Databricks, the Data and AI company, has introduced Genie Code, an autonomous AI agent designed to transform how data engineering, data science, and analytics are performed. Building on the existing Genie capability—which enables knowledge workers to chat with enterprise data for instant, trusted answers—Genie Code extends agentic capabilities to data professionals. It autonomously handles complex, multi-step tasks from ideation to production deployment, including building pipelines, debugging failures, shipping dashboards, and maintaining systems. On real-world data science benchmarks, Databricks reported that Genie Code more than doubled the success rate of leading coding agents, achieving 77.1% compared to 32.1%.
Quick Intel
The Shift to Agentic Data Work
Traditional data tools position AI as an assistant for code generation and local testing, leaving data teams responsible for planning, orchestration, validation, and ongoing maintenance. Genie Code reverses this model by reasoning through problems, devising multi-step plans, producing and validating production-grade code, and managing results autonomously—all under human guidance for critical decisions.
"Software development has shifted from code-assistance to full agentic engineering in the past six months," said Ali Ghodsi, Co-founder and CEO of Databricks. "Genie Code brings this revolution to data teams. We're moving from a world where data professionals are assisted by AI to one where AI agents do the work, guided by humans. We are calling this Agentic Data Work. It will fundamentally change how enterprises make decisions."
Core Capabilities of Genie Code
Genie Code addresses key limitations of existing agentic coding tools by leveraging Unity Catalog's rich context, including data lineage, usage patterns, and business semantics, to deliver accuracy and governance in enterprise settings.
"At SiriusXM, Genie Code supports everything from authoring notebooks and complex SQL to reasoning through table relationships and debugging pipelines," said Bernie Graham, VP of Data Engineering, SiriusXM. "It acts as a hands-on development partner that helps our data teams deliver high-quality work in less time."
"Genie Code changes how our data teams operate," said Emilio Martín Gallardo, Principal Data Scientist, Data Management & Analytics at Repsol. "Instead of stitching together notebooks, pipelines, and models manually, we can hand off complex workflows to an AI partner that understands our data, governance, business context, and internal libraries such as Repsol Artificial Intelligence Products. It accelerates everything from time series forecasting to production deployment, without sacrificing rigor or control."
Strengthening Agent Reliability Through Acquisition
Databricks has acquired Quotient AI, a leader in evaluation and reinforcement learning for AI agents. Quotient provides automated monitoring of agent performance, early detection of regressions, and failure analysis, feeding a continuous improvement loop. The Quotient team's prior experience enhancing GitHub Copilot quality now bolsters Genie Code, ensuring production systems not only operate reliably but improve over time.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including Adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics, and agents. Headquartered in San Francisco, Databricks offers a unified Data Intelligence Platform that includes Lakebase, Genie, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
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