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Content Design AI Accelerator

Build a working AI tool that solves a real problem in your content work. Over 6 weekly workshops, you’ll create a prototype, test it systematically, and document everything you need to bring it to life. Made for content designers.

> Read the syllabus and local times.

First cohort begins Tuesday, March 3. Applications close Friday, January 30.

Cohort fee: US $1600

Payment plan available. Payments in USD.

Apply for March cohort
Content Design AI Accelerator

Meet the presenter

Patrick Stafford
UXCC

Patrick Stafford is the CEO and Cofounder of the UX Content Collective. He hosts the Writers of Silicon Valley podcast, and was previously the Lead Digital Copywriter at MYOB.

Patrick presents the AI: Ethics and AI: Evaluation workshops for UX Content Collective.

Who is this program for?

You have a specific AI problem at work and want to solve it properly, not just experiment with prompts.

You're a content designer and need to demonstrate what's possible with working prototypes.

You're ready to move beyond working on single prompts and start working on a tool that scales your impact.

You want to prove AI concepts work before asking for resources, with clear documentation and requirements.

About the Content Design AI Accelerator

What do you leave the AI Accelerator with?

  • A prototype proving your AI concept
  • An understanding of how to build, document, and test AI tools for content design
  • Evaluation framework with test cases and success criteria for measuring quality
  • Portfolio-ready project demonstrating scoping, building, evaluation, and documentation skills​
  • Guidance on using AI as part of your workflow, not a replacement for it

How does the AI Accelerator cohort work?

Weekly workshops

Each live workshop runs for 3 hours. You'll receive a recording of each live session.

Personalized feedback

A small cohort ensures you'll get valuable feedback from instructors and peers.

Learn and build

Learn with a combination of explanation and practice.

Go beyond prompts

Learn how context engineering plays a key role in AI work and build something that really works.

Content Design AI Accelerator Syllabus

Week 1: Scoping and Requirements Define your project with requirements.

What you’ll learn: How to scope an AI project within realistic constraints, create canonical examples showing what good output looks like, and choose the right prototyping platform for your needs.

Week 2: Build Your Prototype Create v0.1 and test on real examples

What you’ll learn: Project structure, organizing instructions and examples, building system prompts, and getting something working even if it’s rough.

Week 3: Testing and Refinement Run systematic tests and iterate on failures

What you’ll learn: How to diagnose AI failure patterns, create test sets, run systematic evaluations, and iterate instructions and examples to improve output quality.

Week 4: Implementation Planning Document what production deployment requires

What you’ll learn: How to translate a working prototype into production requirements, identify technical dependencies, and assess deployment risks.

Week 5: Production Documentation Create handoff materials for engineering

What you’ll learn: How to document system requirements, evaluation criteria, edge cases, and maintenance plans that engineering teams need to implement your AI logic in production.

Week 6: Present and Plan Next Steps Demo your prototype and share implementation plan

What you’ll learn: How to present your working prototype to stakeholders, discuss implementation next steps, and share lessons learned with your cohort.

Some frequently asked questions

Do I need to have completed other UXCC AI workshops?

No. Obviously, if you’ve completed the workshops you come with useful knowledge but obviously that’s not possible for everyone. If you haven’t attended UXCC workshops we’ll prepare pre-reading material for you to ensure you’re as up to speed as you can be.

In other words: if you haven’t attended the other workshops, don’t let that stop you.

Week 1 helps you scope a realistic project, but you should come in with a general problem area you want to solve (content audits, style guide consistency, documentation generation, etc). As long as you have a problem, that’s the main thing. We’ll help with the rest.

 This is exactly why the program is structured in two phases. Weeks 1-3 focus on proving your AI logic works in a prototype environment.

Even if your employer has stringent restrictions on AI, there’s still value in being able to build and demonstrate possibilities. And at the very least, you’ll have learned valuable AI skills and built something real for your portfolio.

Many participants get employer sponsorship since you’ll be building a tool that solves a real work problem. We can provide a detailed curriculum outline and expected deliverables to support your request.

This isn’t an AI engineering course. You’ll learn practical skills for scoping a tool, system messages, complex prompts, context engineering, evaluation, and documentation within content design constraints. If you’re looking for model training, fine-tuning, or advanced machine learning concepts, this program won’t cover that.

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