August 13, 11am EDT
Dash vs. Full Stack in the AI Era
Why Python and Dash are still the strongest choice when building data apps with AI
Type âbuild a dashboard or data application that tracks our churn by cohortâ into Claude and you might get a Dash app back, or a full React frontend with a backend and an API layer stitched between them.
The AI will happily generate either, but youâre the one who has to live with (and maintain) the result.
In this webinar, we break down why naming Dash in your prompt leads to better outcomes for data apps, internal tools, and reports, which is the majority of what teams are actually building with AI today.
You'll learn how to:
- Simplify your tech stack for data apps to make them smaller and easier to maintain
- Capitalize on the tools you already use in data science to build sophisticated data apps
- Lower the total cost of your token spend by up to 33% when building data apps
- Reduce the attack surface area of your application from hundreds of packages to just 27 as supply chain risks are growing
- Choose the appropriate tool for the job: when to choose Dash and when to reach for full stack
Who it's for:
Data scientists, Python & Dash developers using AI coding assistants, and engineering leaders evaluating frameworks for data applications
Meet the Speakers
Matt Brown
As Senior Product Manager at Plotly, Matt specializes in data analytics and visualization. He helps teams accelerate development practices, enhance user engagement, drive product satisfaction, and grow customer bases. Prior to his career in Product Management, Matt designed and developed web applications, including the front-end architecture for a real-time global asset tracking system.
Robert Claus
Robert is the Director of Engineering at Plotly, specializing in AI-first data analytics platforms and open-source developer tools. With over a decade of experience bridging hands-on engineering and team leadership, he builds high-performing teams and ships products that matter. Prior to Plotly, Robert spent his career scaling engineering organizations from the ground up and building products for startups and Fortune 50 customers alike.