A：The 'agent take control plane' refers to the governance layer in Snowflake's services where intent becomes action, grounded in a customer's enterprise data, business context, models, applications, and security policies. It is designed to help business users and developers to efficiently carry out their tasks without leaving Snowflake's platform.

A：The adoption of Snowflake intelligence has more than doubled quarter over quarter, as more organizations adopt a governed, conversational way for business users to engage with enterprise data. CoCo, on the other hand, is already in use across more than 7100 accounts, enabling builders to create applications, pipelines, agents, and workflows using natural language within Snowflake.

A：A partner called Lambda used Snowflake to build a Customer 360 application in five hours, integrating customer data, churn insight, recommended actions, and live dashboards. Providence, one of the largest health systems in the United States, used Snowflake Cortex to surface insights from clinical notes and patient records in seconds, and they are now building workflows directly in Snowflake to access critical information faster while maintaining privacy standards. Thompson Reuters uses Snowflake's AI-driven legal and compliance workflows to turn complex regulatory data into actionable insights quickly.

A：Snowflake is revolutionizing its global support organization operations with Snowflake intelligence and CoCo, which help in surfacing diagnostic insights and likely root causes before engineers engage. Additionally, the technology aids in faster case resolution, increased engineering productivity, and automation of workflows across various departments.

A：In Q1, Snowflake delivered over 20% more product capabilities than the previous year, showcasing both the pace of innovation and platform expansion. The company is also strengthening its go-to-market organization to support the next phase of growth, with new appointments and strategic partnerships.

A：Jonathan Beier (JB) has been named the new Chief Revenue Officer at Snowflake. He brings over a decade of experience at Snowflake, deep knowledge of the customers and platform, and a strong operational focus to drive continued growth and customer momentum.

A：The collaboration between Snowflake and AWS is significant as it is a new $6 billion multiyear agreement to accelerate enterprise AI adoption globally. This agreement comes as Snowflake surpassed $7 billion in lifetime sales in the AWS Marketplace, reflecting growing demand for AI and data workloads running on Snowflake.

A：The primary ways that Snowflake's customers experience its AI and data platform capabilities are through Snowflake Intelligence and CoCo. These platforms facilitate business users and developers to move from intent to action within a governed environment.

A：In Q1, Snowflake's product revenue grew by 34% year over year, with a significant acceleration of 400 basis points. AI is a key driving force behind this momentum, serving as a catalyst for the core data platform business. Snowflake's net new customer additions increased by 38% year over year, with 13 global 2000s added compared to 4 in the same period last year. Snowflake's AI workload has become a substantial revenue engine, with AI products like Cortex Code expanding the company's opportunity with existing customers.

A：Remaining performance obligations grew by 38% year over year in Q1, compared to 34% in the same period of the previous year. Snowflake continues to see customers favoring renewals, leading to an expectation that bookings will become increasingly weighted towards the fourth quarter.

A：Non GAAP operating margin expanded over 300 basis points year over year in Q1, reaching 12%. This performance was driven by strong revenue growth and disciplined hiring practices.

A：Snowflake added 190 employees in the quarter, with 173 joining through the Observe acquisition. Excluding Observe, organic hiring was limited to 17 people. The company signed a five-year agreement with AWS, more than doubling the prior contract, which is expected to lead to an expanded go-to-market investment and collaboration. This agreement is a significant milestone in Snowflake's partnership with AWS and is fully incorporated into the company's outlook.

A：For FY 27, Snowflake now expects product revenue of $5.84 billion, representing 31% year over year growth. In Q2, product revenue is expected to be between $1.415 and $1.42 billion, showing 30% year over year growth. The acquisition of Observe is progressing as expected and contributed less than 1 percentage point of product revenue growth in Q1. The company now expects the acquisition to add approximately 3 percentage points of revenue growth for the full year. For margins, Snowflake expects a non GAAP product gross margin of 70% for FY 27. Q2 non GAAP operating margin is expected at -5%, and the full year non GAAP operating margin guidance is increased from 11% to 12%. Non GAAP adjusted free cash flow margin guidance remains at 23%, and the full year outlook continues to include a 150 basis point headwind related to the Observe acquisition.

A：Snowflake's priorities for FY 27 include driving growth and margin expansion, and supporting ongoing excellence in the go-to-market motion. AI is transforming the company's operations internally, increasing productivity through slower hiring and more cloud spending. On the go-to-market side, the response to new offerings like Cro JB has been positive, with a proven track record of success in driving outcomes for individual customers and across the organization.

A：The upcoming investor day will be held in conjunction with Snowflake Summit in San Francisco. Interested participants can attend by emailing IR at snowflake.com. This event provides an opportunity for further discussion and engagement with the company's financial and strategic plans.

A：Coco changes the go to market model by making the team AI native and significantly impacting customers' ability to get things done faster in terms of coding transformation and migration. It allows for complex migrations to be broken down and executed methodically with the help of a migration team creating 'harnesses'. Additionally, it enables the demonstration of Snowflake's capabilities with realistic AI-powered demonstrations, thus transforming how solution engineers, sales, and account executives showcase the value of the platform.

A：'Coco' is leveraged by Snowflake's internal teams, including the support team, SRE team, and services team, with over 95% adoption, to greatly benefit their work in creating products. It also facilitates learning, as one can ask a coding agent how to perform certain tasks, receive toy examples, and rapidly iterate to create more complex examples. This self-pedagogical feature means that a new product feature in Cocoa can be utilized by services personnel the same week it is released, thus expediting project completion.

A：Snowflake anticipates that while customers may be concerned about governing the use of 'Coco' to contain spend, the value provided by the tool is likely to outweigh the need for such measures. The reasoning is that 'Coco' enables customers to accomplish tasks they couldn't before or do so much faster, which can lead to significant time and cost savings. Consequently, the investment in 'Coco' is seen as an efficient allocation of resources, especially when considering the human capital costs associated with data systems.

A：Snowflake addresses cost management at scale by implementing cost limits at the account or agent level and restricting the amount of tokens a particular user can spend. However, there are exceptions for very talented users who are deemed to be worth the cost of their token usage. This approach allows for effective scaling of services while maintaining control over expenditures.

A：Snowflake is innovating within the 'coding agent' products by building native capabilities into Snowflake itself for simpler tasks, such as summarizing Slack threads. This enables the agents to handle a variety of tasks efficiently without always relying on the latest and greatest robustness models, which in turn enhances value while keeping costs manageable as the technology continues to expand.

A：The strategy for maintaining a 75% gross margin with AI products involves offsetting any impact through other means, as mentioned with the AWS contract, and being committed to finding efficiencies to sustain that margin.

A：The launch of Cocoa impacted the company's guidance as they based it on observed behavior without prior guidance for this new product. After observing its performance for a quarter, they adjusted the guidance for the full year.

A：Snowflake plays a critical role in providing the gold layer of data for a company, which is highly valuable for AI. It contains important information like revenue and consumption details, and the dashboarding platforms built on Snowflake enhance the context for AI. Snowflake's ability to provide context to AI is exceptional and the company is busy creating products to facilitate faster value from AI investments.

A：Snowflake is enhancing AI results by using metadata and activity within the platform for query optimization and performance, and is now applying similar signals to provide better context to AI. At Summit, they plan to showcase how AI results are improved with Snowflake Intelligence. Additionally, the use of these products within Snowflake helps to make the company's AI agent, Cortex, more effective over time, contributing to a flywheel effect.

A：The company is not leaning harder into the go-to-market side because AI is making their operations more efficient across various functions. This efficiency is resulting in increased effectiveness, winning more use cases, and boosting individual productivity. Investments are being made in key functions driving Snowflake forward, which includes engineering and sales, while also taking advantage of AI automation in functions like support and technical documentation.

A：The impact of Snowflake's products is that customers now expect faster delivery of data and migrations, with timelines running between a quarter and two weeks, as opposed to a two-year period. This change in expectation and the ability to deliver quickly unlock value for customers.

A：Both Snowflake Intelligence and Cortex code are built on the same underlying technology with different tools offering various capabilities to end-users. They share common components such as the Model Garden and the harness, and increasingly they will also share the same runtime.

A：Snowflake's cloud runtime product enables the same level of power that customers get from running AI products locally to be executed in the cloud in a governed manner. This allows customers to launch autonomous agents without needing to keep their laptops open, enhancing the efficiency of their operations.

A：Snowflake's unique value proposition is customer choice and independence from the mechanics of a single cloud provider. Their products work on multiple cloud platforms like AWS and Azure and provide model choice flexibility, which differentiates them from competitors.

A：Snowflake ensures governance, security, and trustworthiness with its AI products by adhering to a set of principles that includes role-based and role-level access control, data masking, and strong organizational support, among other security measures. The company also focuses on creating products that simplify governance and anomaly detection, further fortifying the trustworthiness of data and AI processes.

A：Snowflake plans to showcase new controls and policies that will simplify governance and management. These new features are expected to aid in creating a more robust and governed environment for enterprise data and AI operations.