You need to use Manus

What is Manus - agentic AI

Manus is an AI agent capable of performing a number of high-level tasks that previously could only be done by humans. For example, it can research an area (e.g. a machine learning method) and produce an intelligible report, it can even turn a report into an interactive website. You can get started on it for free.

It created a huge fuss on its release, and rightly so. The capabilities it offers are ground-breaking. We're now a few months later and it's got even better.

In this blog post, I'm going to provide you with some definitions, show you what Manus can do, give you some warnings, and provide you with some next steps.

If you want to get an invitation to Manus, contact me.

How it works 

We need some definitions here. 

An LLM (Large Language Model) is a huge computer model that's been trained on large bodies of text. That could be human language (e.g. English, Chinese) or it could be computer code (e.g. Python, JavaScript). An LLM can do things like:

• extract meaning from text e.g. given a news article on a football match, it can tell you the score, who won, who lost, and other details from the text
• predict the next word in a sentence or the next sentence in a paragraph
• produce entire "works", for example, you can ask an LLM to write a play on a given theme.

A agent is an LLM that controls other LLMs without human intervention. For example, you might set it the task of building a user interface using react.js. The agent will interpret your task and break it down to several sub tasks. It will then ask LLMs to build code for each sub task and stitch the code together.  More importantly for this blog post, you can use an agent to build a report for you on a topic. The agent will break down your request into chunks, assign those chunks to LLMs, and build an answer for you. An example topic might be "build me a report on what to do during a 10 day vacation in Brazil".

Manus is an agentic AI. It will split your request into chunks, assign those chunks to LLMs (it could be the same LLM or it could be different ones depending on the task), and combine the results into a report.

An example

I gave the following instructions to Manus:

You are an experienced technical professional. You will write a report explaining how logistic regression works for your colleagues. Your report will be a Word document. Your report will include the following sections:

* Why logistic regression is important.

* The theory and math behind it.

* A worked example. This will include code in Python using the appropriate libraries.

You will include the various math formula using the correct notation. You will provide references where appropriate.

Here's how it got started:

After it started, I realized I needed to modify my instructions, here's the dialog:

It incorporated my request and did add more sections.

Here's an example of how it kept me updated:

After 20 minutes, it produced a report in Word format. After reading the report, I realized I wanted to turn it into a blog post, so I asked Manus to give me the report as a HTML document, which it did. 

I've posted the report as a blog post and you can read it here: https://blog.engora.com/2025/05/the-importance-of-logistic-regression.html

A critique of the Manus report

I'm familiar with logistic regression so I can critique what Manus returned. I'd give it a B+. This may sound a bit harsh, but that's a very credible result for 20 minutes of effort. It's enough to get going with but it's not enough of itself. Here's my assessment.

• Writing style and use of English. Great. Better than most native English speakers.
• Report organization. Great. Very clear and concise. Nicely formatted.
• Technically correctness. I couldn't spot anything wrong with what it produced. It did miss important stuff out though and did have some oddities:
• Logistic regression with more than two target variables, no mention of it.
• Odds ratio can vary from from 0 to +\(\infty\) but it didn't mention it. This is curious as it pointed out that linear regression can vary from -\(\infty\) to +\(\infty\) in the prior paragraphs.
• Too terse description of the sigmoid function. It should have included a chart and it should have had a deeper discussion of some of the relevant properties of the function.
• No meaningful discussion of decision boundaries (one mention in not enough detail).
• Formula. A curious mixed bag. In some cases, it gave very good formula using the standard symbols and in other cases it gave code-like formula. This might be because I told it I wanted a Word report. By default, it uses markdown and it may be better to keep the report in markdown. It might be worth experimenting telling it use Latex for formula.
• Code. Great.
• References. Not great. No links back to the several online books that talk about logistic regression in some detail. No links to academic papers. The references it did provide were kind of OK, but really not enough and overall, not high quality enough.

To fix some of these issues, I could have tweaked my prompt, for example, telling it to use academic references, or giving it instructions to expand certain areas etc. This would cost more tokens. I could have told it to use high-effort reasoning which would also have cost me more tokens. 

Tokens in AI

Computation isn't free and that's especially true of AI. Manus, in common with many other AI services, uses a "token" model. This report cost me 511 tokens. Manus gives you a certain number of tokens for free, which is enough for experimentation but not enough for commercial use.

What's been written about it

Other people have written about Manus too. Here are some reviews:

• https://www.technologyreview.com/2025/03/11/1113133/manus-ai-review/
• https://www.techradar.com/computing/artificial-intelligence/i-compared-manus-ai-to-chatgpt-now-i-understand-why-everyone-is-calling-it-the-next-deepseek

Who owns Manus

Manus is owned by a Chinese company called Monica (also known as Butterfly Effect AI) based in Wuhan.

Some cautions

As with any LLM or agentic AI, I suggest that you do not share company confidential information or PII. This includes data, but also includes text. Some LLMs/agents will use any data (including text) you supply to help train their models. This might be OK, but it also might not be OK - proceed with caution.

Before you use any agentic AI or an LLM for "production" use, I suggest a legal and risk review.

• What does their system do with the data you send it? Does it retain the data, does it train the model? Is it resold?
• What does their system do with the output (e.g. final report, generated code)? 
• Can you ask for your data to be removed from their model or system?

What this means - next steps

These types of agentic AI are game-changers. They will get you information you need far faster and far cheaper than a human could do it. The information isn't perfect and perhaps you wouldn't give it an A, but it's more than good enough to get started and frankly, most humans don't produce A work.

If you're involved in any kind of knowledge work, you should be experimenting with Manus and its competitors. This technology has obvious implications for employment and if you think you might be affected, it behoves you to understand what's going on.

If you want to get started, reach out to me to get an invitation to Manus and get extra free tokens.