Analytics Data Engineer (ADE) Bench, ft. Benn Stancil

Discover how ADEbench measures real-world analytics engineering tasks for AI-assisted workflows, why it matters for teams building with dbt, and how to run it yourself.

Featuring benchmark co-author Benn Stancil, this session will unpack the design, demo the workflow, and share early takeaways to help you adopt the Model Context Protocol (MCP) with confidence.

• What you’ll learn
  • What ADEbench evaluates across accuracy, reliability, and speed
    
  • How to run the benchmark and interpret results for your stack
    
  • Practical guidance for adopting dbt MCP and agentic workflows
    
  • When Fusion’s reliability advantages may matter for AI-driven development
    
• Who should attend
  • Analytics engineers
  • Data engineers
  • AI engineers and technical decision makers
    
• Speakers
  • Benn Stancil, Benchmark co-author
  • Jason Ganz, Sr Mgr, Developer Experience and AI
    
• When
  • December 9 (virtual). Time 7pm London time, 2pm NY time, 11am California time.
    
• Why attend
  • Elevate your team’s approach to AI-assisted data development
  • Get hands-on with a credible, open benchmark you can rerun and extend
  • See how to quantify improvements and share results with your org and the community

Register now to save your spot and get the replay link.

Meet the speakers:

Benn Stancil

Founder

Mode

Jason Ganz

Senior Manager of AI Strategy and Developer Experience

dbt Labs