Introduction
Let’s dive into the hottest topic in the AI world right now – a groundbreaking autonomous agent called Manis. If you’ve been following AI trends lately, you’ve probably heard terms like “GPT moment,” “DeepSeek moment,” “intern that never sleeps,” or “the universal hand” floating around. All these buzzwords are referring to this innovative product from a Chinese startup called Monica, and trust me, it’s been dominating social media and tech websites over the past few days.
What Exactly Is Manis?
In simple terms, Manis is being hailed as the world’s first truly general AI agent. Sure, we have plenty of AI assistants and chatbots out there that can answer questions, generate text, or offer code suggestions. But Manis supposedly takes everything to another level by actually planning tasks, executing them, and delivering final results. Think of it as an intern who doesn’t just brainstorm ideas but also handles all the grunt work for you – from writing code to browsing websites and analyzing data.
Manis is developed by Monica (website: monica.im), and is described as your “universal hand.” If you’re wondering about the name, “mens et manus” from Latin means “mind and hand,” which perfectly captures the philosophy behind the product. Knowledge shouldn’t just stay in the AI’s brain – it should be actively used to achieve results in the real world.
The Overnight Sensation
How did Manis suddenly become so famous? On March 6th, 2025, Monica officially launched an early preview that triggered a massive wave of people staying up all night just to get an invitation code. No joke – some folks even tried reselling codes on various secondhand platforms for anywhere from 999 Yuan (around $137 USD) to a mind-blowing 100,000 Yuan (nearly $14,000 USD). Most codes were being resold for at least several hundred or a few thousand dollars, all because demand exploded faster than the team anticipated.
What Makes Manis Special?
The excitement stems from Manis’s advanced capabilities. According to the official site, it features a multi-agent structure – essentially different sub-agents inside the system handle distinct parts of a task. One agent might handle planning, another might take care of execution (like writing a Python script or visiting specific websites), and yet another might verify the accuracy of results. This multi-agent collaboration supposedly mirrors how human teams work – one person strategizes, another codes, and so forth. The synergy between these sub-agents is apparently what allows Manis to tackle complex tasks.
We’re talking about everything from screening résumés for job openings to analyzing real estate listings based on income and neighborhood preferences, or analyzing stock data from multiple companies and building dashboards or summarizing entire financial statements.
In one demonstration, a user needed to find a house in New York with a safe community, good school district, and a price matching their budget. Manis systematically searched for safety data online, looked up property prices, performed budget calculations using Python scripts, and finally presented a polished report with recommended properties. That’s way beyond a simple chatbot answer – it’s an entire workflow ending with a finished product.
People have also tested Manis by having it:
- Plan a trip to Japan in April
- Perform thorough Tesla stock analyses
- Create interactive course materials for middle school teachers
- Compile lists of B2B companies from YC’s W25 batch
And Manis doesn’t just provide bullet points – it can write code, generate visual dashboards, and organize everything in tables or Excel documents if that’s what you prefer.
The Team Behind Manis
Monica was founded by Xiao Hong, a serial entrepreneur who graduated from Huazhong University of Science and Technology in 2015. There’s also mention of a co-founder and chief scientist named Ji Zhou, who created a demonstration video that garnered hundreds of thousands of views on social platforms within about 20 hours. Another partner, Zhang Po, stated online that they’ve had to limit invites because their servers can’t keep up with demand.
Interestingly, the company underwent changes in its shareholder structure in 2024. Reports indicate that Ant Group’s venture capital arm invested in them, as did Zen Fund in July 2022. Not many official corporate structure details are available, but that’s typical for startups scaling rapidly.
The Next DeepSeek?
There’s chatter about Manis potentially becoming “the next DeepSeek.” Some are comparing January’s big moment to what’s happening now with Manis. Chinese media and social platforms are calling it “another Sputnik moment” or “another GPT moment,” referencing how ChatGPT revolutionized the world.
Regardless, Manis has made enough waves to receive coverage from outlets like Global Times, China Daily, Malay Mail, Newsweek, and more. Everyone’s connecting the dots that China has had multiple AI breakthroughs this year, from large language models to general AI agents.
Beyond Generative AI
What sets Manis apart from typical generative AI is that it’s aiming for what we often call artificial general intelligence. It obviously won’t pick up your kids from school or do your laundry in the physical world, but in the digital realm, it can handle multi-step processes that you’d normally assign to an assistant or intern.
According to some references, at least 21% of enterprises had already adopted AI agents in some capacity by January 2024. Gartner apparently predicts this number will exceed 80% by 2026, which means if Manis performs well, it’s tapping into an extremely hot market.
The potential for AI agents to fully automate tasks like B2B sourcing, analyzing Amazon store data, or preparing sales improvement strategies could be enormous for businesses. The official Manis page even demonstrates how it can research local data for a barbecue restaurant in Texas to help boost sales, or compete in Kaggle competitions by writing code that ranks in the top 10%. All these use cases are showcased in their official gallery.
The Competition Question
There’s also the question of competition. Giants like Anthropic, OpenAI, and Google have all teased or introduced agent-like systems that can do more than just talk, but we haven’t seen many workable agent demos as comprehensive as Manis right now.
All eyes are on how well Manis scales and whether it can truly deliver on this “agent of the future” promise. Only time will tell if it’s another “DeepSeek moment,” a fleeting hype train, or the next evolution in AI.
What do you think? Is Manis just a well-packaged aggregator of AI tools, or is it truly a game-changer pointing us toward a real general AI future? Thanks for tuning in, and I’ll see you all in the next one!
