What if “working in tech” doesn’t mean what we’ve been taught it means?

In Part 2 of this Q&A series, Dr. Renée Jordan challenges the narrow definition of tech careers by centering “everyday people” working in technology-saturated industries—not just computer scientists or engineers.

This episode explores why expanding our understanding of tech is critical for increasing representation and helping more women and girls see themselves as innovators, contributors, and leaders.

You’ll learn:

• Why traditional definitions of “tech” limit access and imagination
• How technology shows up across careers—not just in coding roles
• The importance of visibility and language in shaping identity
• How redefining tech creates more inclusive pathways into opportunity

Because when we redefine the field, we redefine who belongs in it.

How do you receive critical feedback—without losing yourself in the process?

In this first episode of a 3-part Q&A series, Dr. Renée Jordan reflects on a pivotal moment from her doctoral journey: navigating major revisions after her prospectus defense while staying grounded in her purpose.

This conversation explores the tension between growth and self-preservation—especially for women and girls navigating academic and professional spaces.

You’ll learn:

• How to separate structural feedback from identity-level compromise
• Why not all feedback is meant to be accepted
• How to refine your work without erasing your voice
• A mindset shift that turns feedback into strategy—not self-doubt

This episode is for anyone learning how to evolve their work while staying aligned with who they are.

Because growth should expand your voice—not silence it.

What does it take to design an AI workshop that goes beyond exposure—and actually builds student thinking?

In this episode of the Black-Liberation.Tech Podcast, Dr. Renée Jordan breaks down the how behind her Janiyah GPT workshop model—offering a behind-the-scenes look at how students learn to use AI as a thinking partner, not just a tool.

If you’re an educator, program director, nonprofit leader, or community-based organization responsible for delivering meaningful learning experiences, this episode gives you a practical framework you can apply immediately.

Because the challenge isn’t introducing AI. It’s designing experiences that are engaging, culturally relevant, and cognitively rigorous—without overwhelming your team.

Inside This Episode

• How to teach students to use AI as a thinking partner (not just for answers)
• A simple framework for writing stronger prompts: Context + Data + Action
• How to use Bloom’s Taxonomy to deepen student thinking with AI
• Why culturally responsive AI design increases engagement, confidence, and belonging
• Practical strategies for designing AI workshops that are:
  • Hands-on
  • Interactive
  • Reflective
  • Scalable across programs

Why This Matters for You

You’re not just introducing new technology. You’re responsible for ensuring that learning experiences:

• Build real skills
• Reflect the identities of the students you serve
• Prepare them for a rapidly evolving future

This episode offers a framework that helps you do that—without starting from scratch.

Key Takeaway

Strong AI workshops aren’t about the tool.

They’re about how you structure thinking.

And when you combine:

• Clear prompt design
• Cognitive scaffolding
• Cultural relevance

You create learning experiences that stick.

Resources & Next Steps

Want to bring this framework to your students or staff? Explore the full workshop: https://www.black-liberation.tech/intro-workshop.html

Prefer guided implementation? Book a conversation: https://calendly.com/renee-jordan-nuance/

Reflect as a leader:

“How are we currently using AI—and are we developing thinkers, or just users?”

• How can students use AI as a thinking partner?
• How do you design an AI workshop for students?
• What makes an AI literacy program effective?
• How can educators teach prompt engineering?
• Why is culturally responsive AI important in education?
• How do you use Bloom’s Taxonomy with AI?