Hands-On with Anthropic's New Computer Use API: Teaching Claude to Navigate E-Learning

Anthropic just released something that's getting the AI community buzzing - their Computer Use API. I couldn't wait to take it for a spin, so I decided to try something ambitious: teaching Claude to evaluate an e-learning course. Here's what happened when I gave an AI its first job as an instructional designer.

Watch the video below to see it in action!

What's the Big Deal?

Think of the Computer Use API as giving Claude (Anthropic's AI) actual hands to work with a computer. Instead of just chatting about doing things, it can now actually do them - click buttons, type text, navigate websites, and even analyze what it sees on screen. It's like the difference between describing how to ride a bike and actually getting on one.

Setting Up the Virtual Playground

First things first - safety. While having AI control a computer sounds cool, letting it loose on your actual machine probably isn't the wisest idea. That's why I set up a containerized environment with two parts:

• A chat interface where I could communicate with Claude
• A virtual computer where it could safely experiment

The Zero-Shot Challenge

I decided to test Claude's abilities with what we call a "zero-shot prompt" - basically giving it all instructions upfront and seeing if it could figure things out on its own. No hand-holding, just a clear mission: log into an e-learning platform, go through a course, and provide meaningful feedback.

Watch and Learn

The most fascinating part? Claude operates like a meticulous student. It:

1. Takes screenshots to understand what it's looking at
2. Analyzes the interface elements
3. Plans its next moves
4. Stops to think when it encounters problems

When something unexpected happens (like a popup or an unclear button), it actively tries to problem-solve rather than just giving up.

The Good, the Bad, and the Rate Limits

Here's what I learned from the experiment:

The Good

• Claude successfully navigated Firefox like a pro
• It understood context-dependent choices (like resuming vs. restarting a course)
• It could analyze course content and provide feedback
• It showed impressive problem-solving abilities when things went wrong

The Challenges

• The process isn't exactly speedy - there's a lot of thinking time
• API rate limits are a real constraint (especially on demo accounts)
• Sometimes it makes assumptions that don't quite work out (like mistaking an "Add" button for "Save")

Unexpected Insights

One particularly interesting moment came when Claude encountered a multiple-choice question. It actually recognized that all options were correct, even though the course was designed as a single-select question. Unfortunately, it didn't include this observation in its feedback - a missed opportunity for course improvement!

Looking Ahead

This initial test suggests some exciting possibilities for AI in educational technology. While there are still kinks to work out (like those pesky rate limits and occasional interface misinterpretations), the potential is clear. Imagine AI assistants that could:

• Systematically test and evaluate e-learning courses
• Provide detailed accessibility feedback
• Generate comprehensive course review reports
• Identify potential user experience issues

What's Next?

This was just a first look at what's possible with the Computer Use API. Stay tuned for more experiments - I've got some interesting ideas for pushing Claude's capabilities even further. If you're interested in trying it yourself, remember to:

1. Use a controlled virtual environment
2. Be patient with the processing time
3. Plan for rate limits if you're using a demo account

Have you tried the Computer Use API yourself? I'd love to hear about your experiences in the comments below!

This post is part of my ongoing exploration of AI capabilities and their practical applications in educational technology. Follow along for more hands-on experiments and insights!