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90% of People Fail at Vibe Coding. Here's the Actual Reason: You're Skipping the Hard Part.

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90% of People Fail at Vibe Coding. Here's the Actual Reason: You're Skipping the Hard Part.

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540 segments

0:00

Something clicked in the last couple of

0:01

weeks and the word I keep reaching for

0:03

is playfulness with AI, which is

0:06

probably not what you expect because the

0:08

AI discourse is super loud right now and

0:10

most of it to be honest is ominous. Jobs

0:13

are disappearing, deep fakes,

0:14

misinformation, existential risk, think

0:17

pieces that are anxious, comment

0:19

sections get angry. I'm not here to

0:21

dismiss that. The concerns are real and

0:23

we talk about them a fair bit on this

0:25

channel. But there's a different story

0:26

happening in parallel that we miss. It's

0:29

quieter. It's a little bit odd. And I

0:31

want to talk about that instead today.

0:33

So, vibe coding, which is using AI to

0:35

build software with natural language,

0:37

that's been possible since the earlier

0:39

part of 2025. But for most of the year,

0:42

it was still work. You had to fight the

0:44

tools. You had to babysit the AI through

0:46

the confusion. You had to debug weird

0:48

failures that made no sense. You had to

0:50

learn about databases and backend. The

0:52

friction was high enough that you had to

0:54

be serious about what you were building.

0:57

You wouldn't want to waste that effort

0:59

on something frivolous. What's shifted

1:01

in the last couple of weeks is not just

1:03

that the tools got better, although they

1:05

did. It's that the models hold context

1:08

longer. The agentic patterns have

1:09

matured. Builder platforms have gotten

1:11

more reliable. The real change is

1:14

downstream of all those individual

1:15

pieces. Right? It's like the Lego bricks

1:17

came together to make a set. The

1:19

friction has now dropped enough that

1:22

building software has stopped feeling

1:25

like work and started to feel like play.

1:28

And play produces very different things.

1:30

Last week, a service called Fable

1:32

started making the rounds. You upload a

1:34

photo of your pet and it generates a

1:36

Renaissance portrait with AI. Your dog

1:38

as a baroque duke, your cat as a Flemish

1:41

noble woman. This all sounds extremely

1:44

silly and it ships to you as a physical

1:45

print and it's ridiculous. It's

1:48

delightful and it's doing a This is not

1:51

an identify a market need and execute

1:53

story. This is a wouldn't it be funny if

1:56

story. Someone was playing. They built

1:58

the joke. The internet turned out to

2:00

have demand for it. And this is the part

2:02

that caught my attention. It's not the

2:04

economics of AI coding here. Although

2:06

the economics are real and we'll talk

2:07

about them elsewhere. The thing

2:09

underneath is that software has now

2:11

become cheap enough to make for fun and

2:13

people are making different things.

2:15

They're making weirder things, things

2:16

that come from play rather than

2:18

strategy, creative things. And

2:20

occasionally, because the internet is

2:22

vast and has appetite for nearly

2:23

anything interesting, one of those

2:25

playful things finds a huge audience,

2:27

just like Fable. The internet has always

2:30

been an infinite pool of demand. What's

2:32

new is that the cost of figuring out

2:34

that demand has collapsed. You can just

2:37

try things now. You can build the dumb

2:39

idea. You can see what happens. And if

2:42

nobody cares, all you did is lose a

2:44

weekend. And if they do care, hey, you

2:46

got something fun. There's a particular

2:49

kind of satisfaction that comes from

2:51

making something that works. You have an

2:54

idea. You figure out the pieces. At some

2:56

point, the thing you imagined becomes

2:59

something that exists because you made

3:01

it. People who build real things for a

3:03

living know this, right? Carpenters know

3:04

this. Cooks know this. I cook.

3:07

Designers, engineers. The material

3:09

varies, but the satisfaction is

3:11

recognizable. You had a vision. Now you

3:14

have a real thing. Now, for most of

3:16

software's history, this satisfaction

3:18

was gated behind years of specialized

3:21

training. The gap between I wish this

3:23

existed and I made it exist was way too

3:25

wide to cross casually. Most ideas ended

3:28

up dying in that gap. Not because they

3:31

were necessarily bad, but because the

3:32

activation energy was way too high. The

3:35

gate is open now. the bridge is

3:37

crossable and people are just walking

3:38

through and they're not just startup

3:41

founders looking for leverage. A lot of

3:43

us, frankly, I'm a vibe coder too, are

3:45

hobbyists. We're building things for fun

3:48

and we don't always have a business

3:50

model insight. Really, vibe coding is

3:52

the hobby out of 2025 and now into 2026

3:55

that nobody expected. A designer can

3:58

build a personal dashboard that shows

3:59

the phase of the moon. They can show

4:01

their Spotify listening stats. They can

4:04

show how many days until their next

4:06

vacation, and they can put it all

4:07

together in a way that's fun for them. A

4:09

retiree can automate their greenhouse

4:11

irrigation. Someone can make a browser

4:13

extension that does one absurd thing

4:16

perfectly, like log every time they find

4:19

an article that mentions cat grooming. A

4:22

friend can get a custom Telegram bot

4:24

that alerts them when concert tickets

4:25

drop. None of these are necessarily

4:28

businesses by themselves. They're just

4:30

projects. They're built for the

4:32

satisfaction of building. They're used

4:35

by the maker and maybe a few of their

4:37

friends. This is new. For most of

4:39

software's history, building required

4:40

enough specialized knowledge that it was

4:42

primarily professional. Hobbyist

4:44

programmers technically existed, but I

4:46

code for fun was a very, very niche

4:48

identity and it was not a casual weekend

4:50

activity. What's emerging now looks a

4:53

lot like what happened with photography.

4:54

Actually, taking good photos used to

4:57

require very serious expertise,

4:59

exposure, developing dark rooms. I took

5:02

that dark room class in high school. And

5:04

then cameras got easier. The smartphone

5:06

made everyone a photographer. Instagram

5:08

came along. Professional photography

5:10

still exists to be sure. But alongside a

5:13

vast amateur ecosystem of people who

5:16

just love taking pictures, software is

5:18

going through its Instagram moment. The

5:21

professionals aren't going anywhere.

5:22

Complex systems still require deep

5:24

expertise. But alongside professional

5:27

development, there's now space for a

5:29

service like Fable, for casual creation,

5:32

building for yourself, for fun, for

5:34

friends, because you had an idea and now

5:36

you can make it real. And because it's

5:38

play, people do try weird stuff. They

5:40

follow ideas wherever they go. Some of

5:42

the most interesting software I've seen

5:44

has this hobbyist energy. It's not

5:46

always polished. It's not always

5:48

scalable, but it's genuinely creative in

5:51

ways that commercial software rarely is.

5:53

And I think we need that because one of

5:55

the things I've observed about

5:56

commercial software is that it remains

5:58

stuck in a lot of the design paradigms

6:00

of the 1990s, 2000s, and 2010s. And we

6:04

have not fully seen what AI native

6:06

enterprise software looks like. We

6:08

haven't had that injection of creative

6:10

energy. And I wonder if some of it is

6:12

going to come from people who are

6:14

playful. Here's the thing about telling

6:16

someone they can now build any app they

6:19

want. Most people say cool and then

6:21

never think of anything to build. Not

6:23

because they're uncreative, but because

6:25

most people's problems aren't software

6:27

shaped, and most don't notice when they

6:30

are. There's a concept from parkour, the

6:32

sport, called parkour vision. The

6:34

trained ability to see walls as surfaces

6:36

you can run along, gaps as spaces to

6:39

jump through, railings as pathways. We

6:41

memorably saw this with a Netflix

6:43

special uh with Alex Honold climbing uh

6:46

the Taipei Tower, right? Taipe 101. He

6:48

saw the building differently and so he

6:50

could climb it. The city looks different

6:53

to someone using parkour to traverse it

6:57

because of that vision. And software

6:59

vision is like that. Programmers are

7:02

trained to see repetitive tasks as

7:04

automation opportunities in the same way

7:06

Alex is trained to see a skyscraper as a

7:09

climbable surface. Programmers will look

7:11

at a manual workflow and think, "I can

7:14

script this." And the rest of us just

7:16

keep doing it manually. The people who

7:18

take to vibe coding aren't necessarily

7:20

technical. They're people who already

7:22

have software vision who develop it

7:24

quickly when they don't have it. They

7:26

notice when a problem is software shaped

7:29

intuitively. Hey, I keep doing this over

7:31

and over. I wish I could see all of this

7:33

information in one place, but no one

7:34

would ever build me this software that

7:36

has phases of the moon and also when my

7:39

next homework assignment is due. Or,

7:41

it's annoying that these two systems

7:42

don't talk to each other. If you've ever

7:44

spent an afternoon building a

7:46

complicated spreadsheet to solve a

7:48

problem, I bet you have some software

7:50

vision in you. If you've ever duct taped

7:52

together automations, whether they're

7:53

N8N or Zapier or written macros or bent

7:56

a tool to do something it wasn't

7:58

designed for, that's the disposition. I

8:00

remember writing bash scripts because my

8:03

audio drivers wouldn't work back in the

8:05

early 2000s. That's softwareshaped

8:08

perspective. You don't need to know how

8:10

to code a ton or even at all now. You

8:13

need to notice when a problem could be

8:15

solved by software and curious enough to

8:17

try. The other thing I'll call out that

8:19

you need is some degree of comfort with

8:21

ambiguity. Things won't work on the

8:23

first try. You'll probably describe what

8:25

you want, get something close but not

8:27

right, and you'll need to figure out how

8:29

you refine that description. If you

8:31

require step-by-step instructions for

8:33

everything, this part might get

8:35

frustrating because you can step by step

8:37

your way into a vibe coding space, but

8:41

then it's up to you to do that sort of

8:42

parkour magic and figure out what you

8:44

want to make. And if you're okay with

8:46

that experimentation, if that iteration

8:48

is a little bit of part of the fun for

8:50

you, you'll do fine. I do want to be

8:52

honest about two big failure modes I see

8:55

with vibe coding because oftentimes

8:57

people will jump all the way over and

8:58

say there's nothing but vibe coding in

9:00

the future. I don't think that's true.

9:02

The first failure mode is moving so fast

9:04

you never stop to think. When building

9:07

is instant, which it's becoming now, the

9:09

bottleneck shifts to knowing what you

9:11

actually want. And it's very easy to

9:13

prompt before you figure that out. So

9:15

you generate piles of features that

9:18

don't fit together. You end up hip deep

9:20

in a project that doesn't serve any

9:23

clear purpose. The build test iterate

9:25

loop is so fast now it can feel really

9:28

intoxicating just for its own sake. And

9:30

you can burn a weekend building software

9:32

that doesn't really solve a real

9:34

painoint. And so the invitation here,

9:36

the discipline is to pause, to describe

9:39

what you want really plainly before you

9:41

start prompting to know why you're

9:43

building it. Even if it's just for fun

9:45

and what it should do and and what you

9:47

want it to do, what success looks like.

9:48

It doesn't have to be monetary. The

9:50

tools will happily turn vague intentions

9:53

into their idea of working code. But

9:56

that may not be your idea at the end of

9:57

the day. The second issue is confusing

10:00

works on my laptop with ready for users.

10:03

AI is compressing the cost of creating

10:05

software towards zero. And a working

10:07

prototype now takes a few minutes or

10:09

maybe a couple of hours. But AI doesn't

10:12

compress the cost of owning software in

10:15

production. Someone will still have to

10:17

answer for it. So if you wanted to make

10:19

something that was not just for you,

10:22

that actually had users as Fable now

10:25

has, then someone has to answer for when

10:27

that vibecoded project breaks at 2 a.m.

10:29

when someone's trying to order a dog

10:31

picture, right? Who carries the

10:33

liability when it fails? Who integrates

10:35

it with everything else? For personal

10:37

projects, if it's truly personal,

10:38

doesn't matter, right? You don't care.

10:40

Your greenhouse automation can crash and

10:42

the worst thing that happens is you go

10:43

water the tomato plants. Your friend

10:45

group bot can have bugs and your friends

10:47

can chuckle. The stakes are low and

10:49

imperfection is fine. But for something

10:51

that users are depending on, even for a

10:54

silly dog picture app, the gap between

10:56

prototype and production grade is still

10:58

real. Security researchers have found

11:00

that roughly 10% of apps built on some

11:03

popular vibe coding platforms have

11:05

vulnerabilities. And I would say that's

11:07

a low estimate. This is stuff like

11:09

databases exposed to the public

11:10

internet, API keys visible to anyone who

11:13

looked. AI tends to handle the happy

11:15

path and often misses the edge cases.

11:17

And this is where platforms like Lovable

11:20

are making a bet. They're running the

11:22

same playbook Shopify ran from a

11:24

strategy perspective. They're starting

11:26

with you can vibe code anything and

11:28

we'll help you grow up. That's what

11:30

Shopify did with shops. The tools are

11:32

extending that bridge toward production,

11:35

adding authentication, adding security,

11:37

scaling infrastructure, so you don't

11:39

have to start over when your little vibe

11:41

coded project takes off. The gap is

11:44

narrowing, but it's not all the way gone

11:46

yet. Right now, vibe coding is great for

11:48

prototyping. It's great for personal

11:50

tools. It's great for experiments. And

11:53

it's great to help you figure out if an

11:54

idea has legs. If something does catch

11:57

fire, you may need to level up your

11:59

understanding or you may need to bring

12:00

in someone who can help you go the rest

12:02

of the way. You might be wondering, what

12:04

is the tools stack? What makes sense

12:05

here? I'm not going to go into it in

12:07

depth. I have a whole guide for this

12:08

that I that I put on Substack that you

12:10

can grab. There's two fundamentally

12:12

different paths here. The first one is

12:14

the builder platform path, right? tools

12:16

like lovable, bolt, replet. You describe

12:19

what you want in chat and the platform

12:21

will generate the application front end,

12:23

backend, increasingly database

12:25

deployment, even domain. Lovable does

12:27

that. You never see a terminal. You

12:29

don't have to see code if you don't want

12:31

to. And this path can make sense if you

12:33

have zero technical background. You need

12:35

something fast. You know, you're

12:37

building a prototype. Your tradeoff

12:39

there is control. Those platforms

12:41

optimize for speed to first demo not for

12:44

long-term maintainability and you have

12:46

to be intentional about that. The second

12:47

path has a little bit more of a curve.

12:49

It's command line tools. Tools like

12:51

claude code, cursor, windsurf. You work

12:53

in a code editor or a terminal. The AI

12:56

writes the code. You do see it. You run

12:58

it locally and you commit to your own

13:00

repo and you deploy it when you choose.

13:03

If you have some technical comfort, this

13:05

doesn't feel scary. If you want to

13:07

understand and own what you're building

13:08

and learn, this is also a great path.

13:11

And this gives you the flexibility to

13:13

change your tools very easily without

13:14

starting over. The trade-off is

13:16

obviously the friction and the setup,

13:18

right? There is more of a learning ramp.

13:20

You need to be comfortable enough with a

13:22

command line to run basic operations.

13:24

The trade-off is that the code truly is

13:26

yours. It lives in your repo. You get to

13:29

read it. You get to modify it. And so

13:31

for someone who wants to either really

13:33

learn deeply or build for the long term,

13:36

this is often the right call. The extra

13:38

friction up front essentially pays

13:39

dividends in control and flexibility

13:41

down the one more concept for both of

13:43

these that's worth kind of keeping in

13:45

your mind. AI coding tools degrade over

13:47

conversation. The model will contradict

13:50

itself. It will forget what it built

13:51

etc. Your solution in both cases is to

13:54

break work into small tasks and run each

13:58

task as much as you can in a fresh

14:00

context window. Instead of one long

14:02

conversation that can meander, make sure

14:05

that you have clear tasking for a

14:08

particular job and you can define it

14:10

precisely. Now, if you're more complex

14:12

and you're setting up a full engineering

14:14

project, this often looks like defining

14:16

a spec and assigning multiple agents to

14:18

work on it. But in vibe coding honestly

14:20

what it often looks like is you write

14:22

out what you want to accomplish and then

14:25

it's like a very simple task in lovable

14:27

this one thing that I want to do or it's

14:29

a very clear ask to fix this particular

14:31

thing and tell me when you're done in

14:32

cloud code and you can build real stuff

14:35

right you can build a working web

14:36

application easily in a weekend at this

14:39

point you could build a client intake

14:40

form that saves responses to a database

14:43

no problem you can build an internal

14:44

tool for a small team that does

14:47

something well you build a personal

14:49

dashboard that pulls data from APIs that

14:52

you're already familiar with. These are

14:53

not at all impressive to professional

14:55

developers and they don't need to be.

14:57

These can be like very fun little

15:00

projects if you have that software

15:02

shaped mind we talked about. And yes,

15:04

you can build something more if you

15:06

want. You can build I've seen people

15:07

vibe code an entire customer

15:09

relationship management app for a small

15:12

business. Not a big business, right? not

15:13

something that's like hundreds of

15:15

people, but for a small business, it was

15:17

good enough. The skill that matters in

15:19

all this is learning how to code to

15:22

extract the most value. And this is

15:25

something that is really intuitive if

15:27

you're an engineer, but it may not be

15:29

intuitive if you've never engineered

15:30

before. Because the valuable skill isn't

15:33

really coding anymore. It's

15:34

specification. And experienced

15:36

developers know that. They know how to

15:38

break problems into pieces so that what

15:40

is coded is very very useful and

15:42

contributes to a hole. They know what

15:44

questions to ask, what happens when a

15:46

user isn't logged in, what if the

15:48

database is slow, etc. Beginners tend to

15:50

prompt more vaguely and accept whatever

15:52

the AI generates. Now, you don't need to

15:55

be a professional developer to walk

15:56

across this bridge, but you do need to

15:58

develop enough intuition to specify

16:01

clearly and evaluate with a degree of

16:03

critical thinking. It's a much smaller

16:05

gap than learning to code from scratch

16:07

and it will close faster with practice.

16:09

Essentially, you need to build an

16:11

intuition for building softwares shaped

16:14

things. Start small. Notice what goes

16:16

wrong. Develop a sense for what

16:18

questions to ask effectively if you want

16:20

to develop a vibe coding hobby. The more

16:22

small projects you work on, the faster

16:24

you tend to go. And so, if I were to

16:26

give you a few pieces of advice if you

16:28

wanted to start building, one, it really

16:30

is fun. Start with something you

16:32

actually want. That's going to give you

16:34

motivation and help you get going. Two,

16:36

describe before you build. Actually,

16:38

take the time to write it down. I talked

16:40

about that earlier in the video. Three,

16:42

accept that your early attempts, they're

16:44

going to be rough, and that's okay, and

16:46

it's part of building your intuition.

16:47

Four, just stay in the shallow end until

16:50

you're comfortable. You don't need to

16:51

jump to build something really big.

16:53

Remember, you can be playful. Five, know

16:55

when to ask for help. There's a

16:57

fantastic community of very experienced

16:59

engineers who also vibe code. They hang

17:01

out on X. They hang out in Discords.

17:04

Frankly, they hang out in my Substack

17:05

chat. You can ask them and you will get

17:07

lots of answers. I don't know where the

17:10

software creation hobby is going to go.

17:12

It's all exploding faster than we can

17:14

keep track of. Maybe it stays niche, but

17:16

the tools are going mainstream and I

17:18

built a little app for that may soon

17:20

become as common as I made you a

17:22

spreadsheet. And what I keep coming back

17:24

to is the conjunction of three things

17:27

that haven't been true before. Building

17:29

software is now inherently satisfying.

17:31

It's the feeling of making something

17:33

that just works. That has always been

17:35

true, but it used to be gated behind

17:37

years of specialized learning, and

17:39

that's not the case anymore. Two, the

17:41

internet has nearly infinite demand for

17:43

interesting things. That's been true for

17:45

a while, but finding out what the

17:47

internet had demand for was historically

17:49

very expensive. You had to invest real

17:51

time and money before you knew. And

17:53

three, the cost of building something is

17:55

approaching zero for hobby scale

17:57

software. that is really new and making

18:00

it fun is even newer. It's just a few

18:02

weeks old. The cost of experimentation

18:04

and playfulness has collapsed. If you

18:06

put all of those together, something new

18:09

emerges here. You can be playful. You

18:11

can try the idea. If it doesn't work,

18:12

you didn't lose that much time. If it

18:14

does, maybe the internet loves your dog

18:16

pictures. So, this isn't really about

18:18

hustle. This isn't really about an

18:20

arbitrage opportunity. Although you can

18:22

use these same skills for both of those

18:24

things. It's closer to what happens when

18:27

any creative tool becomes widely

18:30

accessible. Like photography, when

18:32

people have a smartphone in their

18:34

pocket, more people take cool pictures

18:36

and the things they make are more

18:37

creative and weirder and more varied

18:39

because we're just a very diverse

18:40

species. Now, some people will use this

18:42

tool and walk through the door and build

18:44

businesses and that's fantastic and the

18:46

startup use cases are real. But the

18:48

interesting story may be the people who

18:50

walk through just to make things fun.

18:52

They don't necessarily have growth

18:53

metrics. They just have the pleasure of

18:55

building their own tools and following

18:57

the ideas where they lead. The exciting

18:59

thing to me is that the tools exist now

19:01

that make that degree of playfulness

19:03

possible. And the internet truly becomes

19:05

your playground. And frankly, if that's

19:08

you, I'd love to see what you've built.

Interactive Summary

The video discusses a shift in the AI discourse from an ominous focus on job displacement and risks to a more playful and creative approach to software development, termed 'vibe coding.' This shift is enabled by recent advancements in AI models that allow for longer context retention and more mature agentic patterns, significantly lowering the friction of building software. Previously, creating software required significant effort and specialized knowledge, limiting it to serious projects. Now, the reduced barrier to entry allows individuals to build software for fun, leading to the creation of unique, sometimes absurd, but often delightful applications like Fable, which generates Renaissance-style portraits of pets. This democratization of software creation is compared to the evolution of photography, where smartphones made everyone a photographer. The video highlights that the satisfaction of creating something tangible is now accessible to a wider audience, including hobbyists and those without formal technical backgrounds. It introduces the concept of 'software vision,' the ability to perceive repetitive tasks or problems as opportunities for software solutions, which is becoming more crucial than traditional coding skills. The video also addresses potential failure modes, such as building without clear purpose or confusing a working prototype with a production-ready application, and suggests strategies for effective vibe coding, like clear specification and iterative development. Finally, it points to the two main paths for using AI coding tools: builder platforms for speed and simplicity, and command-line tools for greater control and learning. The core message is that the cost of experimentation has collapsed, making software creation a more accessible and playful endeavor, fostering creativity and leading to a diverse ecosystem of applications.

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