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About

Genie Code is an AI agent built for data teams that analyzes, builds, and maintains complex data workflows inside the Databricks workspace. It autonomously plans and executes multistep tasks while adapting to an organization’s data and governance model, with specialized capabilities across data engineering, data science, machine learning, and business intelligence. Grounded in Unity Catalog metadata, semantics, and governance, it can identify authoritative tables, metrics, and assets, understand dependencies across data and AI systems, and respect existing access controls. For data science, Genie Code can find and clean data, explore datasets, test hypotheses, and generate shareable reports. Machine learning workflows include feature engineering, model training and evaluation, deployment, endpoint configuration, and performance tuning. Data engineers can use natural language to automate ETL workloads, optimize queries, and build Spark Declarative Pipelines.

About

Muse Code is Meta’s terminal coding agent, powered by Muse Spark 1.2, for handling complex software engineering tasks across large repositories. The agent can plan changes, write code, validate results, and coordinate multiple persistent subagents during development sessions. Muse Code uses async background agents that stay active throughout a session to reduce repeated information gathering and help complete multi-step tasks with less steering. Its runtime uses a local event log that records model calls, tool runs, approvals, and edits so sessions can be replayed and resumed after failures. Muse Code includes bundled skills such as /plan for approval-gated planning, /grill for stress-testing plans, and /goal for working toward completion. Built for AI developers and software teams, Muse Code helps automate coding workflows, long-running engineering tasks, debugging, and repository-level development.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Data engineers, data scientists, ML engineers, and analytics teams seeking to automate complex data, machine learning, pipeline, and BI workflows

Audience

Software engineers, AI developers, coding agent users, platform teams, DevOps teams, ML engineers, research teams, enterprise development teams, and organizations that need terminal coding agents, repository automation, code generation, debugging, validation, persistent subagents, replay-safe execution, long-running coding workflows, and end-to-end software development support

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

$1.25 per 1M tokens (input)
Standard pricing: $1.25 per million input tokens and $4.25 per million output tokens

Discounted "contributor" tier costing $0.10 per million input tokens and $0.20 per million output tokens for users who agree to share feedback to improve the AI.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Code looks exciting because Meta is finally going after coding agents directly, not just releasing another general AI model. A terminal-based agent that can write code, inspect software, run tests, and validate changes is exactly the kind of workflow developers actually care about. The pricing angle is a big deal. Meta is pitching Muse Code as one of the more affordable coding agents, with a lower-cost tier that is reportedly less than one-tenth the cost of its general Muse Spark model. That matters if you use coding agents all day instead of just for the occasional refactor. I also like that it is powered by Muse Spark 1.2, which sounds more focused on software engineering than earlier Muse Spark releases. If Meta can make the agent reliable inside real repos, Muse Code could become a serious daily tool.

Cons

  • It is still in beta, so I would not trust it blindly yet. Coding agents need to prove themselves on messy codebases, failing tests, weird dependencies, security-sensitive changes, and long multi-step tasks. I would also want to see more independent developer feedback. Meta’s pricing and positioning are interesting, but the real test is whether Muse Code can consistently make good changes without wasting time or creating cleanup work.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Databricks
Founded: 2013
United States
www.databricks.com/product/genie/code

Company Information

Meta
Founded: 2004
United States
meta.ai

Alternatives

No Alternatives

Alternatives

Claude Code

Claude Code

Anthropic

Categories

Categories

Integrations

Databricks
Meta AI
Muse Glimmer
Muse Spark
Muse Spark 1.1
Muse Spark 1.2
Muse Spark 1.3
SQL

Integrations

Databricks
Meta AI
Muse Glimmer
Muse Spark
Muse Spark 1.1
Muse Spark 1.2
Muse Spark 1.3
SQL
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Claim Databricks Genie Code and update features and information
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