Snowflake CoCo: AI Coding Agent for the Modern Data Stack

Snowflake CoCo: AI Coding Agent for the Modern Data Stack

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Blog / AI & ML / Snowflake CoCo: The Coding Agent Built for Data Now Available Where You Work

JUN 02, 2026 / 8 min read AI & ML Snowflake CoCo: The Coding Agent Built for Data Now Available Where You Work

Siddharth Dwivedi +3

At Snowflake Summit 2026, Snowflake CoCo becomes available where builders work. With a native desktop application, cloud agents, agent SDK, and (coming soon) mobile app and slackbot, CoCo will be fully integrated into the surfaces and tools where modern data teams live — all fully grounded in the enterprise data.

Adoption of AI in the enterprise has shifted from the theoretical potential of AI to the practical needs of production environments: putting AI to work safely, securely and governed, at scale.

The first wave of assistants offered autocompletion and query generation. The next wave is agentic: systems that inspect codebases, reason through complex tasks, modify files, run tests and manage pull requests with humans in the loop. In standard software engineering, this is already the new baseline.

For data and AI teams, the bar is higher. Enterprise AI runs inside governed data systems with live schemas, access controls, lineage and operational pipelines. Generic AI coding agents hit a wall here as they often generate code that looks right but lacks the grounding in data context and permissions to actually work in production.

Snowflake CoCo closes that gap, providing an agentic control plane for builders operating on modern data stacks.

"Thomson Reuters has built its data foundation on Snowflake to create a single source of truth across 37,500+ governed tables and 350 data sources, and now Snowflake CoCo is accelerating how we build on top of that. Our teams are modernizing legacy systems, scaling AI pipelines, and delivering insights in days instead of weeks, all within a governed environment. When you can go from idea to production that fast on top of trusted data, it fundamentally changes what's possible.

Caitlin Halferty

Head of Data & Analytics at Thomson Reuters

CoCo was built with a specialized harness for the data lifecycle, not as a generic wrapper around a model, but as an integrated system designed for how data engineers, analytics engineers, data scientists and AI builders actually work. It grounds the agent in data context, and connects it to the right tools and runtimes.

When it comes to real data engineering work, CoCo isn't just keeping pace with leading coding agents. It's setting the bar.

On ADE-Bench , an industry framework created by dbt Labs to evaluate AI agents on real-world analytics and data engineering tasks, CoCo achieved a 72.1% pass rate, outperforming both Anthropic's Claude Code and OpenAI's Codex (each at 65.1%) 1. And the lead widens further on Snowflake native dbt project tasks, where CoCo's deep integration with the platform pays off.

Crucially, CoCo doesn't win by brute force. Compared to Claude Code running on Opus 4.7, CoCo uses 51% fewer tokens and takes 8% less time to get the job done. Two design choices drive that efficiency:

Targeted vs. exhaustive exploration - Rather than scanning everything in sight, CoCo navigates directly to the data that matters, resulting in more efficient data exploration.

A native tools approach - CoCo leans on native tools for working with data systems such as Snowflake, dbt and Airflow instead of falling back on bash based workflows, keeping work close to the data.

1 Efficiency score based on internal testing using ADE-bench, a framework created by dbt for evaluating AI agents on real-world analytics and data engineering tasks

What's new at Summit 2026

At Summit 2026, CoCo evolves from an AI coding agent into a full AI development platform. The new launches are organized around a simple principle: Your agent should work wherever you do and keep working when you can't.

“At Fanatics, our data demands shift constantly, and Snowflake CoCo gives our team the speed to keep pace. Engineers who used to spend days untangling pipeline issues and modeling data can now resolve those problems in hours, freeing them to build and ship new capabilities exponentially faster.”

Maddy Want

VP of Data at Fanatics

Use CoCo, where you work today

Cloud Agents are the foundation for CoCo's broader platform expansion. Automations, Slack integration and a native mobile app (the latter two coming soon) are all powered by Cloud Agents, bringing long-running, autonomous workflows to every surface where teams interact with CoCo.

For builders using CoCo directly within Snowflake environments, Cloud Agents bring the full agentic runtime directly into Snowsight. With Cloud Agents, each Snowsight session can now spin up an isolated, Snowflake-managed cloud environment behind the scenes, giving users the power of the CLI from any browser with no local setup, dependency management or infrastructure required.

When enabled, Cloud Agents provision a dedicated container for each CoCo session. The agent can execute shell commands, run Python scripts, install packages, read and write files, perform dbt builds and tests using a dynamically generated Snowflake profile, and search the web for additional context.

CoCo Desktop

CoCo is coming to Windows and macOS bringing the full power of Snowflake-native development into a native desktop app built for how data teams actually work.

“Snowflake CoCo is becoming a core part of how we operate as a company. We’re rolling it out across the entire organization, not just our data team. Because it understands our data, our environment, and our governance, teams can build and automate workflows on top of trusted data without needing specialized expertise. Matt Luizzi

VP of Analytics at WHOOP

With CoCo Desktop, (generally available soon) builders get one governed surface to build across the data stack . You can create data pipelines, build applications, design agents, debug notebooks and visualize data flows without constantly jumping between screens. The editor becomes the place where code, data, context and execution come together so you can stay in flow from prototype to production.

Beyond the editor experience, CoCo Desktop brings an always-on AI agent to your local machine: a persistent assistant that understands project context, works across sessions and keeps momentum even when you step away.

With Automations , teams can move from reactive prompts to autonomous…