Supercharging the Developer Workflow for AI with Snowflake's Integrated Dev Environment
Developers hold the keys to enabling agentic AI applications, but these days their proverbial key rings are getting overcrowded. With so many tasks and integrations required, they end up fumbling through a host of development environments and tools, slowing down productivity and innovation. To build modern agentic apps efficiently, developers need an integrated solution that is fast, collaborative and easy to use. They need a common development environment that gives them access to everything they need — when they need it.
Grounded in a commitment to delivering the best modernized developer experience, Snowflake is proud to highlight the upgraded capabilities and innovative features that make it a destination for builders. Our robust development environment offers the flexibility to use familiar tools and languages, along with the ability to share environments for better collaboration and controlled access to all data, no matter where it lives. Taken together, developers now wield a master key, unlocking the potential to build any application with ease.
Here, we’ll take a deeper look at the tools and capabilities Snowflake has introduced to help developers bring agentic applications to life.
A robust development environment to meet varied needs
Like any builders, developers often rely on their favored set of tools, and Snowflake is built to accommodate that reality through integrations with a wide range of third-party tooling. With Workspaces, a powerful, unified editing environment within Snowsight UI, developers get a common interface that combines structured code organization, built-in Git integration, Cortex Code (private preview), interactive charting and much more.
By providing a governed, file-based environment with Git integration, Workspaces enables faster, AI-augmented coding and seamless team collaboration. Users can choose to work in SQL or Python, as well as manage a variety of project types, including dbt projects on Snowflake. The newly evolved Snowflake CLI provides an extensive command line interface for working directly with Snowflake objects or building automated tasks that can be executed by a task or set to run on a schedule. With the flexibility to use any tool and ability to control any object inside Snowflake, developers can build with ease on top of their Snowflake environment.
With Git-synced Workspaces, collaborating and incorporating version control for all Snowflake objects is made easy and seamless. Any Git-enabled platform can be used, including locally hosted solutions, giving users the ability to connect to remote repositories, switch or create branches and push or pull changes all from within Snowsight. Workspaces even provides a built-in visual difference view that helps identify and resolve conflicts if they arise — all without leaving the UI.
Git integration also means developers can use their favorite IDE to work on any aspect of Snowflake. Our VS Code integration allows developers to work in their environment of choice and still be able to share it with the rest of their team by using the Git integration. This enables a more streamlined and collaborative development process overall, especially for teams managing shared codebases.
These features all help to strengthen the data strategy that AI depends on, an absolute must for creating agentic apps that work at scale.
Build with AI, and for AI
As developers work to deliver the most cutting-edge agentic AI applications, the Snowflake platform offers robust support from ingestion to consumption, allowing developers to select the most appropriate functionality at every phase of development. AI coding tools such as AISQL and Cortex Code enable faster and more accurate code creation, allowing developers to keep pace with the growing demands of scaling AI development. Instead of getting bogged down in writing code, developers can instead tackle more high-value tasks such as evaluating data integrity, accessibility and validity through testing. It frees them to consider the needs of the business instead of just the code that enables it. These AI-powered tools also contribute to more efficient use of resources, helping to identify performance optimizations — whether through code or otherwise.
For instance, developers and admins can gain a better understanding of how efficiently their code and queries run, again using Cortex Code from anywhere within Snowsight. With the power of AI, this feature allows users to understand the performance of their queries (for instance: What does each cost to run? Who is using them most?) and provides developers the opportunity to review and tune them to better optimize cost.
Finally, to ease the burden of connecting AI models to external tools, data sources and services, Snowflake offers managed model context protocol (MCP) servers that reduce integration complexity and management overhead. Customers can connect their Snowflake data with a variety of agentic applications from providers such as Anthropic, CrewAI and Cursor through MCP connectors to create context-rich AI agents and apps. Offering simplified interoperability, consistent governance and an open standards-based interface for agents to discover and invoke tools and retrieve structured and unstructured data, Snowflake managed MCP servers (public preview) remove the need to deploy separate infrastructure or build custom integrations.
Enjoy flexible execution and distribution options
Given the right development environment, supported by AI and for the advancement of AI, developers then want options for where to run code and applications. Traditionally, SQL, notebooks and other code formats were run exclusively in a data warehouse, but with Snowpark Container Services (SPCS), there is no such lock-in. SPCS provides a fully virtualized environment that offers the luxury of choice in terms of hardware (CPU or GPU) and memory size. VS Code can interface directly with SPCS to execute functions and modules directly in a container, as well.
This flexibility also extends to third-party development environments. Through a new integration with Vercel v0, any employee, from developers to analysts, can vibe code rich, AI-powered applications just by describing them. These apps run compute on your Snowflake account via SPCS and are protected by Vercel's global CDN, helping ensure that data remains in place, governance controls are maintained, and performance is optimized.
Whether developers seek to build applications to run inside an organization or provide them for external consumption, Snowflake has an option. Snowflake Marketplace provides a platform to distribute applications, AI data sources or connectors to millions of users. These Snowflake Marketplace items can also be used to enhance internal applications.
Forge a better path to AI with Snowflake
The promise of agentic AI is vast, and developers need to move fast to stay on the cutting edge. That requires a better development experience — one that provides direct access to the data and tools developers want and need, in an environment that promotes seamless collaboration across teams. Snowflake is committed to delivering just that. By integrating familiar tools, such as Git and VS Code, with Workspaces, and infusing every step of the development process with AI, we’re excited to help developers push the pace of innovation even further.
To get started, explore new and improved Snowflake features, including:
- Workspaces: Watch how easy it is to get up to speed in this three-minute demo.
- AISQL: Learn more with this quickstart.
And check out these Python quickstarts:
Forward-looking statements
This article contains forward-looking statements, including about our future product offerings, and are not commitments to deliver any product offerings. Actual results and offerings may differ and are subject to known and unknown risk and uncertainties. See our latest 10-Q for more information.
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