My Journey with Manus AI Agent: A Student's Perspective

How it all started?

I’ve been totally into AI agents for ages, watching them evolve from chatty assistants to do it all machines. When Manus AI launched in March 2025, dubbed as “the second DeepSeek moment”, I just had to check out the buzz of AI agent automation. I hit their site and applied for an invite code. Little did I know, this would turn my machine learning journey into an epic adventure!

When they asked for a reason, I kept it real: “Just a 2nd year cse ug in ai-ml. I’m fascinated and want to explore your product.” By evening, I had the code. I thought it was standard- turns out, I got lucky. Even blue-tick X accounts have been griping about waitlists!

What’s Manus AI?

For those new to the world of AI agents, Manus AI represents the next generation of artificial intelligence assistants launched in March 2025. Unlike traditional AI chatbots that simply respond to prompts, Manus AI functions as a comprehensive agent capable of performing complex tasks with minimal supervision.

Manus AI differentiates itself through its ability to:

Conduct autonomous research across the internet, pulling information from multiple sources including GitHub repositories, technical documentation, academic papers, and video tutorials

Create structured content organized in a logical, educational manner

Perform technical tasks like generating code, building Jupyter notebooks, and troubleshooting errors

Adapt to user needs through features like "Suggested Knowledge" that tailor content to your experience level

The platform offers a unique "Manus's Computer" view that provides transparency into its thought processes and research methods, essentially letting you see how the AI "thinks" as it works on your behalf. This makes it particularly valuable for students and professionals looking to understand not just the end result, but the methodology behind information gathering and content creation.

Currently available in beta with some usage limitations, Manus AI represents a significant leap forward in how artificial intelligence can serve as a learning accelerator and productivity enhancement tool.

First Interaction

The interface hit me as clean and minimalistic- nothing too fancy, just a sleek GUI I could navigate without a manual. There’s a “Manus’s Computer” window that shows its thought process, which felt like peeking under the hood of an AI brain. For a student used to cluttered IDEs, this AI productivity tools was a breath of fresh air.

Putting Manus AI to the Test

My ambition is to become a skilled MLE, and I am currently focused on learning data science and mastering the prerequisites, like libraries- NumPy, Pandas, Matplotlib, SciPy, Scikit-Learn on the horizon. I presented Manus with a detailed prompt:

“Create a Jupyter notebook with markdown and code samples that teach me the basics and most-used concepts of these libraries. Research popular data science and ML projects online- GitHub, blogs, YouTube and integrate the best real-world examples. Keep in mind, that it should not be a lousy notebook like print(a+b) NO! I want you to research all the popular and well used codes and projects of data science and machine learning available on internet and see what concepts from these libraries are most used and teach that in the notebook. Don't miss any important thing and cover all mentioned libraries. Structure it with theory, explanations, source links, example code, and a ‘test me’ section with interactive problems. Ensure it is practical, detailed, and beginner-friendly to help me achieve proficiency.”

I sought a comprehensive and engaging learning experience.

I want to ensure that after completing this Jupyter notebook, I'll be well-versed in all these libraries, understanding their uses and how to code with them effectively. My goal is to achieve proficiency, so please use your best teaching methods to help me learn in a practical and interactive way.

Manus straight up started cooking, making a todo file for all the tasks and started surfing the internet for the best resources available on the internet.

The Research

Manus exceeded my expectations, compiling a notebook that felt like a masterclass. It drew from GitHub repositories, YouTube tutorials, and blogs, presenting each library in digestible sections. The notebook included theory, sourced examples, clear explanations, and executable code, such as plotting with Matplotlib or running a Scikit-Learn classifier.

The “Suggested Knowledge” feature even adapted to my student status, accepting my preferences for a structured, practical format. I watched it work for 2 hours and 29 minutes before hitting a usage limit (more on that later), but the result was worth it.

The Hiccup: Usage Limits and Errors

It wasn’t all smooth sailing. After 2:29:56, I hit the beta’s daily usage cap. Plus, I noticed some errors- like a terminal hiccup during package installation- that Manus had to resolve. It’s a reminder this is still a work in progress.

Early Wins: A Student’s Dream Tool

Despite the limits, Manus delivered. The final notebook was a 303.8 KB gem, structured for hands-on learning with real-world applications. For a student, it’s a game-changer, turning scattered tutorials into a cohesive ML foundation.

Beyond the Beta

In the last week of March, I received an email from the Manus AI team thanking me for being an early adopter and offering some perks. I used the extra credits wisely for another research project. I haven't tried the mobile app yet but will review it soon.

Overall Conclusion

After spending a few weeks with Manus AI, I'm convinced we're witnessing a shift in how AI agents can supercharge our productivity. What would've taken me days of scouring through countless tutorials and documentation- creating a comprehensive learning resource; was accomplished in just a few hours. It's mind-blowing!

Sure, there are valid ethical concerns about AI automation, and we should address them. But my experience shows that when used thoughtfully, these tools can be incredible accelerators for learning and productivity. They're not replacing human understanding; they're amplifying it.

Major props to the Manus AI team for crafting such a powerful yet intuitive tool. The attention to detail, from the clean interface to the thoughtful 'Suggested Knowledge' feature, shows they really get what users need. Despite being in beta, it's already impressive, and I'm excited to see how it evolves.

Will I keep using Manus AI? Absolutely! It's become an invaluable part of my learning toolkit. For students like me, it's not just a tool-it's like having a super-smart study buddy who never sleeps. Can't wait to see what other adventures await!

GitHub Link

For those interested, here is the GitHub repository containing the full project and resources related to the data science libraries I’ve been learning about. Feel free to check it out!

Thanks!

Thank you for reading about my journey with Manus AI! If you found this helpful or have your own experiences to share, I'd love to hear from you. Let's keep learning and growing together :)