AI Design Leader | x-Uber/Google/Amazon

The job posting asks for a designer who can research, prototype, code, and ship. One role, three people's worth of expectations. Design teams got smaller. The work did not. And now every product roadmap includes AI features that need to be designed by people who were never trained to design for probabilistic systems.
The pressure is coming from two directions. Inside your organization, you are expected to move faster with fewer resources while somehow incorporating AI tools into workflows no one has figured out yet. Outside, the profession itself is shifting. AI generates interfaces, writes copy, produces prototypes in minutes. The execution work that built your career is compressing. The question is no longer whether designers need to adapt—it is whether you are building the skills that will matter in two years.
Claude Code for Designers answers both pressures at once. You move faster because you can build functional prototypes yourself. You stay relevant because directing AI to build is the new execution skill. You leave with a deployed project and a workflow system you can use on anything that comes next.
Go from trial-and-error prompting to systematic AI-assisted building. Ship functional projects with a workflow you can use on every project
Project intake framework for defining scope, constraints, and context before building
Phased build planning that breaks complex projects into executable stages
Live workflow demos from brief to deployed application
Learn to communicate with AI through structured prompts, context files, and specifications
Context architecture techniques that shape AI output across an entire project
MCP configuration for integrating external tools, agents, and knowledge sources
Apply the full workflow end-to-end on a real project you define
Hands-on building with real-time troubleshooting and technical support
Deployment walkthrough from local build to live URL
Build a functional application you can demo and link in your portfolio
Document your process as a case study: context decisions, iteration patterns, troubleshooting
Articulate how you scope, direct, and validate AI-assisted builds with confidence

AI Design Leader | AI enablement for UX orgs | ex-Uber, Google, Amazon, Stanford
Product Designers. You design in Figma and wait on engineering. You want to build and ship functional prototypes yourself.
Design Leaders. Your team needs to move faster and integrate AI workflows. You want firsthand fluency before rolling this out.
MXDAI Alumni. You have the strategic frameworks for AI design. Now you want the execution skill to match.
This course assumes working knowledge of design systems, user research, and product workflows.
Experience using AI assistants in your workflow. The course moves quickly and assumes baseline comfort.

Live sessions
Learn directly from Rupa Chaturvedi in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
8 live sessions • 14 lessons • 4 projects
Mar
17
Mar
21
Mar
24
Mar
28
Live sessions
1-3 hrs / week
Tue, Mar 17
8:00 PM—9:00 PM (UTC)
Sat, Mar 21
3:00 PM—4:30 PM (UTC)
Tue, Mar 24
8:00 PM—9:00 PM (UTC)
Projects
1-2 hrs / week
Async content
1 hr / week
$1,750
USD