internal priorities; they are essential for external partnerships. To address this, Christian also introduced multi-party collaboration, which allows multiple organisations to securely analyse and activate data in a shared environment without exposing raw PII or proprietary information.

“Multiple parties cannot collaborate in a single secure environment,” he said. “We can have different roles in a single environment be someone that contributes data or maybe someone that just does analytics. 

“This starts with our favourite technology but it has been built on the foundation of broader global collaboration.”

Christian cited Netflix as being at the forefront of this technology, having built rooms and collaborated with a number of its partners.

Meanwhile, the third act focused on openness and flexibility, ensuring that data is never trapped in vendor silos but can instead flow freely across an organisation’s tech stack.

“I think we are the only vendor that has full bidirectional support and growth between catalogues engines allowing retail right to any data whether it's managed by the horizon panel or by external catalogue,” Christian said.

Finally, the fourth act represents the ultimate destination of the data journey.

Christian used these four acts to show how Snowflake customers are using CoCo and CoWork to turn their foundational data into autonomous, intelligent workflows.

This evolution is exactly what Under Armour is executing today. In collaboration with partners like Elementum, Under Armour has launched an internal AI agent that allows teammates to quickly query data and automate workflows. 

Ultimately, this collaboration shifts Under Armour toward an agile, AI-driven environment where every employee can instantly access data-driven insights to achieve business outcomes.

Highlighting the real-world impact of this final act, Patrick Duroseau, Chief Data AI Officer at Under Armour, noted just how much the paradigm has shifted for their workforce: “Our teammates are able to talk, chat and engage with our internal AI agent [to get] answers to questions quickly on their own.

“That partnership with Elementum and Snowflake gives us the trusted data that our teammates are looking for.”