When I compare this to my experiences with Operator or other AI helpers: Operator might have been able to do the browsing steps too, but I suspect it would have needed a bit more hand-holding. For example, Operator might have asked me which listing to click next if it wasn’t confident. OpenAI even says Operator will “hand control back to the user” if it gets stuck – a nice safety feature, but it means more interruptions. Manus, conversely, **didn’t hand control back at all during this task. It just powered through the entire process, acting like a truly autonomous agent.
There was one moment I held my breath: on Bezrealitky, after translating the page, Manus had to click a drop-down. It hesitated a second or two (I could see the cursor wiggle as if unsure), but then it selected “Prague” from the region menu and pressed on. That felt so human – a tiny pause to think, then “oh okay, I’ll do this.” It was a glimpse of the “agentic capabilities” that AI researchers have been hyping about Manus – the ability to figure out multi-step tasks on its own. One researcher called Manus “the most impressive AI tool I've ever tried... The agentic capabilities are mind-blowing, redefining what’s possible.” Watching it in action, I started to agree.
Where Manus Struggles: The Not-So-Perfect Moments
Alright, it wasn’t all rainbows and unicorns. Manus is impressive, but not infallible. In my apartment hunt session, I noticed a few hiccups and limitations that remind you this tech is still brand new (and occasionally too good to be true). In the spirit of a fair review, let’s talk about where Manus stumbled:
Repetition and Loops: After giving me the initial list of five apartments, I wanted to see how it would handle follow-up queries, so I asked, “Great, can you email the landlords to schedule viewings for the top 2 options?” This is where things went a bit haywire. Manus definitely tried – it went back to the browser, clicked the first listing, and looked for contact info. But I suspect the site required a login to reveal the landlord’s email, and Manus got a bit stuck. It started refreshing the page a couple of times, almost like it was in a loop trying to find something it couldn’t access. After a minute or two, it apologized and gave a somewhat generic error message. So, contacting landlords autonomously was a bridge too far (for now). I had to step in at that point. This aligns with some reports from other users who pushed Manus on complex multi-step tasks and saw it “fell into loops, and sometimes failed at executing what was required.” It’s a known issue that when an agent doesn’t have a clear path, it might spin its wheels.
Missing obvious details: While the summary list was great, I did catch a small mistake. One apartment was listed as “2 bedrooms” in the summary, but when I clicked the link, it was actually a 1-bedroom with a living room (which local listings count differently). Manus had misinterpreted the Czech listing term “2+1” as two bedrooms, whereas it really means one bedroom + one living room. A human familiar with the local terminology wouldn’t mix that up. This shows Manus can miss some context or nuance – it’s powerful, but not omniscient. A reviewer of Manus noted that it can still “make mistakes or miss obvious details”, which is exactly what happened here. Not a deal-breaker, but a reminder that you can’t blindly trust the AI’s output without double-checking important facts.
Not-so-great at creative or interpersonal tasks (yet): Out of curiosity, I also asked Manus during the session to draft a nice email in Czech to introduce myself to a potential landlord (after it had provided the listings). The email it generated was polite but a bit awkward – definitely not as smooth as something like ChatGPT might produce in terms of tone. It got the job done, but felt a tad robotic. It seems Manus’s strength is in the action-oriented “agent” stuff (browsing, scraping, collating info), whereas for pure writing or nuanced communication, it’s just okay. One AI commentator on Twitter observed that Manus excels at things like trip plans or general research, but for coding or more complex reasoning it might perform “worse than googling. More LLM than agent.” In other words, it’s optimized for certain tasks and not a master of all trades. My experience echoes that – superb at automating web-based tasks, a bit less remarkable at free-form dialogue or creative output.
Occasional interface quirks: Since Manus is in beta, the interface had a couple of bugs. At one point the browser view froze (even as Manus presumably kept working). I had to refresh my page, which fortunately didn’t stop the agent. But if you’re not somewhat tech-savvy, that might freak you out (“Ah! Did I break it?!”). I also noticed a slight delay in the chat response updating after the web actions – like Manus was very careful to finish all browsing before telling me the results, which is fine, but you don’t get streaming updates. In contrast, Operator provides a step-by-step rundown of what it’s doing as it does it (with reasoning steps visible). Manus keeps its cards closer to its chest until it has an answer. Different design philosophies: OpenAI wants the user in the loop for transparency, whereas Manus leans into the “agent takes care of it” feeling.
Given these flaws, I wouldn’t say Manus is ready to completely replace my own decision-making or double-checking. It got me 90% of the way on the apartment search, but that last 10% still required me to verify details and handle the final communication. And that’s okay – it is a beta product after all. As one early adopter wrote, “Manus isn’t ready for full-scale business use...instead, test it out to see where AI agents are headed.” That resonates – I approached Manus as an experiment, not a guaranteed solution. In a mission-critical scenario, I’d keep a close eye on it. But for a personal apartment hunt, it was a fantastic assistant despite the rough edges.
What Other Users Are Saying: Hype vs. Reality
After my session, I was curious: was my experience typical? Are others getting similarly great results with Manus, or did I just witness a bit of beginner’s luck? So I dove into some online discussions and found a mix of euphoria and skepticism surrounding Manus.
On the positive side, plenty of tech enthusiasts are absolutely blown away. I already mentioned Andrew Wilkinson’s “time traveled six months into the future” comment – and I felt that vibe too. Another AI researcher, Victor Mustar, gushed that “Manus is the most impressive AI tool I've ever tried. The agentic capabilities are mind-blowing, redefining what's possible.” Clearly, Manus made a strong first impression on those who tried it. These folks highlight how Manus can autonomously navigate and execute tasks that we usually associate with human internet users. There’s a sense that “wow, this is what we imagined future AI would be like.” Even tasks like complex trip planning or deep-dive research – Manus has been shown to handle them with relative ease, which for many was unheard of just months ago.
However, not everyone is singing unqualified praise. For instance, I came across some commentary from users in China (where Manus originated) who felt the hype was a bit manufactured. There were claims that Manus’s team drummed up excitement via influencers, leading to an inflated perception of its abilities. While I can’t verify those claims, it’s a reminder that in the age of viral tech, sometimes the marketing runs hotter than the product. A few AI developers dug into how Manus works and found that it’s not an entirely new magical brain, but rather a clever orchestration of existing AI models. In fact, Manus’s founder admitted they use Anthropic’s Claude (a well-known large language model) along with a fine-tuned Alibaba Qwen model to power the agent. In plain terms, Manus is like a super-skilled project manager coordinating known specialists, rather than a brand-new genius itself. This led some to call it just a “wrapper” around other models. One commenter, perhaps a bit salty, tweeted that after trying Manus they felt it was “optimized for influencers… More LLM than agent” when it came to real hard tasks.
So, is Manus overhyped? From my hands-on time with it, I’d say it largely delivers on its promises for the right kinds of tasks, but it’s not infallible and not yet a replacement for careful human oversight. The hype is understandable – using Manus really did wow me – but the skepticism has merit too. We’re still in early days, and as with any beta tech, some things will be flaky. I got lucky that my project (apartment hunting) is exactly the kind of thing Manus is currently great at: web research, data gathering, multi-step planning. If I had asked it to, say, debug a complex piece of code or make high-level business decisions, I suspect the outcome would be less stellar.
What’s encouraging is that even those who point out Manus’s flaws aren’t denying its potential. They’re basically saying, “Yes, it’s built on existing tech, yes it can mess up, but it’s still a pivotal step forward.” And I agree. The fact that an independent developer (or a small startup) combined these models and tools into an agent that outperforms what the big players have publicly released is telling. In one benchmark test (the GAIA agent benchmark), Manus reportedly achieved state-of-the-art results across various task difficulty levels, outscoring OpenAI’s own agent by a wide margin. That’s a big deal – it means this approach to AI agents is working and pushing boundaries.
Bigger Picture: AI Agents Are Improving Fast – What’s Next?
My evening with Manus left me both excited and contemplative. If today an AI can handle apartment hunting (mostly) autonomously, what will these agents be able to do in just a few more months? The pace of improvement in AI right now is insane. It genuinely feels like every few weeks there’s a new breakthrough. Just half a year ago, tools like AutoGPT were fumbling through simple tasks, getting stuck constantly. Now I have Manus, which feels like a competent intern. Extrapolating forward, I can’t help but imagine a near-future scenario where AI agents become seamless problem-solvers for a wide range of complex tasks.
One obvious example that comes to mind is tax preparation. I dread doing taxes – it’s paperwork-heavy, requires fetching documents, cross-checking numbers, and using clunky software. I bet that an AI agent akin to Manus will soon be able to take on something like, “Hey AI, here are my financial documents, please file my tax return.” It would sort through PDFs, figure out the forms, maybe even e-file on your behalf. Sound far-fetched? Perhaps, but so did an AI renting apartments on my behalf not long ago. Given how fast these systems are evolving, this vision might be closer than we think. In fact, after seeing Manus in action, I’d say I trust an AI agent to at least draft my tax return for review. The agent could gather all the relevant info, fill out the forms, and flag any uncertainties for me to finalize – saving me a ton of grunt work.
The implications go beyond personal convenience. Think about business tasks: market research, competitor analysis, customer support, scheduling logistics. We’re inching towards a world where you can delegate such tasks to an AI agent and expect competent results. One investor described Manus as having “Deep Research + Operator + Computer Use + Memory” all in one – basically an amalgam of multiple expert systems. That’s like having an analyst, an assistant, and a librarian in one digital entity. And this is just today’s capability.
If Manus is a glimpse of mid-2025 tech, by the end of 2025 we might see refined versions (maybe from OpenAI, maybe from others or open-source projects) that iron out the kinks we discussed. The occasional loops and mistakes could be reduced as the models learn from more interactions. Safety will improve too, so they know when to stop or ask for help in truly risky situations. There’s already an open-source effort called OpenManus aiming to replicate Manus’s abilities without the invite gatekeep. Competition and community innovation tend to accelerate progress. I wouldn’t be surprised if by then, tasks like “find me the best home, negotiate the rent, and arrange the move” become one-shot requests to your AI agent.
However, a dose of caution: as these agents become more capable, we’ll need to trust but verify. Just like I had to double-check that listing detail or eventually handle the landlord contact myself, we’ll always need a human in the loop for important decisions, at least in the foreseeable future. The goal is not to drop our guard, but to raise our productivity. From what I’ve seen, we’re well on our way. As one observer put it, even if Manus is using older underlying models, “that doesn’t mean it isn’t good” – in fact it delivered impressive results by smart integration. The trend is clear: each iteration of these agents gets better at understanding our intentions and carrying out tasks. We’re watching a new kind of software emerge – not just a static program, but a dynamic assistant that learns and adapts.
In practical terms, I’m already thinking of other errands I could offload to an AI agent. Apartment hunting in Prague? Check. Next up, maybe planning the actual move – finding moving companies, getting quotes, scheduling the move date. Or how about handling all the address change notifications and paperwork once I do move? These are boring, multi-step tasks that I’d love to hand over. If not Manus, perhaps a similar agent will handle it soon. And if I project a bit further: booking complex travel itineraries, doing a year’s worth of expense reports, researching the best school options for your kids, you name it – an advanced AI agent could tackle it.
We truly are, as Wilkinson said, time-traveling a bit into the future with these tools. The experience of using Manus was a sneak peek at what everyday life with AI assistants might be like. It’s not perfect yet, but it’s rapidly getting there. As someone who’s been following AI for years, this was the first time I felt “Wow, I could get used to this” about delegating a personal task to an AI.
Conclusion: A Personal Takeaway
Wrapping up my experience – did Manus find me my dream Prague apartment? Not exactly on its own, but it gave me a darn good head start. I ended the night with a solid shortlist of places to check out and a newfound appreciation for how far AI has come. Manus proved to be better than Operator (and most other agents I’ve tried) in one crucial way: it actually did the thing, with minimal fuss. The independence and competency it showed made it feel less like a chatbot and more like an actual assistant working for me. That’s a game-changer.
Of course, Manus isn’t a silver bullet. It had its fails and “huh?” moments, and it’s still a bit of a black box at times. But the beautiful part of this story is that those failures were learning moments – both for me and, presumably, for the developers who are improving the agent. Even with occasional loops or errors, the net benefit I got was huge. Instead of spending my whole evening on ImmobilienScout24 or Sreality, I let the agent handle the drudgery. I could then spend my time making the final judgment calls (like deciding which landlord to call first, or verifying pet policies).
Comparing Manus to Operator, it’s clear that Manus’s autonomous approach spoiled me. Going back to a more hand-holdy tool would feel cumbersome now. It’s like switching back to manual transmission after driving an automatic – sure, you can do it, but why would you if the automatic is good enough? Operator, as OpenAI positions it, is carefully constrained and asks for user input to stay safe and aligned. Manus in its beta form took the leash off a bit more. That came with a couple of scrapes (nothing too bad in my case), but also with a lot more ground covered. For a personal project like mine, I appreciated that trade-off. In a regulated industry or critical task, you’d want the safety nets – but for apartment hunting, I was happy to let Manus be bold.
In the broader sense, this experiment made me optimistic. If today’s AI can handle tasks like these, tomorrow’s AI (literally tomorrow, or a few tomorrows from now) will handle even more. We’re on the cusp of something really exciting where “AI agents” go from demo-worthy to actually useful in daily life. The moment I realized I could trust Manus to scour the web for me was the moment I glimpsed how my workflow might change in the near future. It’s not about AI taking over our jobs; it’s about AI taking over the boring parts of our jobs (and lives), so we can focus on the parts that truly need the human touch.
Standing here, with a list of Prague apartments in hand that an AI fetched for me, I can’t help but smile. The future arrived a bit early in my living room tonight. And you know what? I could get used to this kind of help. Here’s to Manus, and all the rapidly evolving AI agents – may they continue to learn, improve, and perhaps make finding my next apartment (or doing my next tax return) as simple as asking for it. After all, if an AI can tackle the Prague rental market without breaking much of a sweat, who knows what else it’ll be capable of by the time I actually move. Exciting times ahead, indeed!
Sources:
- OpenAI, Introducing Operator – details on Operator’s design as a collaborative agent.
- Decrypt, China's Manus AI Challenges OpenAI's $200 Agent – background on Manus, user reactions (Wilkinson’s “time traveled” quote, others praising mind-blowing capabilities), and reported issues (loops, failures).
- Exponential View, What’s the deal with Manus? – hands-on insights comparing Manus with Claude’s “Computer Use” and OpenAI’s Operator, noting Manus’s strong execution but occasional mistakes.
- Twitter user feedback via Decrypt – both hype (e.g. “most impressive AI tool… agentic capabilities are mind-blowing”) and skepticism (“fell into loops… more LLM than agent” critiques).
- Manus official site – tagline and claims that Manus “excels at various tasks… getting everything done while you rest.”, illustrating its goal of true autonomy.
- Personal observations from testing Manus on a Prague apartment search, March 2025 (as described above).
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