This AI is FREE & Better Than GPT Operator (Manus AI Demo)

Okay, this is an incredible time to be alive. It is now possible to create an entire AI workforce who work for you around the clock and do anything you want to do. And Kip and I are going to showcase the tool that you can use today to do this for you and give you some of the best use cases that we found of Manus AI, the very first ever autonomous agent and oh wow, is it powerful.

Okay, Kieran, the entire Internet is talking about Manus and Manus is another one of the growing AI startups out of China and it is really the first real like you don't need to know how to code, you can just type in in your natural language and build a multi step agent is what we, I think what we thought OpenAI's operator was going to be. But it is actually able to deliver on that promise, right?

It's actually accurate. It's pretty fast actually compared to operator it's pretty fast and it can do a lot of work. Like think about it as you set a task and if, if it has to do data analysis, if it has to write some lightweight code, whatever it has to do to complete that task, it can actually do it. And on this episode we're going to break down how it does it and also give you some real examples that we've done and use MANAS for. So you can actually go sign up for the wait list and start to use it today. This is the incredible thing, it's not a vaporware product. You can actually start to use this today. And some of the actual use cases that I've seen and some of the use cases you run it for are pretty mind blowing.

I want to just go straight in and show everybody something I built in Mana. Shout out to the Manus team for getting me off the wait list and letting me go in and build here. So Kieran, you and I have talked a lot about in the world of AI kind of targeting and personalization and conversion rate is kind of a solved problem problem. And one of the ways I wanted to test that out is I wanted to say, hey, could I write a prompt that would basically allow Manus to be my own kind of bdr? And what I said is please identify companies and contacts at those companies that might be a Strong fit for HubSpot's product offering. These companies should be growth minded, small medium sized businesses in the United States. I would like you to do the following. I said first research, identify prospective customers for HubSpot in this research. Please return company name, contact name and any contact information and LinkedIn URL, like this is pretty complicated, right? Right.

You're basically the setup here for listeners. Obviously we're showing the actual screen is. You are giving it all of the context needed to figure out how to identify the right icp, which is your, your ideal customer profile.

Yeah, I love that. And so what we're really trying to do is give it some very precise, specific and like step by step instructions. And so like I wanted it to evaluate each of these company sales and marketing strategy, their strengths and their weaknesses. That is something like if you are an entry level salesperson, you go out and do you identify a company, you look at its website, you say hey, I think it's really good. And I say sales and marketing because that's the tools HubSpot provides. We help sellers, marketers, customer service folks. And so I did sales and marketing. It identified what those sales and marketing strengths and weaknesses are by company. Right. And then I was like, write a call script for each of those companies. If I was actually going to pick up the phone and call those companies, like what would I tell them? And then I was like, please give me all this information in a CSV file. So that's what I requested.

Right. And I think what you're showcasing is again, you still need the domain expertise to be able to guide the agent. And the better the prompt you give it, the better context you give it, the better you set it up for what the outcome is you want. And in very much the same way again you would actually manage an employee, the better your results are going to be. And that's where a lot of the skillset is going to go to, is like how to manage these agentic workflows.

Yes. And keep in mind right now I'm doing all this for free. This is, this isn't a free version of this product. Right. And so Kieran, it worked. So first of all I tried to do it a couple times and it was, the service was too busy. So one of the challenge with startups is that they have kind of more constrained capacity. Then eventually I was able to get it to work. And then here you see, it basically said, hey, I'm going to start going through these steps. And so it tells you the Steps here. Research HubSpot products, offerings and it's, it's actually browsing the Internet, it's creating files, it's executing commands, it's clicking on elements on pages. Right. So it's like, it's amazing the level of steps involved here. Like this is very complex, very multi.

Step Workflow, it can just scrape all of the websites, right? Like that's. That. That in itself is pretty cool. Like you actually have all these different tools that have built to scrape websites where menace. Menace can just go and actually background write that code and start to. It uses a tool called browser use. That's how it's navigating all these websites and pulling it into the CSV for you.

Yeah, so I think that's really cool. And so this took about 35 minutes approximately to do all of these steps which if you think about it's wild. What do you think it would take a human and ended up doing five companies? And we'll talk about that in a second. How long do you think it takes a human to do five to find do all this work for five companies?

I can tell you like that, that like the average BDR is going to spend the majority of their time doing these tasks and trying to research a company and trying to identify prob. Like product problem fit. Right? Like what is the core problems that this company is trying to solve and what are the problems that are a good map. And so this is a, the most time consuming part of that job.

It takes a ton of time. And so what it, what it actually did here Kieran is it gave us a CSV and it failed these five companies. Shout out to these companies. But basically it failed five companies. It found the CEO at each of those five companies. Cause I didn't specify who with those companies. If I were doing this like at real scale, like it's one of the things I would do is talk about the specific profile of person, right. And it got me their contact information, their LinkedIn profile. And I think what was really interesting to me about this Kieran and is the work it did to determine what were its strengths and weaknesses as it relates to the HubSpot product offering. Right. So you can see here it's like it basically created a known taxonomy of things and whether they were good or bad at it, right. So clear value proposition, emotional marketing approach, user generated content strategy, free trial option.

Right.

These are all things that were marketing strengths for these companies. Hey everyone, I want to talk about prompting with you today. Being great at prompting is like gives you superpowers. It changes how you can build and work and do everything with AI. And because of that we wanted to make a special guide just for you around how to get better at prompting framework for how you actually build prompts. And so we've got this baseline framework that you can then go and build and customize any prompts that you want to. You can check it out in the link of the description below. And right now we're going to get back to today's show.

The other thing, like for people to think about when they're following along here is just how disruptive of a force this is going to be. So what the agent is unbelievable what this agent is doing, right? To like make sure people understand what's happened here. What Manus really is, is like a. People have heard of Cursor. Cursor is this development tool that is wrapped around CLAUDE and other models. But for the most part people are using it with Club 35 to code full stack apps. And the only two things that I'm really spending my time on outside of like keeping up, up to date with this and trying to do all of the things that I do day to day in AI outside of that, it's really like Cursor and mcps. And what this really is is a cursor like equivalent for autonomous agent, which, I mean, it's like a wrapper that's built around Claude 3.5 and we're going to get into some of that and then it's extended using tools so very. We're going to do an episode on mcps this. So these model context protocols. And I'm not going to go really technical here. All, all they need, all people need to know is like, you're able to like extend these agents by giving them tools to use, right? You can say here's a bunch of tools. And so when I give you a task, you can choose whatever tools you want to use. And that's what Manus really is. It's like a wrapper around Claude. So it's built on Claude model and then it has all of these tools and then when you give it a task, it's like, it's like using all these tools. I'm going to use the browser used to scrape all this website and I'm going to use my coding tool to code something, a lightweight tool that I need. And it's really incredible to see just how much, how many tasks it can get through in such a short amount of time. And the other thing I was pretty impressed by is number one, how fast it is. Like much, much faster than I think OpenAI's operator. I'm sure they will scale it up pretty rapidly. And then the second thing is just how accurate it is. And so the reason I like my original point here is how disruptive this is. And so let's say there's all these kind of data source tools and, and today you have all these data source providers and you would have to go and you would have to say to these data source providers, I'm looking for these kind of people in this kind of market that I can solve this problem for. You can easily extend Manus by giving us more tools and then you actually have the equivalent now in that agent because it can call, it can scrape all of the stuff on the web, you give it some access to other data sources and can pull all that in. You have your own kind of like data provider, right? And for B2B now you can build your own kind of little data provider that actually gives you all of the ideal customer profiles that you need to actually market to. And I think that's what you originally said was like we believe marketing is going to become, I believe marketing is going to change from like a very volume centric play, how we acquire lots of things to a very like value. How do you target.

Yes.

Get very, very targeted and how do you like really over deliver for those people to way increase your conversion rates completely?

Because the magic here and what this Atmanis did for free was it told it found these companies, found the right person at this company, then found out what the strength and weaknesses were for this company as it relates to HubSpot's products, right? And so you have some, some weaknesses here. Limited lead generation tools, limited pricing, transparency, the blog organization is a weakness. Limited enterprise positioning, limited nurture lead nurturing visibility. These are all things that if you are selling a marketing tool you want to understand, right? Like it's amazing, pretty incredible. The thing that really blew my mind Kieran is it went and it found out these weaknesses and then it went and looked at HubSpot's product pages to figure out what HubSpot products map to those weaknesses.

And I can tell you that because we have such a broad product set that is also a very tough, that's a hard problem for sales. And so what it picked up when I looked through your results, it picked up things that were kind of interesting, right? It said hey, this, this company do not have a blog. This company has not posted many blog posts so they're not leaning into content marketing. It actually picked up that this company had a couple of 404 so it's scraping their website, right? And actually that is just bananas. And so it's able to like take all of the website, use that as data to say well here are, here's my assessment, like here's my grade. And then based upon their weaknesses, it did a pretty good job of not only pattern match into the right HubSpot, the right HubSpot kind of product at its first attempt. Right. You didn't. This is no revision.

This is, this is one shot.

And then, and then, and then did pricing and then created a pretty good pitch. That alone is an entire couple of days of work.

Yeah. I mean if you're really good at this work, what this did would have taken, would have probably taken you two hours. And if you're like top level and.

You have 35 minutes, you reduce like that and then this thing.

And that wasn't active. It's not like I was doing things for that 35 minutes is doing something else.

And that's one instance of madness I would, I would challenge people to think about when you have. I want to show you this, actually I can show you a quick screen just to like just this one because it's just like bananas to think about. Like this is actually, I think one of the best visuals and just how wacky things are going to become. So this is my point. You're showing a single.

Oh, I love this.

You're showing a single agent doing a task and it looks pretty cool. What I'm showing on my screen is 50 instances of manus all running different social media. All running different. Yeah. Social media accounts. And so there's no reason you can't have a hundred. There's no reason you can't have a company of 10,000 people that are always doing this work. It is like incredible to think about. And Manus, for me, the operator, I don't know what you felt like, but when I used OpenAI operator, I thought it was like cool. But you couldn't really grok how powerful it seemed to be.

It didn't feel like it had any scale or power to it.

But this is the first, this is the first time where you're like, holy smokes. If I have a bunch of these things running, the amount of work get.

Done, I can do 10x100x in a day.

The, the other one I want to show you before you get into your other example because it's the, the. The thing I'm obsessed about is the re. The reverse of what you're showing. So let me show what I mean by that.

Oh, please.

So what we, what we. What we think about a lot, obviously because we're in marketing is the, our ability to better market to people who want to buy B2B software. What I am really obsessed about is the B2B's buyer, the B2B's buyer ability to use agents to not have to do any of the buying themselves. Because that to me is more transformational than the reverse of that.

Right. I couldn't agree more.

And so this is a really good example of what I mean. So this is Manus. And what I believe happens in the future is you don't touch anything that exists on the web today to actually choose software. You get it all built for you in a personalized way. So the example I'm going to show here is Manus is going to build a aggregator because with the thing for, for rubber mats. And the thing I really care about is the price, right. So I actually want to build my own recommendation engine that is allows me to like, like my own, my own recommendation engine, like my own kind of G2 crowd for rubber mats. And I can actually sort it based upon price. And so what it's going to do here, I'm going to go to the end because like people saw your example, I could see it, it's running through all sites. But I want to get right to the end to show you what it's built. So this here you can see on the right hand side, it's basically built this whole app. And this app now allows me to sort through the suppliers that I'm trying to find in a very customized way based upon what my core criteria.

Bananas.

So think about it. If you were buying any software, I can say I care about A, B, C, D and E. Now build me an aggregator app that aggregates them all together and allow me to like, I can, I can look through it based on user reviews. I can look through it based upon whatever I want to do. And not only that, I actually think you're going to be able to get Manus to go in and actually do the trial. Yeah, like sign in, use the software. Tell me, does it do A, B and C? And you can actually ingest that back into the app. That to me is pretty wild. Like I can't wait to actually start to use this to try to build some product sites that I can actually choose what products I want to buy based upon a custom site built for me. I never have to touch the vendor site only to actually complete the transaction.

I mean, I don't. Are we ready for this?

I think this year is. I don't know what you think we're, you know, we're.

I think a decade happens in this year.

We're only in March. I think things are moving. It's the first time I think things are moving too fast. I actually need someone to just, like, say, can I just learn? Can I just finish my cursor course and build my MCP servers before you release any more stuff? Because I just can't keep up.

You and I are. I would call us hyper learners.

Yeah.

Like, we're obsessive learners. And this is.