A：The acquisition of Observe, a leading observability platform, integrates observability directly with data and AI products, reducing complexity and enabling faster, more reliable operations at scale, targeting the $50 billion IT operations market and positioning Snowflake to lead in next-generation AI-powered observability.

A：Efficient work is being transformed within Snowflake and across the industry with the creation of new AI-native systems on Snowflake. Snowflake Intelligence and Cortex code are resulting in faster project completion, improved response accuracy, and more efficient implementation cycles.

A：The partnership with Google Cloud allows customers to access the latest Gemini models natively within Snowflake, significantly expanding model choice and accelerating innovation.

A：Snowflake agents are used not only to analyze information but also to automate complex workflows, sometimes retiring entire categories of previously used software systems, as seen in the example of Sanofi's transition from traditional software to AI-powered workflows.

A：Snowflake is building conditions for AI safety, scalability, and enterprise readiness, including a single source of governed metrics, shared business definitions, cross-cloud and cross-domain interoperability, security, auditability, and governance.

A：Q4 financial results include year-over-year revenue growth, a strong net revenue retention rate, and increased remaining performance obligations. For FY 27, Snowflake expects product revenue growth, stability and ongoing excellence in the go-to-market motion, continued investment in growth, and margin expansion, and strong non-GAAP product gross margin and operating margin forecasts.

A：The projected growth for the company's product revenue in Q4 is 30%. For the following fiscal year, the projected sustained growth rate is around 27%.

A：The company's guidance for the upcoming fiscal year is based on high stable growth observed in the core business, the growing contribution from AI workloads, and a one percentage point growth from observed acquisitions.

A：Snowflake Intelligence is a significant driver of growth across the data life cycle with over 2,500 customers. It offers critical access to business information, reinforcing the need for enterprises to adopt Snowflake to transform their data estates. Snowflake Intelligence can process any open data, which is a powerful feature. Additionally, it enables the creation of OpenFlow pipelines for data integration and performance optimization, significantly faster than before.

A：The $400 million deal was with an existing customer, and it was already factored into the run rate. The deal signifies the importance that Snowflake delivers to large financial services customers and represents the company's maturity as a durable provider. It is a testament to the trust that customers have in Snowflake's future, underpinned by product acceleration and velocity.

A：The company has adjusted the compensation plan to include bookings, a practice that signifies a return to historical ways and is expected to continue. The latest deal reinforces the alignment between Snowflake and its customers, showing a buy-in to the company's product roadmap and AI strategy, and the positive business outcomes that Snowflake delivers.

A：Based on the feedback from the sales kickoff and the first full year with the new go-to-market strategy, the company anticipates that continued product innovation and the excitement around new offerings like Cortex Code will drive momentum. Sales teams are encouraged by positive customer feedback and the transformational impact of these products on the business.

A：Cortex Code has been transformational, with many people expressing excitement about its capabilities since its inception. The product has been instrumental in accelerating the delivery of value to customers, showcasing faster data integration, transformation, and insights generation. The overall excitement and feedback indicate that Cortex Code is a significant addition to Snowflake's portfolio.

A：Snowflake's observability tools streamline the use of data from Snowflake and are designed to address the need for AI observability, a significant market with many different areas of expertise. The tools are built on top of Snowflake and inherit its data and compute foundation. They are especially valuable for customers dealing with large volumes of data, offering efficiency gains and lower costs compared to traditional methods, thus extending the utility of the Snowflake data platform.

A：The integration of Observed into Snowflake was driven by the belief in the value that Observed could bring to a large set of customers that also use Snowflake. Both Jeremy and the Observed team wanted to be part of Snowflake due to the synergies and opportunities it presented for their tools to enhance the data platform's capabilities.

A：Snowflake aims to address potential sticker shock by offering a consumption-based model with features like per user caps on top of Snowflake intelligence, ensuring price predictability. They believe in demonstrating value from the outset, as evidenced by their sales agent that replaced a legacy system. The company is committed to innovation in this area to provide controls for wide deployments of Snowflake intelligence and has integrated Snowflake with identity providers for simpler user configuration.

A：Snowflake's vision is for every employee of every enterprise customer to have access to AI agents that provide key business details, correlated with outcomes. They aim to offer consumption-based pricing with price predictability through features like user caps. The company's goal is to be predictable and provide necessary controls for wide deployments of Snowflake intelligence, thereby avoiding sticker shock.

A：Interoperability is a core part of Snowflake's strategy. Over the past two years, they have executed flawlessly on an interoperable data strategy, supporting Iceberg as a first-class construct within Snowflake and managing rights to block storage. Snowflake focuses on offering interoperability at every layer of the stack, from storage to SQL queries and semantic models, while also providing world-class products that simplify the use of these interoperability features.

A：The 9.8 billion RPO growth of 40% is attributed to a big contract in the quarter for over 400 million in 7-9 figure deals. The company views the overall performance as a result of good sales execution and the alignment with business outcomes that customers are driving for. The sales team is acknowledged for their role in delivering across consumption and driving use cases, both in wins and with services, along with monumental contracts.

A：The speaker identifies the sales team, which includes both consumption and services, as well as the services team, as performing exceptionally well. They are recognized for driving platform usage, contributing to monumental contracts, and overall stellar performance.

A：The company continues to have sophisticated systems for consumption prediction, with a focus on accuracy within a 5% deviation. There has been improvement in contract prediction and TACV prediction, but there is still less predictability in the transition from use cases to consumption. The company actively works on enhancing this area, which remains a research project due to the unpredictable nature of customer actions.

A：The speaker feels very good about the company's ability to model business and is confident in the predictability of the core business, which is considered to be among the best teams he has worked with. There is also an acknowledgment of the positive impact of AI, particularly with increased visibility and efficiency brought about by projects like C3 pools, which has led to better outcomes for both customers and the company.

A：The company's approach to product launches prioritizes building great products, making them easy to use, and driving revenue. Margins are optimized by finding efficiencies in the core business, and the company aims to balance growth with operating margins. New AI products have a margin profile that's not as high as the core business, but this is offset by improving efficiencies in other areas of the core business.

A：Projects that have benefitted from AI include optimizing free pools across all deployments, improving visibility into compute resources, and optimizing storage lifecycle policies. These efforts have led to significant benefits, such as reduced wait times for customers and cost efficiencies. AI has also changed the investment framework for the company, shifting focus from headcount to growth and resulting in a small reduction in force with minimal impact on net adds in the fourth quarter.

A：The speaker is inquiring if the native integration of AI services at the top is showing an impact on increased demand.

A：According to the company's perspective, the overall impact of AI on software is that the winners will be the companies that provide a single source of enterprise truth, with built-in security, auditability, trust, governance, and data access controls.

A：Snowflake's differentiation in the context of AI and agent building includes its packaging of AI model providers into a cohesive product, which is easy to use, and its ability to work with multiple model providers. This, along with features like Snowflake Intelligence and Cortex, aims to make the deployment of AI agents more efficient.

A：Snowflake's technical advantages for users to build agents include its position as a data platform that makes data easy to use and its commitment to interoperability, allowing agents to be built using a variety of tools, including NCP.

A：The speaker hints at an increase in query volumes from Cortex code users but does not provide a direct confirmation or quantification.

A：When providing financial guidance, the company considers every ounce of data available and follows a strict process that focuses on historical data and the ability to reliably predict the future.

A：From the beginning of last year to the current year, Snowflake's offerings and performance have evolved significantly, with the introduction of Snowflake Intelligence, adoption of AI services, and advancement in the use of AI with agents. This is expected to culminate in stronger performance in the current year.

A：The projected seasonality for free cash flow follows prior years, with the majority collected in the fourth quarter. The company has guided to 23% free cash flow, whereas the observed value over the past two years was a 150 basis point headwind. The guidance provided is based on comfortable numbers that can be performed against.