Manus AI. Agents at work

You've probably heard the phrase "AI agent" thrown around a lot lately. Most of the time, what people mean is a chatbot that can search the web or write code when you ask it nicely. Manus is something a bit different — and when it launched in March 2025, it caused enough of a stir that people started calling it "the second DeepSeek moment." Big claim. So what's actually going on?

What Manus Actually Is

Manus (the name comes from the Latin word for "hand") is an autonomous AI agent. The difference between Manus and something like ChatGPT isn't subtle — it's architectural.

When you give ChatGPT a task, it gives you an answer. When you give Manus a task, it goes and does it. You could type "research the top five competitors for my product, analyse their pricing, and build me a presentation" — and Manus will open a browser, search the web, read websites, write code, create files, and hand you back a finished presentation. All while you do something else.

This distinction — from answering to doing — is why it got so much attention so fast. One early user described giving it a zip file of 20 job applications for a CEO role. Manus went off, researched each candidate individually across the web, and came back with a deep-dive report on all 20. That kind of thing used to take hours.

Under the hood, Manus runs a team of specialised mini-agents — one focused on planning, one on browsing, one on writing code — that coordinate together rather than relying on a single AI model doing everything at once. It's built on top of Anthropic's Claude and fine-tuned versions of Alibaba's Qwen model, so it's not actually a new AI model itself. It's a very clever coordination layer on top of existing ones.

A Real-World Example That Shows What It Can Do

Here's a use case that shows exactly where Manus shines. I needed to build a complete picture of vet clinics across an entire state — how big each clinic was, whether it was part of a larger group, and who the key decision makers were at each one. That's the kind of task that would normally mean days of manual research: finding clinic websites, reading about-pages, cross-referencing group ownership, tracking down contact names. The kind of work you'd normally hand to an intern with a spreadsheet and a lot of patience.

Manus handled it in one go. It went off and found the clinic websites, gathered the information for each one, stored it in a structured database, and then generated a web page to present the whole thing in a clean, usable format. The output was better than expected — comprehensive, well-organised, and ready to use. No step-by-step instructions needed. Just the goal, and then results.

That's the thing Manus does that nothing else quite matches yet: it doesn't just research and report, it builds something from what it finds. The combination of browsing, data collection, and delivering a finished output in one workflow is genuinely different from anything you'd get from ChatGPT, Perplexity, or Claude on their own.

How Its Research Actually Works

One of the things Manus is most used for is deep research — and it's worth understanding how this differs from a standard AI search.

When you ask a regular chatbot a research question, it either draws on its training data (which has a knowledge cutoff date) or does a quick web search and summarises what it finds. Fast, but shallow.

Manus approaches research more like a human researcher would. You give it a topic, and it:

1. Plans out what it needs to find and in what order

2. Browses multiple websites, reading actual page content rather than just scanning headlines

3. Cross-references sources and adjusts its search strategy as it goes

4. Handles obstacles — if it hits a login wall or a CAPTCHA it can't solve, it flags it and asks you to step in

5. Delivers a structured, downloadable report — usually as a Word doc or PDF you can edit straight away

The transparency here is genuinely useful. There's a feature called "Manus's Computer" — a live window where you can watch the agent working in real time, see which websites it's visiting, and step in if something looks off. Unlike some tools that quietly skip blocked sources without telling you, Manus surfaces problems and asks for input.

How It Compares to the Big Players

Here's the honest competitive picture:

OpenAI's Deep Research — More thorough for serious research. Think detailed analyses citing hundreds of sources. But it's slow (sometimes 30+ minutes per report), more expensive per task, and only gives you text. Not great for tasks where you need a finished deliverable.

Perplexity Deep Research — The fastest of the three. Excellent for quick, well-sourced summaries with citations. But it stops at the research stage — it won't build you a presentation, write code, or create a file. Research without the "doing."

ChatGPT Operator — OpenAI's browser-controlling agent, theoretically similar to Manus in ambition. But in real-world testing it gets stuck, fails silently when it hits blocked content, and needs more hand-holding. Multiple independent testers rated it below Manus on complex tasks.

Anthropic's Claude with Computer Use — Better coding quality and fewer privacy concerns, but less autonomous for full end-to-end workflows.

The honest verdict: if your task is just research, Perplexity is faster and cheaper. If you need a deeply written analysis, OpenAI's Deep Research is more thorough. But if you need something done — a file created, a website deployed, a structured database built — Manus is currently ahead of the pack.

The Big News: Meta Bought It (And It's Getting Complicated)

In December 2025, Meta (the company behind Facebook, Instagram, and WhatsApp) acquired Manus for over USD $2 billion. By February 2026, the integration had already started — Meta rolled out Manus inside its Ads Manager, positioning it as an AI work partner to help advertisers automate data analysis and report generation.

The roadmap reportedly includes deeper integration into WhatsApp (imagine telling it to research and book a holiday), Instagram, and Facebook Marketplace. Mark Zuckerberg described the acquisition as part of building "personal superintelligence" — AI that can act on your behalf, not just answer your questions.

There are two complications worth knowing about, though.

The first is regulatory. China's commerce ministry has deepened its investigation into the acquisition, concerned that technology developed by the Manus team while based in China may fall under export control regulations. Manus was originally founded in China before relocating to Singapore — and Beijing isn't happy about the move. The most likely outcome is a longer approval process and potential conditions on how Manus technology can be used, rather than a full block, but it's an ongoing situation as of February 2026.

The second is a customer trust issue. When the Meta acquisition was announced, a meaningful number of existing Manus users left. Some were uncomfortable with Meta's history of data use. One CEO who described Manus as his favourite agentic AI tool said his company stopped using it the moment the deal closed. If data privacy is a concern for your organisation, it's worth factoring in before you commit to a subscription.

What Users Actually Think

The gap between the demo experience and the daily-use experience is genuinely wide.

The enthusiastic: Users who give Manus the right tasks are impressed. Research compilation, competitive intelligence, data analysis, building simple web apps, creating presentations from raw data — for these, it's a real time-saver. The ability to watch it work in real time and jump in when needed feels meaningfully different from other tools.

The frustrated: The pricing model has caused real anger. Manus runs on a "credit" system where every action the agent takes costs credits — and there's no way to know how many credits a task will use before you start it. Some users burned through an entire month's credit allocation on a single task and ended up with nothing usable. Trustpilot reviews include multiple billing complaints: charges after cancellation, unexpected plan upgrades, and credits draining mid-task with no usable output.

The honest limits: Manus struggles with paywalled content (anything behind a login), creative writing, and serious software development without close review. One tech reviewer described it well: an "enthusiastic intern" — capable, but needs oversight before anything goes near production.

Pricing: What You're Actually Getting

• Basic — ~USD $19/month, good for testing and light personal use

• Plus — ~USD $39/month (realistically covers around 4–5 complex tasks)

• Pro — ~USD $200/month for heavier workloads

Credits expire monthly with no rollover. Complex tasks can drain them faster than you'd expect, and there's no upfront cost estimate before you run a task. The Plus plan can be consumed in a day if you're running ambitious tasks. Worth knowing before you commit.

Should You Try It?

Manus does something genuinely useful that the big Western AI tools haven't nailed yet — it closes the loop between "here's my goal" and "here's the finished thing." The vet clinic example above is a good illustration: not just a list of results, but a structured dataset and a web page to present it, all from one instruction.

It works best for:

• Open-web research that produces a downloadable report

• Tasks that combine research and building something — a web page, a structured database, a presentation from raw data

• Repetitive intelligence-gathering — competitive research, market mapping, data collection across multiple sources

• Tasks you can hand off and check back on later

It's not the right tool for anything behind a paywall, high-quality creative work, or software going anywhere near production without careful review.

If you want to experiment, the free tier gives you 300 credits per day — and if you sign up using this referral link you'll get an extra 500 credits to play with, which gives you a much better chance to actually put it through its paces before deciding if it's worth paying for. Start with a clearly scoped task on publicly available information, watch the "Manus's Computer" window, and you'll get a quick read on whether it fits how you work.

One thing to keep an eye on: as Meta's integration deepens through 2026, the product available on manus.im may look quite different by the end of the year. Whether that's a good thing depends a lot on how you feel about Meta's approach to data — and that's a fair question to sit with before you hand this tool access to your research tasks.