WEBVTT

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We all have that feeling, right? The execution

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gap. You get an idea maybe in the shower or you're

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stuck in traffic and it's perfect in your head.

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A brilliant app, a new business, little game.

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But then there's this friction between your brain

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and the screen. And that friction is almost always

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code. It's code, it's syntax, it's the thousands

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of dollars you'd need to hire a dev team. It's

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the classic technical wall. It's where most great

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ideas go to die. Right. And usually on this show,

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when we talk about AI, we're talking about tools

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that help you climb that wall. You know, they're

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like assistants. Or librarians. But the guide

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we're looking at today, it covers Manus AI 1

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.6 Max, makes a much bolder claim. It says the

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wall is just gone. It is a bold assertion. But

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looking at this, the shift is very real. We're

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moving from AI as a consultant to AI as a contractor.

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And that distinction is everything. I want to

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drill down on that right away, because consultant

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implies advice, but contractor, that implies

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labor. What's the real difference here? Well,

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think about chat GPT or Claude. They're text

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engines, right? So if you say, I want a pet grooming

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app, they act like a consultant. You'll say,

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OK, here's a recipe. Here's a block of Python

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code. Good luck. They hand you the blueprint,

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but you still have to pour the concrete. You

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have to compile it, host it. debug it. And the

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contractor. The contractor. Manus AI. It has

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file system access. It creates the directory.

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It writes the index .html. It writes the CSS.

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It spins up the server. It doesn't just tell

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you how to build a website. It just builds it.

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It builds the website. Precisely. It's the difference

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between asking for a recipe and asking a chef

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to put the meal on your table. So that's the

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promise. But I want to test the reality. The

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guide lays out this whole journey, starting with

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a pretty simple app, then a game, then some deep

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market research, and then a full business launch.

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So let's start with that first stress test. The

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local business, happy pause. Right, happy pause.

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The local pet grooming service. Now, traditionally,

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building a booking app for a local dog groomer

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is a total nightmare of logistics. You're managing

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freelancers, you're worrying about server costs.

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It's months of work, minimum. So in this case

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study, what was the input? What did they tell

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it to do? It was a single paragraph of just plain

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English. The prompt was basically, build a fully

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functioning mobile app for happy paws. Use soft

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blue and white colors. List services like dogwash

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and nail trim. Oh, and add a booking page and

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a map placeholder. OK, but I have to be the skeptic

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here. I can ask an image generator to make a

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picture of an app, and it'll look pretty. But

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it doesn't do anything. Is this just a really

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good mockup, or is it actual software? That is

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the aha moment in the guide. A little window

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pops up, a preview pane, and it's live. You can

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click the Book Now button. It actually takes

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you to a confirmation screen. The guide even

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notes the AI included a mobile view icon so you

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can see exactly how it feels on a phone. Does

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this actually result in usable software or just

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a mockup? It creates real functioning technology

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you can use immediately. You could run the business

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off it five minutes later. That's significant.

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But an appointment app, you know, it's useful,

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but it's kind of static. It's forms and buttons.

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I want to see if this thing can handle real complexity,

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like state management. Yeah. Physics. The guide

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moves on to a game next, right? Space Dodger.

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Space Dodger. OK. A browser game. This feels

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like a proper stress test. Moving from pure utility

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to entertainment. It is. They really wanted to

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see if Manus AI could handle the fun factor.

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So they asked for a game inspired by Dino Run.

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Really simple concept. You're a rocket. Asteroids

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fly from right to left, and you just don't crash.

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And again, a simple prompt. Super simple. Rocket

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moves up and down, asteroids come from the right,

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keep score, and bam, it built it. But here's

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where it gets really interesting for anyone who's

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ever tried to code a game with an LLM. The dreaded

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context window. Exactly. Usually you build version

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one and it works. Then you say, okay, now make

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the asteroids faster. The AI rewrites the code,

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but it forgets how the rocket moves. Or it breaks

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the collision detection. Yeah. It's like playing

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Jenga. You pull one block out and the whole tower

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just collapses. So how did Manus handle that,

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the iteration? The guide calls it conversational

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iteration. The user just typed. Make it more

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challenging. Every 10 seconds, make the asteroids

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move 20 % faster. Also change the background

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from blue to black as it gets harder. And it

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didn't break the original movement logic? Not

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at all. It understood the existing code base

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it had just created. It just injected a timer

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function and a speed variable multiplier without

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touching the core rendering loop. The code updated

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in real time. So the coding happens dynamically

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during the conversation? Exactly. You just keep

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talking and the software mutates to match what

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you want. It treats the code like a living project,

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not some disposable text snippet. Let's pivot

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to something that I think plagues a lot of us.

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It's not always the coding that stops an idea.

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It's just the chaos of the process. The research

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rabbit hole. I have to admit, I still wrestle

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with this. I call it prompt drift. You start

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researching a market, and three hours later,

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you have 50 tabs open. You've completely lost

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the thread, and now you're reading about the

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history of coffee beans. It's cognitive overload.

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Yeah. Yes. Yeah. And Manus AI seems to tackle

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this with a specific feature, automating deep

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market research. The example they used was for

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a healthy snack subscription box called Green

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Bites. Okay, Green Bites. So how does the AI

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handle that research any differently than me

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just Googling for three hours? It brings structure

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to the chaos. The prompt actually asked for a

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spreadsheet. It said, conduct a deep competitive

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analysis. I need a spreadsheet with multiple

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tabs. Tab 1, top 10 competitors and their prices.

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Tab 2, target audience analysis. Right, but usually

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if I ask an AI for competitor prices, it either

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hallucinates or it gives me data from 2021 because

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that's when its training data cuts off. Right,

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but Manus has a live browser agent, so it goes

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out to the live web right now. It checks the

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current pricing on the competitor websites. And

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the output, is it just a wall of text? This is

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the cool part. It rendered a functional spreadsheet

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UI right there inside the chat. Rows, columns,

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tabs, you could sort it. It looks just like Excel

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or Google Sheets. That's a huge workload change.

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I'm always copying and pasting into a separate

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document. It removed that whole copy -paste tax.

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It formatted the live data perfectly. It even

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identified gaps in the market. For Green Bites,

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it pointed out that nobody was offering a low

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-sugar option specifically for office workers.

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How does it link the research to the strategy?

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It remembers the context. using the spreadsheet

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data to inform the plan automatically. The user

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just said, OK, use that data to build me a go

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-to -market plan. It just remembers the spreadsheet.

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It remembers everything. So it looked at the

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competitor pricing in that spreadsheet. Let's

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say the average was $35. And it automatically

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suggested a penetration price of $28 a month

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for GreenBytes. So it didn't just guess a number,

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it calculated a strategy based on the research

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it had just done. Exactly. It linked the raw

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data to a strategic decision without the human

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having to connect all the dots. OK, let's talk

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visuals, because a business needs a brand. And

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honestly, AI image generation has been, well,

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it's been hit or miss, especially with text.

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Oh, the alien text struggle is real, yeah. You

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ask for a sign that says coffee and you get coffefe

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or some weird hieroglyphics. Right. But Manus

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AI has this feature they call magic edit. And

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honestly, whoa, it is a bit of a game changer

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for design. And the example was for Greenbite's

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marketing assets, the Instagram posts. Right.

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So they asked for a close -up of a vegan cookie

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with the text 100 % plant power. Simple enough.

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Yep. And the AI generates it. Looks great. But

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then the user decides, you know what? Plant power

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is a bit generic. Let's change it. in Mid -Journey

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or Dali -E, if you change the prompt, you get

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a completely new image. The cookie looks different,

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the lighting's all wrong. You lose all the consistency.

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Exactly. But with Manist, you click a button

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that says Edit Text, you type Power Your Morning,

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and the AI swaps the text inside the image while

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keeping the cookie, the lighting, everything

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else exactly the same. Is this basically Photoshop

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inside the chat? It's a visual editor that understands

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text inside images perfectly. No more re -rolling

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the dice. That solves so many workflow headaches.

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Okay, so we've built the app, the game, done

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the research, the strategy, the visuals. Now

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for the big one, the mega prompt. The indoor

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jungle. I love this example. It shows the sheer

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scale of what's possible here. They wanted to

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launch an entire education business, an indoor

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gardening course. And instead of doing it piece

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by piece, they asked for everything at once.

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The audacity of this prompt. They asked for four

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distinct things. A course outline with four modules,

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a five email launch sequence, a 30 -minute sales

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webinar outline, and 10 blog post titles. All

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at once. That's a week's worth of work for a

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human copywriter. How long did it take? About

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10 to 12 minutes. which, yeah, is longer than

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a typical chat response, but it produced a whole

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business in a box. And normally, an AI would

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just choke on that. It would time out or give

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you four short, generic paragraphs. Right. But

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because Manus works in the background, it generated

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these really detailed, deep assets for all four

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deliverables. But the killer feature for me,

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it's the interconnectivity that turned into website

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button. Yes. This is it. So it writes the webinar

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outline, just text. The user highlights that

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text, selects turn into website, and boom, instantly

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it renders a registration landing page connected

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to the site builder based on that text. It actually

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parses the meaning of the text. Yes. It sees

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introduction, so it makes a hero header. It sees

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key learning points, so it creates a bulleted

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list section. It interprets the meaning of the

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text and translates it directly into design elements.

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That's the end of the lorem ipsum placeholder.

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You're designing with real content from day one.

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It's totally seamless. Can you customize the

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website after it's generated? Yes. And again,

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it's just natural language. You don't have to

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touch any CSS. You just tell the chat, make the

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background a lighter mint green, or make that

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headline bigger. And it just updates. The recurring

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theme here seems to be about flow, about removing

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all the little points of friction between I want

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this and here it is. Absolutely. It's just compressing

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the time between your intent and the final execution.

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Sponsor. We are back on the deep dive, exploring

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Manus AI 1 .6 Max. We've walked through the examples,

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Happy Paws, Space Dodger, Green Bites. It's all

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very impressive. But I want to ground this for

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our listeners who might be thinking, OK, I already

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pay for Chad GPT+. Do I really need this? It's

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the million dollar question, right? And the guide

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has a really helpful comparison table that kind

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of visualizes the whole thing. It really boils

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down to three main differences. OK, let's run

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through them. The first one is the role. Right.

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Consultant versus contractor. We touched on this.

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Yeah. Chat GPT talks. Manus builds. If you want

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advice, you get a consultant. If you want a house

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built, you get a contractor. Second is workflow.

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Disconnected versus connected. With the standard

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LLMs, you are the clipboard. You copy the text.

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You paste it into Word. You paste the code into

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your editor. You're the glue holding the entire

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process together. And with Manus? With Manus,

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the data is all synced. The research talks to

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the strategy, which talks to the website builder.

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You aren't the glue anymore. You're the architect.

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And the third one. Editing. It's start over versus

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visual editing. That ability to just tweak the

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text on that cookie image or change the game

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difficulty without having to scrap the whole

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thing and start from scratch, it turns generation

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into iteration. And iteration is where good products

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actually come from. It really feels like we are

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seeing the complete removal of that technical

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wall we talked about. That's the conclusion the

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source draws, and I have to agree. For decades,

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I don't know how to code was a perfectly valid

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reason not to start something. It was a real

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tangible barrier. And now... That barrier is

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gone. It's just evaporated. The only limit now

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is your imagination. You know, as we wrap this

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up, I'm struck by a thought. We spent years,

00:12:03.549 --> 00:12:06.570
a decade really, telling people... Learn to code.

00:12:07.029 --> 00:12:09.090
It was the golden ticket. It was the literacy

00:12:09.090 --> 00:12:12.070
of the 21st century, for sure. But looking at

00:12:12.070 --> 00:12:14.169
this, it feels like the definition of literacy

00:12:14.169 --> 00:12:17.710
is changing. It's not about speaking the machine's

00:12:17.710 --> 00:12:20.210
language anymore. It's about speaking your language

00:12:20.210 --> 00:12:22.350
clearly enough that the machine understands.

00:12:22.750 --> 00:12:26.299
It shifts the premium from how to what. If the

00:12:26.299 --> 00:12:28.379
cost of building something drops to near zero,

00:12:28.799 --> 00:12:31.580
the value of a truly unique idea goes through

00:12:31.580 --> 00:12:34.200
the roof. So it democratizes the build, but it

00:12:34.200 --> 00:12:36.480
meritocratizes the idea. I love that. That's

00:12:36.480 --> 00:12:38.759
perfect. OK. It puts the focus back on human

00:12:38.759 --> 00:12:42.779
creativity and taste and strategy. So for the

00:12:42.779 --> 00:12:44.960
listener who's sitting there, maybe with that

00:12:44.960 --> 00:12:47.480
idea they had in the shower this morning, what's

00:12:47.480 --> 00:12:51.960
the first step? The move is to just start. The

00:12:51.960 --> 00:12:54.639
guide encourages you to use the free credits.

00:12:54.840 --> 00:12:56.679
You don't have to build the next Facebook today.

00:12:56.799 --> 00:12:59.519
Just build a portfolio. Build a silly game for

00:12:59.519 --> 00:13:01.500
your kids. Just get your hands dirty with it.

00:13:01.559 --> 00:13:04.460
Yes. Because once you see your own words turn

00:13:04.460 --> 00:13:07.580
into a real thing, once you type make the rocket

00:13:07.580 --> 00:13:10.820
fly and the rocket actually flies, you will never

00:13:10.820 --> 00:13:13.500
look at technology the same way again. It fundamentally

00:13:13.500 --> 00:13:15.460
changes your relationship with the machine. I

00:13:15.460 --> 00:13:17.000
think that is the perfect place to leave it.

00:13:17.019 --> 00:13:19.559
The wall is down. The tools are here. The rest

00:13:19.559 --> 00:13:21.679
is up to you. Thank you for joining us on this

00:13:21.679 --> 00:13:23.440
deep dive. We'll catch you on the next one. Go

00:13:23.440 --> 00:13:24.120
build something cool.
