SkillSwap

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Inspiration

The idea for SkillSwap came from something I personally experienced. I wanted to learn graphic design, so I started looking at online tutorials and using generative AI. It was easy to find information, but I realized that information wasn't the same as having someone who could actually guide me.

AI can explain how to design something, but when you make a mistake, you often need someone to look at your work, correct you, and explain how they would approach a real project. That human experience is difficult to get from a tutorial.

At the same time, I realized that I already had skills that someone else might want to learn. That led to a simple question: "What if people could exchange skills instead of paying for another course?"

That's how SkillSwap started.

What it does

SkillSwap connects people who want to learn with people who can teach.

Users create a profile showing what they can teach, what they want to learn, their experience level, availability, and learning preferences. Our AI finds complementary people, explains why they could be a good match, and helps them start a skill exchange.

From there, users can connect, message, schedule sessions, and learn together.

Premium adds AI-powered learning support such as preparation packs, session summaries and transcripts, and quizzes to help users retain what they learn.

How we built it

We built the iOS experience using "Swift and SwiftUI", with a web platform for broader access. The backend manages users, skills, matching, sessions, messaging, and learning progress.

We use "OpenRouter" to power our AI features, including complementary skill matching, match explanations, and learning support. "RevenueCat" handles our Premium subscriptions and entitlements.

Our goal was to keep the core skill-exchange experience accessible while using AI to make the learning process more personalized.

Challenges we ran into

One of our biggest challenges was figuring out what makes a good match.

Simply matching two people who want to learn the same thing doesn't solve the problem. We wanted to connect people whose skills complement each other for example, someone who knows Python but wants to learn Figma with someone who knows Figma but wants to learn Python.

We also had to think about how to use AI without making it the center of the experience. SkillSwap is about people learning from people, with AI helping them find each other and learn more effectively.

Accomplishments that we're proud of

We're proud that we turned a personal frustration into a product that could help other learners.

We're especially proud of the idea of skill exchange itself. Instead of treating people only as students or teachers, SkillSwap lets everyone be both.

We're also proud of integrating AI and RevenueCat in ways that support the core experience rather than simply adding features for the sake of adding them.

What we learned

Building SkillSwap taught us that having access to information isn't always the same as having access to learning.

We learned that technology can help people find knowledge, but human interaction provides something different: feedback, real experience, accountability, and the ability to ask questions in the moment.

We also learned that a good AI feature shouldn't replace the human experience. It should make that experience easier and more useful.

What's next for SkillSwap

We want SkillSwap to grow into a larger community where people can exchange skills across technology, design, languages, academics, hobbies, and professional development.

Next, we want to improve our matching system, expand collaborative learning tools, make sessions more interactive, and give users better ways to track their progress over time.

Ultimately, we want SkillSwap to make learning something new feel less like searching for the right course and more like finding the right person.

Learn what you want. Teach what you know. Grow together.

Built With

• cursor
• openrouter
• revenuecat
• swift