We all have that feeling, right? The execution
gap. You get an idea maybe in the shower or you're
stuck in traffic and it's perfect in your head.
A brilliant app, a new business, little game.
But then there's this friction between your brain
and the screen. And that friction is almost always
code. It's code, it's syntax, it's the thousands
of dollars you'd need to hire a dev team. It's
the classic technical wall. It's where most great
ideas go to die. Right. And usually on this show,
when we talk about AI, we're talking about tools
that help you climb that wall. You know, they're
like assistants. Or librarians. But the guide
we're looking at today, it covers Manus AI 1
.6 Max, makes a much bolder claim. It says the
wall is just gone. It is a bold assertion. But
looking at this, the shift is very real. We're
moving from AI as a consultant to AI as a contractor.
And that distinction is everything. I want to
drill down on that right away, because consultant
implies advice, but contractor, that implies
labor. What's the real difference here? Well,
think about chat GPT or Claude. They're text
engines, right? So if you say, I want a pet grooming
app, they act like a consultant. You'll say,
OK, here's a recipe. Here's a block of Python
code. Good luck. They hand you the blueprint,
but you still have to pour the concrete. You
have to compile it, host it. debug it. And the
contractor. The contractor. Manus AI. It has
file system access. It creates the directory.
It writes the index .html. It writes the CSS.
It spins up the server. It doesn't just tell
you how to build a website. It just builds it.
It builds the website. Precisely. It's the difference
between asking for a recipe and asking a chef
to put the meal on your table. So that's the
promise. But I want to test the reality. The
guide lays out this whole journey, starting with
a pretty simple app, then a game, then some deep
market research, and then a full business launch.
So let's start with that first stress test. The
local business, happy pause. Right, happy pause.
The local pet grooming service. Now, traditionally,
building a booking app for a local dog groomer
is a total nightmare of logistics. You're managing
freelancers, you're worrying about server costs.
It's months of work, minimum. So in this case
study, what was the input? What did they tell
it to do? It was a single paragraph of just plain
English. The prompt was basically, build a fully
functioning mobile app for happy paws. Use soft
blue and white colors. List services like dogwash
and nail trim. Oh, and add a booking page and
a map placeholder. OK, but I have to be the skeptic
here. I can ask an image generator to make a
picture of an app, and it'll look pretty. But
it doesn't do anything. Is this just a really
good mockup, or is it actual software? That is
the aha moment in the guide. A little window
pops up, a preview pane, and it's live. You can
click the Book Now button. It actually takes
you to a confirmation screen. The guide even
notes the AI included a mobile view icon so you
can see exactly how it feels on a phone. Does
this actually result in usable software or just
a mockup? It creates real functioning technology
you can use immediately. You could run the business
off it five minutes later. That's significant.
But an appointment app, you know, it's useful,
but it's kind of static. It's forms and buttons.
I want to see if this thing can handle real complexity,
like state management. Yeah. Physics. The guide
moves on to a game next, right? Space Dodger.
Space Dodger. OK. A browser game. This feels
like a proper stress test. Moving from pure utility
to entertainment. It is. They really wanted to
see if Manus AI could handle the fun factor.
So they asked for a game inspired by Dino Run.
Really simple concept. You're a rocket. Asteroids
fly from right to left, and you just don't crash.
And again, a simple prompt. Super simple. Rocket
moves up and down, asteroids come from the right,
keep score, and bam, it built it. But here's
where it gets really interesting for anyone who's
ever tried to code a game with an LLM. The dreaded
context window. Exactly. Usually you build version
one and it works. Then you say, okay, now make
the asteroids faster. The AI rewrites the code,
but it forgets how the rocket moves. Or it breaks
the collision detection. Yeah. It's like playing
Jenga. You pull one block out and the whole tower
just collapses. So how did Manus handle that,
the iteration? The guide calls it conversational
iteration. The user just typed. Make it more
challenging. Every 10 seconds, make the asteroids
move 20 % faster. Also change the background
from blue to black as it gets harder. And it
didn't break the original movement logic? Not
at all. It understood the existing code base
it had just created. It just injected a timer
function and a speed variable multiplier without
touching the core rendering loop. The code updated
in real time. So the coding happens dynamically
during the conversation? Exactly. You just keep
talking and the software mutates to match what
you want. It treats the code like a living project,
not some disposable text snippet. Let's pivot
to something that I think plagues a lot of us.
It's not always the coding that stops an idea.
It's just the chaos of the process. The research
rabbit hole. I have to admit, I still wrestle
with this. I call it prompt drift. You start
researching a market, and three hours later,
you have 50 tabs open. You've completely lost
the thread, and now you're reading about the
history of coffee beans. It's cognitive overload.
Yeah. Yes. Yeah. And Manus AI seems to tackle
this with a specific feature, automating deep
market research. The example they used was for
a healthy snack subscription box called Green
Bites. Okay, Green Bites. So how does the AI
handle that research any differently than me
just Googling for three hours? It brings structure
to the chaos. The prompt actually asked for a
spreadsheet. It said, conduct a deep competitive
analysis. I need a spreadsheet with multiple
tabs. Tab 1, top 10 competitors and their prices.
Tab 2, target audience analysis. Right, but usually
if I ask an AI for competitor prices, it either
hallucinates or it gives me data from 2021 because
that's when its training data cuts off. Right,
but Manus has a live browser agent, so it goes
out to the live web right now. It checks the
current pricing on the competitor websites. And
the output, is it just a wall of text? This is
the cool part. It rendered a functional spreadsheet
UI right there inside the chat. Rows, columns,
tabs, you could sort it. It looks just like Excel
or Google Sheets. That's a huge workload change.
I'm always copying and pasting into a separate
document. It removed that whole copy -paste tax.
It formatted the live data perfectly. It even
identified gaps in the market. For Green Bites,
it pointed out that nobody was offering a low
-sugar option specifically for office workers.
How does it link the research to the strategy?
It remembers the context. using the spreadsheet
data to inform the plan automatically. The user
just said, OK, use that data to build me a go
-to -market plan. It just remembers the spreadsheet.
It remembers everything. So it looked at the
competitor pricing in that spreadsheet. Let's
say the average was $35. And it automatically
suggested a penetration price of $28 a month
for GreenBytes. So it didn't just guess a number,
it calculated a strategy based on the research
it had just done. Exactly. It linked the raw
data to a strategic decision without the human
having to connect all the dots. OK, let's talk
visuals, because a business needs a brand. And
honestly, AI image generation has been, well,
it's been hit or miss, especially with text.
Oh, the alien text struggle is real, yeah. You
ask for a sign that says coffee and you get coffefe
or some weird hieroglyphics. Right. But Manus
AI has this feature they call magic edit. And
honestly, whoa, it is a bit of a game changer
for design. And the example was for Greenbite's
marketing assets, the Instagram posts. Right.
So they asked for a close -up of a vegan cookie
with the text 100 % plant power. Simple enough.
Yep. And the AI generates it. Looks great. But
then the user decides, you know what? Plant power
is a bit generic. Let's change it. in Mid -Journey
or Dali -E, if you change the prompt, you get
a completely new image. The cookie looks different,
the lighting's all wrong. You lose all the consistency.
Exactly. But with Manist, you click a button
that says Edit Text, you type Power Your Morning,
and the AI swaps the text inside the image while
keeping the cookie, the lighting, everything
else exactly the same. Is this basically Photoshop
inside the chat? It's a visual editor that understands
text inside images perfectly. No more re -rolling
the dice. That solves so many workflow headaches.
Okay, so we've built the app, the game, done
the research, the strategy, the visuals. Now
for the big one, the mega prompt. The indoor
jungle. I love this example. It shows the sheer
scale of what's possible here. They wanted to
launch an entire education business, an indoor
gardening course. And instead of doing it piece
by piece, they asked for everything at once.
The audacity of this prompt. They asked for four
distinct things. A course outline with four modules,
a five email launch sequence, a 30 -minute sales
webinar outline, and 10 blog post titles. All
at once. That's a week's worth of work for a
human copywriter. How long did it take? About
10 to 12 minutes. which, yeah, is longer than
a typical chat response, but it produced a whole
business in a box. And normally, an AI would
just choke on that. It would time out or give
you four short, generic paragraphs. Right. But
because Manus works in the background, it generated
these really detailed, deep assets for all four
deliverables. But the killer feature for me,
it's the interconnectivity that turned into website
button. Yes. This is it. So it writes the webinar
outline, just text. The user highlights that
text, selects turn into website, and boom, instantly
it renders a registration landing page connected
to the site builder based on that text. It actually
parses the meaning of the text. Yes. It sees
introduction, so it makes a hero header. It sees
key learning points, so it creates a bulleted
list section. It interprets the meaning of the
text and translates it directly into design elements.
That's the end of the lorem ipsum placeholder.
You're designing with real content from day one.
It's totally seamless. Can you customize the
website after it's generated? Yes. And again,
it's just natural language. You don't have to
touch any CSS. You just tell the chat, make the
background a lighter mint green, or make that
headline bigger. And it just updates. The recurring
theme here seems to be about flow, about removing
all the little points of friction between I want
this and here it is. Absolutely. It's just compressing
the time between your intent and the final execution.
Sponsor. We are back on the deep dive, exploring
Manus AI 1 .6 Max. We've walked through the examples,
Happy Paws, Space Dodger, Green Bites. It's all
very impressive. But I want to ground this for
our listeners who might be thinking, OK, I already
pay for Chad GPT+. Do I really need this? It's
the million dollar question, right? And the guide
has a really helpful comparison table that kind
of visualizes the whole thing. It really boils
down to three main differences. OK, let's run
through them. The first one is the role. Right.
Consultant versus contractor. We touched on this.
Yeah. Chat GPT talks. Manus builds. If you want
advice, you get a consultant. If you want a house
built, you get a contractor. Second is workflow.
Disconnected versus connected. With the standard
LLMs, you are the clipboard. You copy the text.
You paste it into Word. You paste the code into
your editor. You're the glue holding the entire
process together. And with Manus? With Manus,
the data is all synced. The research talks to
the strategy, which talks to the website builder.
You aren't the glue anymore. You're the architect.
And the third one. Editing. It's start over versus
visual editing. That ability to just tweak the
text on that cookie image or change the game
difficulty without having to scrap the whole
thing and start from scratch, it turns generation
into iteration. And iteration is where good products
actually come from. It really feels like we are
seeing the complete removal of that technical
wall we talked about. That's the conclusion the
source draws, and I have to agree. For decades,
I don't know how to code was a perfectly valid
reason not to start something. It was a real
tangible barrier. And now... That barrier is
gone. It's just evaporated. The only limit now
is your imagination. You know, as we wrap this
up, I'm struck by a thought. We spent years,
a decade really, telling people... Learn to code.
It was the golden ticket. It was the literacy
of the 21st century, for sure. But looking at
this, it feels like the definition of literacy
is changing. It's not about speaking the machine's
language anymore. It's about speaking your language
clearly enough that the machine understands.
It shifts the premium from how to what. If the
cost of building something drops to near zero,
the value of a truly unique idea goes through
the roof. So it democratizes the build, but it
meritocratizes the idea. I love that. That's
perfect. OK. It puts the focus back on human
creativity and taste and strategy. So for the
listener who's sitting there, maybe with that
idea they had in the shower this morning, what's
the first step? The move is to just start. The
guide encourages you to use the free credits.
You don't have to build the next Facebook today.
Just build a portfolio. Build a silly game for
your kids. Just get your hands dirty with it.
Yes. Because once you see your own words turn
into a real thing, once you type make the rocket
fly and the rocket actually flies, you will never
look at technology the same way again. It fundamentally
changes your relationship with the machine. I
think that is the perfect place to leave it.
The wall is down. The tools are here. The rest
is up to you. Thank you for joining us on this
deep dive. We'll catch you on the next one. Go
build something cool.