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I Tested Claude Code: $20 vs. $200 Subscription

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I Tested Claude Code: $20 vs. $200 Subscription

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491 segments

0:00

So, you've been hearing about this

0:01

Claude Code lately, or maybe you even

0:03

went out and got an Anthropic

0:05

subscription for 20 bucks, and you're

0:07

using Claude Code a little bit, and you

0:09

wonder, should I pay 200 bucks? Is it

0:12

worth it? Today, we are definitely going

0:15

to find out. Oh man, did the vibes go

0:18

bad? Oh, good gosh, how far did these

0:21

things get? This is amazing. Holy

0:24

mackerel.

0:26

[Laughter]

0:29

All right. What What is going on,

0:32

Claude? I'm going to throw the same

0:35

request, the same PRD at both Opus and

0:38

Sonnet. That's the differentiation

0:40

between the $20 plan and either one of

0:42

the Max plans. And we're going to see if

0:45

there's an actual difference between the

0:47

output on these and whether or not it's

0:49

immediately needed that you upgrade from

0:51

20 bucks to $200 or maybe you don't need

0:55

to or exactly when you should. Those are

0:58

all the questions that we're going to

0:59

look into today. Let's dive in. This is

1:01

just kind of an experimentation project

1:03

today. Let's go have some fun. Okay. I

1:06

love these kinds of things. I hope you

1:07

do, too. This is just me running some

1:09

experiments in two different modes. So

1:12

on the left we have Opus and on the

1:14

right we have Sonnet. I have prefilled

1:17

the project a little bit. So I've got

1:19

Nex.js installed and shad CN just so

1:22

that they could be kicked off

1:24

appropriately. What I've done is I've

1:26

worked with 03 in chatbt to try to get a

1:30

very explicit PRD which is a

1:33

requirements document. I also have a

1:36

design doc which gives a very brief idea

1:39

of what we're trying to build. I will go

1:41

into each one of these and make sure

1:43

that this one is set to opus and this

1:45

one is set to sonnet so that we lock

1:47

them down. And lastly, what I will show

1:50

you is the design dock themselves. So

1:52

what I've done is I've broken it into

1:54

two parts. We'll do phase one and it

1:57

will hopefully build a bit of the

1:58

architecture and then the second one

2:00

over here. It's got the same top, but

2:02

then it has the intelligent variance.

2:04

So, how do we use LLMs and that kind of

2:07

information to enhance what we're

2:09

building? And so, I wanted to say, okay,

2:11

if I only had the $20 plan, what kind of

2:13

outcome do I have with the same starting

2:15

point? If I have an expensive plan, what

2:18

kind of outcome do I have? That's

2:20

basically what we're running. Frankly, I

2:22

did this yesterday and both of them fell

2:24

on their face. So, I gave these two

2:27

phases that you just saw me describe. I

2:30

gave them both at the same time and I

2:32

didn't give any of the technical

2:33

details. I let them do the planning. I

2:35

thought well if you do have one or the

2:38

other maybe the technical plan is also

2:40

something that we want to evaluate and

2:42

the problem was they both went in kind

2:44

of very different directions and fell on

2:46

their face for different reasons and it

2:48

became really difficult to evaluate.

2:50

Okay, if we look at the anthropic docs,

2:52

really what I want to point out is just

2:54

a few simple things is they say Claude

2:56

for Opus delivers sustained performance

2:59

on longrunning tasks that require

3:01

focused efforts and thousands of steps

3:03

with the ability to work continuously

3:05

for several hours and it dramatically uh

3:08

outperforms all the other sonnet models.

3:11

Okay, I got them both started and then I

3:13

pulled up the browser. So remembering

3:15

this is Opus over here. Opus does run

3:18

excellent. So, this already looks pretty

3:20

good. On this side, I have a single

3:23

error. I am not going to fault anything

3:25

for having a single error. So, let's

3:27

collapse that and give it that error and

3:30

give it a chance to fix it. If I was

3:32

asking whether or not I needed to spend

3:34

10 times more money to get a

3:36

subscription so that I could do the same

3:38

kind of work, I'm willing to fix one

3:40

bug. And it turns out I fixed I just

3:42

pasted that one bug in and it did fix

3:44

it. At least it got it to this point.

3:46

Now, admittedly, we don't think this

3:48

project is done yet. So, I don't want to

3:50

go too far, but this is fantastic. Just

3:53

seeing this. By the way, like I said, I

3:55

did this yesterday and oh man, did the

3:58

vibes go bad. All right, so I'm going to

4:01

stop here and say, let's move on to

4:03

phase two just to say this is where it

4:05

got us for phase one. What does phase

4:08

two look like? I will peek under the

4:10

hood of these. Here we go. I'm going to

4:12

let you help me peek under the hood. I

4:14

will not judge them for any of this

4:17

being wrong. So, we're going to create a

4:19

project called librarian. That one

4:20

worked. Let's create a project called

4:23

librarian. Okay. All I am so gunshy from

4:26

yesterday. This is already great. So,

4:29

let's open this project first. All

4:32

right. Looking pretty pretty reasonable.

4:34

Open this project. I mean, these are

4:37

great. Do I have to keep going? I'm just

4:39

nervous. I know you're not nervous with

4:40

me, but All right. Ah, that looks

4:44

brilliant.

4:47

Also brilliant. Oh, good gosh. How far

4:50

did these things get? This is amazing.

4:53

Uhhuh. All right, let me resize these so

4:56

that we can see. Yeah, these are nodes

4:58

that you'll be able to move around on a

5:00

board as expected. Holy mackerel.

5:05

Okay, this is so many steps ahead of

5:08

what I hit yesterday. This is where I

5:09

thought I would get. So, I'm hugely

5:12

excited here. I'm going to stop here

5:15

because I do know that it has not tied

5:17

in some of the other moving parts. I

5:19

mean, do I know that? Okay, let's let's

5:22

put something in here. Okay. All right.

5:24

I have not gone any further than this.

5:26

I've just filled in uh small elderly

5:29

female librarian and a little piece of

5:31

text. And first, let's hit create clips.

5:35

I don't expect it to do anything, but

5:38

let's give them a shot. All

5:40

[Laughter]

5:44

right. What What is going on, Claude? Oh

5:48

my god. Is anyone else freaking out

5:52

right now? I did not expect it to get

5:54

nearly this far. All right. The designs

5:57

are definitely different, but they're

5:59

both frankly quite attractive. All

6:01

right. Are we ready? This one's 8

6:03

seconds long, apparently. Oh, it doesn't

6:06

play. Okay, that's fair. Doesn't play.

6:09

Not shocking. And we definitely have an

6:11

issue. No supported sources. Fine with

6:14

it. Fine with it. This is so much

6:15

further than I expected. Let's try on

6:17

this side. Excellent. Same thing. Okay.

6:20

So, this got us incredibly far. I don't

6:24

have the variance. That's actually in

6:25

phase two of the document. So, let's go

6:27

add that so that we can see what the

6:29

variants work like. But I don't know if

6:31

you could tell. I'm actually blown away

6:33

by this. Oh, I can't wait. I got to go.

6:35

Here we go. Okay. I'm gonna cover really

6:38

briefly what's inside of this thing.

6:40

This thing is I'm It's relatively

6:42

sophisticated, frankly. It's not one

6:44

moving part that's in here. We've seen

6:47

some of this already with that

6:49

mindblowing first pass of the PRD. It

6:53

created an endless canvas. There are

6:56

utilities out there that it's using. So,

6:57

it did not build all of that. It's using

6:59

open-source solutions. They're both

7:01

using the same intentionally. That was

7:03

part of my brief. They both put that

7:05

inless canvas down perfectly. There is a

7:09

set of LLMs that we'll be using and

7:11

that's the variance. We'll see that in

7:12

the next step. This is this step of I

7:15

want to create I have a voice. So

7:17

there's just a small elderly librarian,

7:20

but then I want to be able to use

7:22

intelligence to creatively alter the

7:25

prompt that I'm putting in. That's not a

7:27

great prompt obviously. So, we would

7:30

want something that's more descriptive

7:31

and kind of written in a way that a

7:34

voice model, which is we're using 11

7:36

Labs. You'll see this API down here is

7:38

an API that allows us to do text to

7:41

speech. And this in this case, what

7:44

we're allowed to do is create unique

7:46

voices and then do text to speech. So,

7:49

we're really trying to create new

7:50

characters with this definition. And

7:52

then there's a document database that's

7:54

storing all of this stuff so that we can

7:56

keep it in projects, come back to it.

7:58

So, that's the build. This is not a

8:00

small set of components to build from

8:03

just a simple PRD. So, I'm excited we

8:06

got this far. It's time for me to put

8:09

the second prompt in. Okay, I've put the

8:11

second prompt in. Let's let this cook

8:13

for just a minute. See what I can come

8:15

up with. Uh, they both finished again,

8:17

which is great. I want to try the create

8:20

variants. Let's create a variant off of

8:22

that. And here's another character. All

8:24

right. small elderly female librarian

8:27

but with exhausted night shift tone but

8:29

with heavy French accent. Okay. Uh all

8:32

right. So this is just very repetitive.

8:34

Something's going on. This feels

8:35

algorithmic. Okay. So full disclosure,

8:39

there's been a lot of back and forth.

8:40

There's a couple things that were

8:42

findings out of all of this. Really

8:45

still a pretty good experience and like

8:48

we mentioned kind of a sophisticated

8:50

project, but they're both ready. Let's

8:53

go take a look at what they have for us.

8:56

All right, here we are. We have Opus on

8:58

the left. We're going to create a new

8:59

project. Call it the cowboy. We'll do

9:01

the same over here. All right, let's

9:03

move into the cowboy in both cases. As

9:06

before, excellent looking. So, here we

9:09

are with our initial nodes for each one

9:11

of these. So, let me grab the data that

9:14

we're going to need to put into these.

9:15

So, what we have, if you recall, we can

9:17

create variants, which is basically a

9:18

new character. This one, in fact, called

9:20

it create characters. And if you hit

9:23

create characters, what it's going to do

9:25

is it's going to reach out and talk to

9:27

two LLMs as we talked about before and

9:31

create a new set of characters that are

9:33

related. What we've got is a warm,

9:36

easygoing male voice with a slight

9:38

southern draw on a calm, steady rhythm,

9:41

mid-range pitch with a touch of gravel

9:44

like someone who spent years outdoors.

9:46

So, it's kind of a cowboy sound at this

9:48

point. Um, so I will look into some of

9:50

these characterizations as well. And

9:54

here you'll see this warm, easygoing

9:57

male voice retains its slight southern

9:58

draw and calm, steady rhythm, but now

10:00

carries a pronounced Appalachian twang.

10:03

Okay, that one's interesting. Easygoing

10:05

male, southern draw, calm, steady

10:07

rhythm. Sounds like a man who's seen

10:10

some things, right? So, these aren't

10:11

terribly unique. I'm not so sure these

10:14

are really uh that creative yet. So,

10:16

that prompt probably needs some work.

10:18

All right. So, let's create some clips

10:20

for the grandfather and create some

10:22

clips for our original cowboy over here.

10:25

So, let's start with, "Well, now reckon

10:27

life's like riding a wild horse. You

10:30

don't get to choose the trail, but you

10:31

sure as hell decide how long you stay in

10:34

the saddle."

10:35

>> Well, now reckon life's like riding a

10:37

wild horse.

10:39

>> Okay, that one's interesting. I really

10:40

like this one quite a bit, actually. I

10:42

could use that one. This one sounds like

10:43

a cowboy on a telephone telling a story

10:45

from the old days, basically. That one's

10:48

kind of interesting. All right. What

10:49

does this guy over here got?

10:50

>> Well, you know, when I was just a young

10:53

fella, we used to spend every summer out

10:56

by the old oak tree, watching the stars

10:59

light up the night sky.

11:02

Well,

11:04

you know, when I was just a young fella,

11:06

we used to spend every summer out by the

11:08

old oak tree watching the stars light up

11:12

the night sky.

11:13

>> Okay, I like that one. So, this is

11:14

another one that I like quite a bit. And

11:16

of course, then you would just start

11:18

working from here. So, we could take

11:20

this one and say space cowboy,

11:23

but not just space cowboy. Let's create

11:26

a new one from him and start creating

11:29

other variations of a space cowboy.

11:32

Rugged space cowboy.

11:34

>> Well, now, partner, ain't it a fine

11:36

sight to see the

11:38

>> No, no, no, no. This is too boring. Out

11:41

here among the stars, you learn real

11:43

quick that justice ain't just a word.

11:45

It's a way of standing tall.

11:48

>> Out here among the stars, you learn real

11:50

quick that justice ain't just a word.

11:53

out here among the stars. You

11:56

>> No, no, no, no, no, no. Okay, so let's

11:59

see. We got kind of a crazy figure now.

12:02

Let's see if that helps.

12:03

>> Keep your heads low and your mouth shut.

12:06

You move when I say not a second before.

12:08

These bots don't miss. And I'm not

12:11

dragging any more kids back in pieces.

12:13

Let's go.

12:14

>> Awesome. That was really good. Let's try

12:16

the ones from Sonnet. It doesn't really

12:19

matter. It's all 11 Labs at this point,

12:21

but it's fun. Keep your heads low and

12:22

your mouth shut. You move when I say not

12:25

a second before. These bots don't miss.

12:27

And I'm not dragging any more kids back

12:29

in pieces. Let's go.

12:31

>> All right. I mean, honestly, that's a

12:34

success. So, there are some nuances

12:36

here. You will still need to engineer

12:38

things. So, I don't want to paint too

12:40

rosy a picture that you can just create

12:42

this cold from a few prompts. But

12:44

really, honestly, it got super close to

12:47

creating this really well from just a

12:49

few prompts. And then the engineering

12:51

part of it kind of really takes hold. Uh

12:54

so I would call this frankly a complete

12:57

success on both of these. Okay, closure

13:00

here. Right. So this one I'm struggling

13:02

with just a little bit. It was a great

13:04

experiment to run these side by side.

13:07

Oh, hold up. One last thing. You just

13:11

thought we were done. Let's go take a

13:13

look at this special surprise that I've

13:16

got for you. Yeah. Yeah, that's right.

13:19

You knew I was going to do it. You knew

13:20

it was happening behind the scenes. I

13:23

can't fool you anymore. I decided to

13:25

also do this in Gemini. And I will

13:27

admit, I did not go nearly as far with

13:30

Gemini. It got to a success place very

13:33

quickly, but I never got to the

13:36

completion of pushing back in multiple

13:37

times to create the files and a couple

13:39

other things. Let's take a look. This is

13:42

the project as Gemini created it. And it

13:46

it really this is many times I've done

13:48

this with Gemini as a comparison between

13:50

this and Claude Code. And Gemini's

13:52

design is never as thoughtful. It's very

13:55

fast. It's probably twice as fast,

13:57

frankly. And its engineering seems

13:59

really pretty good, but it just does not

14:01

create any thoughtful design whatsoever.

14:04

So, if we go into the librarian project

14:06

here, you can see like it won't save the

14:09

locations of things. I didn't work my

14:10

way through that, but you can see many

14:12

of the other parts. So, it can create

14:14

clips even though they won't play. I

14:16

didn't go back and say use the the file

14:18

as a clip. Trying to get to one. Okay.

14:20

Well, let's use this character. If we

14:22

create a clip, it'll go and create

14:23

clips. If we create variants, it'll go

14:25

down and create more variants. So, this

14:27

was Gemini completing very quickly and

14:30

truly for free. I mean, I can't say

14:32

enough about free. If you were looking

14:34

for an outcome of this, I know you

14:36

weren't expecting Gemini CLI again. And

14:39

I love 2.5. This is the 25 Pro model.

14:42

So, I really do like what it does, but

14:44

honest to gosh, it does not compare to

14:47

the completion aspect that Gemini is

14:50

bringing to things. And really, the

14:51

design here to some degree matters. Some

14:54

of the thoughtfulness of the way the

14:55

error messages and things like that

14:57

happen are really pretty well thought

14:59

out. even the layout of the screen and

15:02

what it looks like to start the

15:04

application. These are pretty obvious

15:06

things for it just to create a label at

15:08

the top and a linked list below it is

15:11

super old school. So it feels like it's

15:14

meeting the spec rather than kind of

15:16

using some intelligence to figure out

15:18

how it can meet the spec creatively. All

15:21

right, so that's my Gemini comparison. I

15:23

wanted to share that. You knew it was

15:24

happening behind the scenes. Success.

15:27

Okay. And now for the actual uh kind of

15:30

conclusion here. What do I think? Is it

15:32

better? Like full stop. No, it is not

15:36

better period. Was it better during

15:39

development to have Opus? No. It took

15:41

longer. Sonnet did a fantastic job.

15:44

Finished much faster than Opus and had

15:46

far fewer errors, frankly, that it

15:48

couldn't get out of. In fact, I didn't

15:50

run into any that it just couldn't get

15:51

out of. And I think in there is the

15:53

surprising answer. So agentically, I

15:56

think all models become far more

15:58

performant with a good solid agentic

16:01

loop. Anything that has an evaluation

16:04

process and is really thoughtfully

16:06

utilizing the tools that it has is going

16:08

to be far more performant than the model

16:10

itself. And I think that's the answer.

16:13

What's happening here is claude code is

16:15

the agent loop. What's happening in

16:17

Claude Code I believe is partially

16:19

inside of Opus is this agentic kind of

16:22

comparative evaluator that's going on

16:25

inside of that thinking loop is what

16:27

Claude code has built into it so that it

16:29

can use something simpler like sonnet

16:32

and so sonnet starts to behave a lot

16:34

more like opus and I think that's why a

16:36

lot of people that are using this are

16:37

starting to say I use sonnet a lot I do

16:40

go into opus when it's a big problem

16:42

even I have used opus in a scenario

16:44

where I thought wait this is this is not

16:47

solving the problem. Sonnet is going in

16:48

circles and having the same problem. Let

16:50

me go up to Opus and it really has

16:51

solved the problem. So, there is a value

16:53

to it. It's there. But is it worth $80?

16:58

I would say no. Is it worth you know

17:01

$180?

17:03

Definitely. Unquestionably no. However,

17:06

the one thing and this is this is the

17:09

final takeaway. Best thing I can tell

17:11

you is I think Anthropic has their

17:15

metering done just right. The way that

17:17

they limit it per five hour block allows

17:20

you to bump into your thresholds at a

17:22

given moment and realize you're getting

17:23

closer to it and understand that oh my

17:26

gosh in a couple hours, 2 hours, 3

17:28

hours, I'm going to have to refresh. I

17:30

have to wait until that time. So, I

17:31

either slow down now or I'm kind of out

17:33

until that time rather than I'm done

17:35

until the next day or in case in in many

17:38

cases V3, I'm looking straight at you.

17:40

Uh, you're done for the month.

17:42

Congratulations, you're on day three.

17:44

You got no more credits. You're out of

17:46

here. That really sucks. So, with that

17:49

awesome metering that they have, you'll

17:51

know when you need to upgrade. This is

17:53

the beautiful part. I think Anthropic

17:55

built exactly the right set of tools. I

17:57

mean, we I cannot applaud enough for

17:59

what they've built. Go get the $20. Use

18:02

Claude code because it is literally

18:04

fantastic. $20 absolutely will get you

18:07

there until you notice that you're being

18:09

limited. Once you're being limited, you

18:10

realize, oh, I'm going to have to move

18:11

up because I use too much and that's it.

18:14

And if you start hitting that limit when

18:15

you're on the $100 plan, you got to move

18:17

up again. So, they've really done it

18:20

exactly right. And it's not really the

18:21

Opus upsell. The upsell is excellent.

18:24

It's upsell so that you can get, you

18:26

know, a little bit more traction on your

18:28

coding efforts. That's it. That's the

18:30

takeaway. I know. I think we were all

18:33

hoping that Sonnet would clobber Opus in

18:35

some crazy way and we'd all go, "Oh, we

18:38

don't need the $200 model." And you

18:40

really don't. My answer, I guess, is you

18:41

really don't unless you need it, but

18:43

you'll know you need it. It's It's not a

18:45

surprise. Don't Don't FOMO over it. Get

18:48

the $20 plan. You'll be perfectly fine.

18:50

Okay. I hope you got something out of

18:51

this one. Really, thanks for coming

18:53

along for the ride on this one and I'll

18:55

see you in the next

Interactive Summary

The video provides a practical comparison between using Claude's Opus and Sonnet models within Claude Code for software development. The creator tests both models by building a sophisticated 'librarian' project to determine if upgrading from the $20 monthly subscription to the more expensive plan is worthwhile. The conclusion is that Sonnet is remarkably capable and often faster, making it sufficient for most users. The decision to upgrade should be based on Anthropic's clever usage metering, which informs users when they hit limits and truly need more capacity, rather than just FOMO.

Suggested questions

3 ready-made prompts