Designing Curricula For The Age Of Co-Intelligence

The urgency to prepare learners for an AI-shaped future is no longer up for debate. Everywhere we look, AI is reshaping job descriptions, rewiring how people approach their work, and shifting the expectations employers have of their teams. And to this end, curriculum designers—especially those shaping Career and Technical Education (CTE) programs- face a mammoth task.

The challenge today is about designing a curriculum that helps learners build the skills to work with AI and also helps them retain their sense of purpose and identity. And while many institutions recognize the importance of AI readiness, few have found the right blueprint for integrating it meaningfully into their programs.

Recently, we had the opportunity to have a conversation with Ziplines Education, who design training courses for mid-career professionals.

This blog brings together the highlights of the conversation between our VP of Sales and Marketing, Dipesh, and their Senior Learning Experience Designer, Dalia. The conversations focus on what educators need to consider as they redesign curriculum for an AI-augmented future.

Redesigning For AI Literacy

AI has evolved over the years. Today, we have more than just AI. There’s Artificial Narrow Intelligence, Strong Artificial Intelligence, and Artificial Superintelligence. A force difficult to ignore, people who were once skeptical about AI have started using it.

“New York City schools banned AI at the beginning, but then they now use it, and a lot of school districts did the same.”

And while that is exciting, it also means many are rushing to adopt it without pausing to ask some foundational questions:

1. What am I outsourcing when I rely on AI?
2. Is this the best output I can produce?
3. Am I still thinking deeply, or just moving fast?

Today, the erosion of critical thinking is one of the biggest risks posed by AI. It’s especially concerning for learners who haven’t yet developed their own internal barometer for quality. How will they know what’s “good” if AI is doing the heavy lifting?

If we want to design a curriculum that helps learners show up fully in this new world of work, we need to help them navigate AI sensibly, purposefully, and appropriately.

Beginning With a No-Regret Move: Level With AI

It has become important to assess where individuals stand in relation to AI. Where does AI perform better? Where can you do better than AI? It’s going to be essential in order to be able to compete in an AI-driven economy.

“One of the most helpful frameworks I’ve come across is from Ethan Mollick’s Co-Intelligence. He recommends bringing AI into every task—not necessarily to use what it gives you, but to learn how you compare to it.”

This kind of active experimentation is essential because it helps learners (and educators) understand:

• Where AI is better
• Where human perspective still matters
• And how to create better outcomes through collaboration, not dependence

AI literacy programs that encourage this type of exploration create self-awareness, and that’s a critical ingredient for long-term employability.

Implementing AI Literacy Beyond the Tool

AI literacy is a multilayered skill. Yes, there’s the technical side: knowing how to use a tool, prompt an LLM, or set up a workflow. But there’s also a human layer: how we acknowledge its role in our process. As time goes by, AI models are going to get better, and the more data that’s fed into these LLMs, the harder it will be to achieve this balance.

Eventually, we run the risk of creating a workforce that can be easily taken over by AI. So, how do we consciously inculcate AI literacy among learners? This can be looked at in two parts:

Teach To Acknowledge

In our conversation, Dalia shared how students in their AI courses often ask: “Is using AI cheating?” The answer is: only if you pretend it’s all yours. Learners need to be taught that it’s okay to use AI, provided they are transparent about it. Here’s how that can be done:

Acknowledgement: “Hey, I used AI to take a first stab at this, and then I went through and added my own insights and made some modifications.”

Communication: “Hey, I took a look at this. I used AI. What do you think?”

This teaches ownership, discretion, and integrity. By giving credit to AI, learners build their credibility in a team within which AI is increasingly becoming a part.

Teach To Re-Evaluate

Earlier success was about how fast you could learn new tools or systems. Today, knowledge is being increasingly commoditized by AI.

What is important is the wisdom to use the knowledge in the right way, in the right manner, and there are different skills within that.

In this context, three human skills need to be unlearned:

Taste – The ability to tell the difference between the good and the bad. AI can keep generating outcomes depending on how you keep prompting it, and that depends on your taste.

Empathy – As AI replaces technical skills, the most valuable team members will be the ones who are easy to work with, who understand nuance, people, and context.

Curiosity – Not just about learning new tools, but about questioning the way things work and imagining something better.

Develop For Efficiency and Design For Originality

Questions that often come up are: How do we help people think for themselves when AI is doing so much of the work? AI is creating a state of digital dementia where users completely rely on AI for everything without creating their own thoughts. How do we build that muscle to modify AI outputs and infuse them with personal expertise and experiences?

Both Dipesh and Dalia agree on the importance of finding structured opportunities to work with AI outputs.

1. Save the original kernel of the idea
Use AI to refine, expand, or challenge it, but do not allow it to replace individual voices.

2. Use AI as a co-editor
Encourage learners to use AI as a co-editor and not a ghostwriter. Encourage them to think first, and then ask AI to critique it.

3. Create a feedback system
Ask, “Is this the best output you can produce?” That question alone prompts a second round of thought. Sometimes a third. And almost always, the output improves with each iteration.

The Infusion Of Cross-Disciplinary Education Improves Critical Thinking

The future of education lies in the intersection of liberal arts and STEM. We have spent decades separating the two. Dalia recalls how her experience in traditional education was binary. “Liberal arts are on one side of campus, and the STEM majors are on a completely different side.”

But as AI continues to automate more of what we traditionally considered “hard skills,” the value of human-centered abilities—like empathy, discernment, and philosophical reasoning—is becoming more obvious.

Liberal arts disciplines cultivate those skills. They help learners make sense of complexity, question assumptions, and communicate with clarity and depth. That doesn’t mean STEM becomes any less important. However, the education systems need to do a better job of blending both.

User Reflection Remains The Key For Achieving AI Literacy

Reflection is just as important as experimentation. We can’t prepare learners for an AI-shaped future by handing them tools and hoping for the best. Here are 3 action steps to begin with:

1. Identification of gaps
Help learners figure out where they stand—what they know, what they don’t, and what they need to work toward.

2. Create a structured learning path
Outline levels of AI competence or create simple checklists of must-have skills. Learners should be able to see the road ahead.

3. Incentivize learners
Offer professional development stipends or create recognition programs to help learners upskill.

By capturing the various nuances of AI literacy, institutions can achieve the holy grail of improved productivity and learner upskilling.

Catch the full discussion between Ziplines Education and Magic EdTech, where we dive deeper into what real AI readiness looks like—from building co-intelligence with tools, to fostering critical thinking, to creating learning paths that balance technical skills with human judgment. See how Ziplines is helping mid-career professionals upskill with speed, and how we’re working together to shape a curriculum that blends experimentation, ethics, and employability, without losing the human touch.