HomeVideos

CLAUDE SKILLS FULL COURSE: Automate Your Work (2026)

Now Playing

CLAUDE SKILLS FULL COURSE: Automate Your Work (2026)

Transcript

1555 segments

0:00

Hey, welcome to the definitive resource

0:01

all about skills. I currently run a

0:03

business that does over $4 million a

0:05

year in profit and I manage it primarily

0:07

through AI agents and skills and I teach

0:09

over 2,000 people how to do the same

0:11

thing. I think a lot of demos and

0:13

walkthroughs of skills right now are

0:15

like really flashy and they're typically

0:17

centered around the personal assistant

0:19

angle, but a lot of people are leaving

0:20

tons of money on the table because

0:22

they're not applying them to specific

0:23

business use cases that actually tend to

0:25

produce large returns on investment. And

0:27

so what I wanted to do in this resource

0:29

is I just wanted to walk you guys

0:30

through what that actually looks like.

0:32

I'm going to start by showing you guys

0:33

examples of a bunch of skills that I

0:35

currently use in my $4 million a year

0:36

business, as skills that other people

0:38

are currently using across a variety of

0:40

different industries like e-com, service

0:42

businesses, consulting, and so on. And

0:44

then I'm going to show you guys how to

0:45

build them. And we're not just going to

0:46

build cookie-cutter skills that are

0:48

glorified personal assistants, but

0:50

skills that you guys could actually

0:51

implement in your business to do the

0:52

work of dozens of people in just a few

0:54

minutes. Okay? So everything you need is

0:55

in the link in the description. It'll

0:57

give you guys these skills so you guys

0:59

could use them across your own business.

1:00

It'll also give you guys the framework

1:01

that you could use to to build new ones

1:03

regardless of whatever use cases. No

1:05

fluff. Let's get right into it. So if

1:07

you don't know what I'm looking at right

1:09

now, this is anti-gravity running five

1:11

different Claude Code plugins.

1:13

If you guys are new or unfamiliar with

1:15

this sort of interface, just check the

1:17

link that I'm pasting right over here.

1:19

It'll walk you through everything from

1:20

like what the icons here mean to, you

1:23

know, how to communicate with Claude

1:24

Code and Gemini and and other, you know,

1:26

agent and coding platforms. I'm

1:28

literally from the ground up. So you'll

1:29

know everything after that. But assuming

1:31

you guys are somewhat comfortable, I

1:32

want to show you guys five different

1:34

skills today and then I'll throw in a

1:35

couple of additional bonuses. The first

1:37

one over here is going to follow up with

1:38

all of my leads. So if you guys are

1:40

running a business at really any level

1:42

of revenue over a few thousand dollars a

1:43

month, you probably have something akin

1:45

to like a list of leads or a list of

1:47

contacts. This type of thing is

1:48

typically referred to as a customer

1:50

relationship manager and in general what

1:52

you do is you store leads at different

1:54

areas along the pipeline from when you

1:56

first met them all the way to close

1:58

deals and money is in your pocket. And

1:59

so, I have an example one here with a

2:01

bunch of leads at different stages.

2:03

Meeting booked, Jimmy Clin. Proposal

2:04

sent, Sarah Chen, Jessica Park, Aisha

2:07

Mohammad, and so on and so on and so

2:08

forth. And basically, right now, in

2:11

order for me to move this pipeline

2:12

forward, every day I just have to

2:13

manually check in with all the leads.

2:15

Well, I built a skill that effectively

2:17

automates the entire process. In order

2:19

to trigger this, all I need to go and do

2:21

is go {backslash} follow up nurture.

2:24

Now, what this skill does is it'll goes

2:25

through my pipeline. It identifies and

2:27

captures all of the conversations I've

2:29

ever had with any of these prospects.

2:31

So, it actually goes through all of my

2:32

email chains and so on and so forth. And

2:34

then it uses a couple of templates to

2:36

personalize check-ins uh depending on

2:38

where they are. So, you know, if a

2:40

meeting has been booked, but we haven't

2:41

actually attended it, it might check in

2:42

with Jimmy and say, "Hey Jimmy, how's it

2:44

going? Just wanted to check in on our

2:45

meeting in a couple days. Really excited

2:47

to have it." You know, if it's to Sarah,

2:49

and maybe we send a $2,500 quote for a

2:51

specific type of product, I'd be like,

2:53

"Hey Sarah, you know, hope you had a

2:55

lovely week so far. Just wanted to

2:57

circle back on X, Y, and Z proposal. Let

2:59

me know if you have any questions." The

3:00

whole key here is we do this really

3:02

informally and then really casually, so

3:03

they think it's us. I think a big

3:05

problem that a lot of these automated

3:06

follow-up services typically run into is

3:08

they just use really like non-human

3:10

language. It's very clear, and you know,

3:12

I think prospects can tell when an L L M

3:14

does the following up for them. But, I

3:15

also like the fact that this just does

3:17

it all in one shot. And so, the workflow

3:18

is literally like you just wake up in

3:20

the morning or your salesperson wakes up

3:21

in the morning. Um they go {slash}

3:23

follow up nurture. They immediately

3:25

clear out their full pipeline of

3:26

follow-ups, and then they can just focus

3:27

on acquiring new business. What's also

3:29

cool is it does all this in the tone of

3:30

voice and in the same chain of

3:33

conversation as the initial email. And

3:35

so, in this case, this is an email that

3:36

I sent to Mr. James that said, "Hey

3:38

James, circling back on the proposal.

3:39

Let me know if I can answer any Qs." Uh

3:41

this is another one that I sent to Priya

3:43

that said, "Hi Priya, hope you had a

3:44

great week. Checking in on that test

3:46

brief. Let me know where we're at." You

3:47

know, this just continuously customizes

3:49

based off where the person is. And then

3:50

it also gets to pull in, you know,

3:52

context and

3:53

uh more or less everything that you

3:54

currently talked about. So, you're not

3:55

just repeating the same thing. This also

3:57

goes through and then it lists all of

3:58

the follow-ups that I've made to every

4:00

single person. So, you can see here

4:01

we're signing off slightly differently

4:02

between them. We're using uh reply

4:04

chains and stuff like that to stay

4:05

within the same thread. Um and I'm going

4:07

to give you guys that for free. I use it

4:09

basically every day. This second flow is

4:11

basically a one-shot thumbnail

4:12

generator. Um I have this funny image of

4:15

Jon Hamm or Don Draper in Mad Men, if

4:17

you guys are familiar. And this image

4:18

went viral a little while ago. It's all

4:20

about vibes and whatnot. And so, I

4:21

figured, you know, as somebody making

4:23

videos on vibe coding and agentic

4:24

platforms, I would try and reproduce the

4:26

thumbnail. Um but instead of doing it

4:28

manually, I'm actually just going to

4:29

say, "Reproduce the Jon Hamm thumbnail.

4:31

Use similar lighting, etc."

4:33

And then what it's going to do is it's

4:35

going to take this thumbnail or this

4:37

image, which has already been created,

4:38

then it's going to go get my face, and

4:40

then it's just going to superimpose my

4:41

face onto that image in a really

4:43

realistic-looking way. It's also,

4:45

instead of just generating one variant,

4:46

going to generate multiples so that we

4:48

can pick and choose which one looks the

4:50

best. And also because not all AI

4:52

outputs are perfect. This is an example

4:54

of the finished product, and we did that

4:55

just in a few seconds. Um I also ran it

4:57

again so you guys could see even more,

4:59

but I mean, just like going back and

5:01

forth between this, pretty freaking

5:02

close, right? However, there are some

5:04

important differences. The people in the

5:05

background are different. The lighting

5:07

is just a tiny bit different, uh and so

5:09

on and so forth. And I mean, we've we've

5:11

generated more. Uh I have this running

5:12

again in the background. This one's with

5:14

like a darker lighting and different

5:15

tone. Uh I don't know. This one here is

5:17

sort of like Matrix-style blue and

5:19

sepia. And so, all these are just a

5:20

little bit different. One's that it's

5:22

not just like a one-to-one rip of the

5:23

source image, um but also because, you

5:25

know, I get to pick and choose variants

5:26

that I like the most. And so, in my

5:27

case, I really like this one. I think

5:28

this like did the most justice to my

5:30

face, and this is probably the one I'm

5:31

going to use for my video. By the way,

5:32

despite the fact that I hate when people

5:34

do this to me, I'm going to do it to

5:35

you. If you like this sort of thing,

5:37

please subscribe. Uh something like 69%

5:39

of you guys aren't subscribed for some

5:41

reason. So, that's two out of every

5:42

three people that I'm talking to right

5:43

now. And it just significantly impacts

5:45

my channel's ability to grow. So, if

5:47

I've given you anything, any value at

5:49

any point in time over the course of

5:51

this video or any others, just click

5:52

that button for me. You'd be doing me a

5:53

big solid. Okay, back to the video. This

5:55

next one here is all about scraping

5:57

leads, and so I can actually just say,

5:59

"Scrape me 50 management consultants

6:02

in I don't know, let's just say

6:04

Arizona." And what this will do is it'll

6:06

go on LinkedIn Sales Navigator, which is

6:08

currently the highest quality place that

6:10

you can get information about real human

6:12

beings. It then creates a bunch of

6:14

LinkedIn search URLs. And in case you

6:17

guys didn't know, LinkedIn Sales

6:18

Navigator allows you to filter people

6:20

really granularly based off things like

6:22

what their job title is, um where they

6:24

live, you know, their various seniority

6:26

levels, and other industry. And then

6:29

basically I just get a list, and not

6:31

within Sales Navigator, but in a Google

6:34

Sheet with these people and then all of

6:36

their email addresses. And like

6:38

pre-existing solutions exist to do this

6:40

for Apollo and AmpiFire, but I don't

6:42

think there's like currently a big one

6:44

for LinkedIn Sales Navigator. The reason

6:45

why that's valuable is cuz there is no

6:47

better source right now for B2B lead

6:48

data than LinkedIn Sales Navigator. It's

6:50

the most current. Um most other services

6:52

just scrape from there anyway. And as a

6:54

result, I got to go straight to the

6:55

source and then just ask a system for

6:58

what I want in natural language. Uh so,

7:00

within, you know, three or four minutes

7:01

I end up with a nicely optimized list of

7:03

high-quality leads with probably like

7:05

the highest deliverability out of more

7:07

or less any source that you could get

7:08

today. And then you end up with a really

7:10

high-quality list of people, literal

7:12

their full names, first names, last

7:14

names, email addresses, and so on and so

7:17

forth that we've sourced basically

7:19

directly from LinkedIn Sales Navigator.

7:21

Um this is done pretty effectively via

7:23

cost as well. And then the fact that

7:25

it's just going to occur in the

7:26

background while I do other tasks, it

7:28

can retest its leads, it can figure out

7:30

like the best filters to use, and so on

7:32

and so forth, um eliminates a fair

7:33

amount of my own day-to-day work as

7:35

somebody that runs like a growth

7:36

management agency. This next one here

7:38

writes my cold email campaigns. So, for

7:40

those of you guys that don't know, a

7:41

cold email is something that goes to

7:43

somebody who you haven't actually talked

7:45

to before, hence why it's cold, and then

7:47

it tries to sell them on some service.

7:49

And so, I run cold emails just as my

7:50

day-to-day for a couple of clients.

7:53

Essentially, what I commonly have to do

7:54

is I have to iterate and change cold

7:56

email campaigns based off of a new

7:58

client's information. And so, what I

8:00

want to show you guys is basically how

8:01

you can automate this process. I now I'm

8:03

going to use the backslash convention.

8:05

I'll go cold-email-campaigns.

8:07

Sorry, I think that's actually a forward

8:08

slash. And this will basically ask you,

8:11

"Hey, what are the details of the

8:12

client?" And now I'm just going to voice

8:14

transcribe and say, "The client is 1

8:16

Second Copy.

8:17

Their offer is they want to write free

8:19

500-word sample articles with no strings

8:21

attached. Find the similar campaigns and

8:24

then use those as inspiration."

8:27

I'm then going to feed that in, and then

8:29

my skill is going to go through and then

8:31

essentially duplicate high-performing

8:33

pre-existing campaigns within my cold

8:35

email platform, and then rewrite them so

8:38

that they're as similar and high quality

8:39

as humanly possible for that given

8:41

niche. Then sets it all up in my cold

8:43

email platform. So, again, a step that

8:45

previously might have taken me 30 to 60

8:47

minutes just logistically is now taken

8:49

care of. And then obviously all the

8:50

offer management stuff like that is also

8:52

handled entirely autonomously. So, yeah,

8:54

I mean, this takes something that might

8:55

be 3 or 4 hours into something that

8:57

takes minutes. And then afterwards, we

8:58

end up with a bunch of different

8:59

campaigns. This is an example of one of

9:01

them that says for, I don't know, Nick,

9:03

just wrote you a blog post. "Hey Nick,

9:05

big fan of your work. Was on 1 Second

9:06

Copy site earlier. Thought I'd write you

9:08

a free 500-word sample article with a

9:09

twist. I'm not giving value up front is

9:11

how you form connections, so I thought

9:12

I'd start with that. If you have any

9:13

interest, just reply and I'll send it

9:14

right over. If you want more, just say

9:15

the word. Got a few other interesting

9:16

pieces of content for you." It also

9:18

gives you different variants that you

9:19

could use to split test, and then also

9:21

even like a little follow-up. So, in

9:23

that way, you know, me just templating

9:24

out like 80 90% of my work significantly

9:27

streamlines the actual offer building

9:28

process. And nowadays, because the

9:30

models are themselves are getting really

9:31

good, like I was doing this with Opus

9:32

4.5. Now I'm doing it with Opus 4.6.

9:35

Because the models are getting really

9:36

good, like half the time I don't

9:38

actually make a change. I just say,

9:39

"Okay, sure. Let's give this a test and

9:41

we'll see how this performs relative to

9:42

some of the other ones." The last skill

9:44

I want to show you is a simple website

9:46

builder. Basically, to make a long story

9:47

short, you know, we do a fair amount of

9:49

outreach. My goal here is I wanted a way

9:51

to quickly and easily whip up

9:53

high-quality, reasonably templated, but

9:56

also pretty unique websites for clients

9:58

or prospects. And then just send them

9:59

over, whether or not I have their

10:01

business. I was thinking about ways to

10:02

offer more value while reaching out to

10:04

people cold. And um me literally

10:06

building like end-to-end high-quality

10:08

websites and then giving them a link

10:10

that they could use to access them in

10:11

one shot. It's probably like the biggest

10:13

value add that you can get so far. So,

10:14

this is like very, very low-hanging

10:16

fruit. And I would also say that there's

10:18

quite uh room right now to do knowledge

10:20

arbitrage, where basically because you

10:22

have access to tools like this and then

10:24

most prospects don't, you could offer

10:25

either completely free websites or you

10:27

could offer a like a really simple or

10:29

templated website or something like that

10:30

in order to really blow their socks off.

10:32

When it's done, it actually pushes this

10:33

to Netlify, which is a hosting service

10:35

that lets me get a website like this.

10:37

Then I can actually just click this link

10:38

and then I have the website right over

10:40

here. And I don't think you guys could

10:41

see it so super clearly, but um it's

10:44

pretty high-quality, you know, it uses

10:46

its own customized prompt in order to

10:48

build slightly different navigation bars

10:50

and menus and then uh different content

10:53

types and stuff like that. And then you

10:54

end up with I think what most people

10:55

consider to be pretty high-quality.

10:57

Guess you guys are interested, I

10:58

showcased a really similar builder on my

11:00

Claude Code course a little while ago

11:02

and then my Gemini course as well. Um

11:04

you know, this is pretty high-quality,

11:05

right? I think if an average person were

11:06

to get a website like this for free,

11:08

they'd probably be like, "No way,

11:09

really? There has to be a catch." But

11:11

nowadays, you can generate these

11:12

deliverables for basically cents on the

11:14

dollar and then get like high-quality

11:16

animations and stuff like that um with

11:18

literally you just putting one prompt.

11:21

So, obviously, I wanted to build a bunch

11:22

of economically valuable skills and I

11:24

have dozens more, probably close to 30

11:26

or 40 right now that manage most aspects

11:28

of my bu- business. But um I also wanted

11:31

to show you guys, sorry, that's my alarm

11:32

here. I want to show you guys how easy

11:34

it was also just to build skills that

11:35

handle like really nuanced one-off

11:37

things. And so, um, in addition, I also

11:40

built a couple of cool ones that I want

11:41

to show you. One called WeWork booking,

11:43

another called Amazon shopping. And I

11:44

mean like these aren't even really as

11:45

businessy as they are me just like

11:47

dealing with a problem that I had. So,

11:49

for the WeWork one, um, WeWork is a

11:50

shared co-working space which basically

11:52

allows you to book and then show up

11:54

sometime in the next few hours. Uh, you

11:57

have access to things like kombucha on

11:58

tap sometimes. Uh, I don't know, free

12:01

coffee. Well, it's not free, I guess

12:02

we're paying for it. Looks like their

12:03

marketing's worked on me. But to make a

12:05

long story short, um, in order for me to

12:07

access WeWork, I need to like book ahead

12:09

every day. And uh, one day I tried

12:11

booking the same day and then I showed

12:13

up and my card reader didn't work and I

12:14

was like, "Why?" And they're like,

12:15

"Well, it's usually good to book ahead

12:16

because sometimes the card reader takes

12:18

time to sync." And I was like, "Well,

12:19

this sucks. I don't want to freaking do

12:20

this." And then I realized like, "Wait a

12:22

second, I have Claude now. So, why don't

12:23

I just write a skill that just

12:25

automatically books me every single day

12:27

for like the next 30 days." And so,

12:29

that's what I did. Uh, I basically just

12:30

took like 30 seconds of my day. Then I

12:32

said, "Hey, write me a skill that books

12:33

me in for WeWork." So, when I want to

12:35

access it, I just go, "Book me into

12:38

WeWork." Then this goes and books me

12:40

automatically for like the next 30 days

12:42

ahead using some credentials that I've

12:44

already set up and then it also like

12:46

actually literally opens up a tab. So,

12:48

you could see this is doing it right

12:49

here at the one that I currently

12:51

frequent, um, Steven Avenue Place. So,

12:53

I'm just going to say, "Hey, hit me.

12:54

Give this a a book." And then it'll go

12:56

through and actually make like HTTP

12:58

requests behind the scenes in order to

13:00

to push. If necessary, it'll actually

13:01

also open up WeWork so you could see it

13:04

actually like do the freaking desk

13:05

bookings, which is wild. Um, and you

13:07

know, watching this thing go is pretty

13:08

neat. And then after I built this and

13:11

then, you know, did all of the WeWork

13:12

bookings, I also naturally got more

13:14

interested in like, "Hmm, what could I

13:15

automate with my browser?" And I ended

13:16

up creating another skill. So, that was

13:18

a pretty interesting one-off build.

13:19

Takes just like 30 seconds as you see

13:21

there. You just have to log into

13:23

whatever service and then say, "Hey, I

13:24

want you to automate this with Chrome

13:25

DevTools MCP." I'll show you guys how to

13:27

do that as well. But, I was also kind of

13:28

interested in um what else I could

13:30

automate that was just kind of like a

13:31

silly personal task that I used to have

13:33

to do. And one thing that I do nowadays

13:35

quite a bit is like I just buy stuff off

13:36

Amazon, and then I have it shipped

13:37

directly to my door. And I do that

13:39

because I think, you know, I'm making a

13:40

fair amount of money, and I don't really

13:41

want to drive all the way over to Home

13:42

Depot or whatever because it'll just

13:44

consume a lot of time and energy and

13:45

ultimately be unnecessary. Why not pay

13:47

for the premium of having somebody else

13:49

do it? The only issue is, as I'm sure

13:51

you guys know, anybody here that shops

13:52

on Amazon, there's like a bajillion

13:54

listings nowadays with like um

13:57

crappy SEO, and they try and use every

13:59

term to rank for everything. So, what I

14:01

did is I just built a really simple

14:02

Chrome DevTools MCP called Amazon

14:04

Shopping. And what I do is I simply say,

14:06

"Hey, find me the best floss on Amazon."

14:11

It then loads up the Amazon skill right

14:13

over here, and then it opens up Amazon,

14:15

in my case CA. And I'm just going to

14:17

make that a little bit smaller here so

14:18

you guys can't see my postal code. And

14:20

then it automates the process of like

14:22

going through Amazon and then looking

14:23

for whatever the heck I want. So, in my

14:25

case, I'm looking for dental floss,

14:26

right? Well, it's just going to open up

14:28

one little thing here, and then it's

14:29

going to go through, and it's going to

14:31

compare all of the dental floss with

14:33

each other to find basically the best

14:34

combination of cost and then

14:36

effectiveness that does whatever I want.

14:38

And at the end of it here, you can see

14:39

we have all of the products that it's

14:41

recommending um literally in just like a

14:42

little sheet, so I can give this a quick

14:44

click. We also have the cost, uh

14:46

popularity, the why buy, and so on and

14:48

so forth. Uh and then, you know, he

14:50

basically uses all these things in order

14:52

to recommend them. So, I basically built

14:54

like a personal shopper app. Um I've

14:55

done the same thing with like grocery

14:57

delivery, which is pretty cool. So, I

14:58

just one-shot my grocery delivery. I go

15:00

on, you know, Instacart or another

15:02

related service, click a few buttons,

15:03

and then boom, you know, I'm basically

15:05

done for the rest of the year. Uh and

15:07

you know, you could build these sorts of

15:08

one-off systems at this point now with

15:10

Opus 4.6, you know, GPT 5.2, 5.3, or uh

15:14

Gemini 3.1, whatever model you want to

15:15

use, whether or not you're using Claude

15:17

Code or some other platform, okay?

15:19

Now that you guys have seen at least a

15:20

little bit about what I think like

15:22

actual helpful useful skills that

15:23

realistically move the needle, not just

15:25

glorified um you know, personal

15:27

assistant demos look like. Let me show

15:28

you guys how to actually go ahead and

15:30

then build them. Okay, so first, if it's

15:32

not already abundantly clear, skills are

15:34

basically the evolution of standard

15:36

operating procedures just for agents.

15:40

Whereas SOPs and checklists are for

15:43

human beings for the most part, skills

15:46

are for these new AI agent

15:48

intelligences. And just as such, you

15:51

wouldn't really just give a checklist

15:53

over to an agent and say do it. You'd

15:55

have to translate its language just a

15:57

little bit into sort of like the native

15:59

format that the agent understands. So, a

16:01

brief example here, if I have maybe a

16:03

checklist and it's make a PB

16:08

and J sandwich. And you know, I work at

16:11

a company where all we do all day is

16:13

make PB&J sandwiches. Boy, would I love

16:15

to live there.

16:16

You can imagine how new hires go their

16:18

very first day and then they're given a

16:20

checklist of tasks. And it's basically

16:23

take bread

16:26

out of basket.

16:28

Put jam on one side.

16:32

Put peanut butter on the other side. And

16:35

then maybe one final one that just says

16:37

stick them together. So, this might be

16:39

for a human. And essentially, as a human

16:41

goes through it, what do we do? We

16:42

obviously check all of these tasks off.

16:45

That's just how standard operating

16:46

procedures are in business. They just

16:48

for the most part standardize things,

16:49

hence the name. Because this is

16:50

organized differently for agents than

16:53

you know, for human beings, we organize

16:55

them into what are called markdown or

16:57

.md files. And these markdown files are

16:59

basically just text files with a little

17:01

bit of a twist. For instance, I have a

17:03

markdown or .md file open over here. If

17:05

I try and create a new file here and

17:07

then I call it skill spec.txt and then I

17:10

paste everything in, you notice how

17:12

everything is the same color. Whereas,

17:14

if I go back to that markdown variant,

17:16

we all of a sudden have blue, we have

17:18

orange, we even have some green.

17:20

Well, the way that markdown files work

17:22

is they take base data, and then they

17:24

also take a little bit of formatting,

17:26

and then they apply the formatting to

17:28

the base data, just so that it's a

17:29

little bit easier to see, a little bit

17:31

more interpretable.

17:32

And so, if you guys could tell, the data

17:34

that we're marking up here, okay,

17:36

funnily cuz it's called markdown, but

17:38

the data that we're changing the the

17:40

color of and stuff like that, is usually

17:41

prepended with a couple of symbols. The

17:43

first symbol here is this little

17:45

hashtag.

17:47

This always refers to like a header. And

17:49

so, you can kind of think of it like a

17:50

chapter heading in a book. Another one

17:53

are these sort of backticks here, which

17:55

typically refer to files. There are a

17:57

couple of other little tiny formatting

17:59

things here, like links and so on and so

18:01

forth, that you don't really get with

18:03

TXT files, but hopefully you guys

18:05

understand that it's not really that big

18:07

of a deal to memorize everything in a

18:09

markdown file. You just have to know

18:10

that they're slightly different

18:11

formatting compared to text files. The

18:13

reason why is because you're never

18:15

really going to have to make them

18:16

yourself. All you're going to have to do

18:18

is just give your agent some bullet

18:19

points, usually a brief description,

18:21

which I'll show you how to do, and then

18:22

it'll combine all of that into the

18:24

optimal markdown skill format for you.

18:27

Now, unlike just a few months ago, today

18:30

every major provider on Earth,

18:32

basically, so our OpenAI's, our

18:34

Google's, our I wrote Claude here, but I

18:36

really meant Anthropic. They're all

18:38

moving towards harnessing and then

18:41

making skills generally available, just

18:43

as part of like their their their LLMs.

18:46

And so, here you could see Anthropic has

18:48

a page on their Claude code box that say

18:50

extend Claude with skills. These are the

18:53

guys that sort of made skills up first,

18:55

but because of popularity, a bunch of

18:57

people um that were OpenAI developers

18:59

and stuff like that started talking

19:00

about it and asking for it. And so,

19:02

they've created their own skills format.

19:04

It's very, very close to the Claude code

19:07

skills format. And then also, over here

19:10

the Gemini CLI, you could see you can

19:11

add agent skills.

19:13

Basically, no matter what framework or

19:15

LLM or platform you're using, you can do

19:18

the exact same thing. So, my rule of

19:20

thumb is if you guys have a standard

19:22

operating procedure, if you have an SOP,

19:25

you have a skill. Okay, all you really

19:27

have to do is just copy that SOP from

19:29

your business and feed it into Claude or

19:32

Gemini or Codex and ask it to make a

19:35

skill. As of the time of this recording,

19:37

the skills spec or definition is it's

19:41

not like baked directly into the models.

19:43

So, the one thing that you have to do in

19:45

addition to that is you basically have

19:46

to give it the skill spec and then ask

19:49

it to turn your task list into a skill.

19:52

But, assuming you can, you know, drag a

19:53

file into your freaking working

19:55

directory and assuming you have any SOPs

19:58

at all, even poorly written ones, you

20:00

now basically have an agent capable of

20:03

doing a big chunk of your knowledge

20:05

work. Once you're done with this, you

20:06

just ask the agent to run it at least

20:08

once cuz you have to test and amend.

20:10

On the first run, if the agent needs

20:12

something else, it'll ask you for it.

20:14

Otherwise, it'll build the asset

20:15

yourself itself. So, maybe like an Excel

20:18

file or something like that, it'll

20:19

actually put that together for you.

20:21

Although obviously if you have assets

20:22

like some contacts or PDFs or whatever,

20:25

you can provide them, no problem. And

20:26

then assuming that you prompted it right

20:28

with the spec that I'm going to provide

20:30

to you, every time the skill runs after

20:32

that, if the agent finds a mistake while

20:34

doing it or maybe a service is out or it

20:36

doesn't have the knowledge it needs,

20:38

it'll automatically figure out how to

20:39

solve it and then it'll patch the skill

20:41

for you. And so, in that way, here's the

20:43

real power of skills, they're

20:44

self-healing over time. They heal

20:46

themselves. They get better, they

20:47

improve constantly. Much like an

20:50

ambitious intelligent staff member who

20:52

sees a checklist, notices that there's a

20:54

gap and then chooses to fill it. Skills

20:56

are the same thing, just with agents,

20:58

which is what makes them so incredible.

20:59

So, why don't we get started and produce

21:01

ourselves some skills and then as we

21:03

produce and then shortly after, I'll

21:05

also run through the special directory

21:08

of dot Claude skills, which with Claude

21:12

is how you organize these things. I'll

21:14

also touch on just a couple of other

21:15

ones in case you're using a different

21:17

LLM. But for the most part, they're

21:18

going to be exactly the same.

21:20

So, the very first thing you need to do

21:22

is you need to grab the skillspec.md.

21:24

And you can grab that down below from

21:26

the Google Drive link. Um it's free, as

21:28

mentioned, you don't need to sign up or

21:29

give me your email. I don't need it. I

21:30

have enough of those.

21:32

And what you're going to see in here is

21:34

basically the condensed spec or

21:36

definition of skills, as well as the

21:39

file structure, all the locations, all

21:42

the different formatting options, and

21:43

stuff like that. Um and what we're going

21:46

to do is we're going to give this to our

21:47

agent alongside our request, so that it

21:49

can just figure out how to put together

21:51

the highest quality skills for us.

21:53

What I did in order to put this

21:54

together, by the way, is I just went

21:56

over to Anthropic's Claude code docs

21:58

with skills page. I copied the entire

22:01

thing, fed it back into the LLM, and

22:03

then just said, "Hey, I want you to

22:04

really, really shorten this, compress

22:06

this, significantly increase the

22:08

information density, because I don't

22:09

want this to be 500 lines. I want this

22:11

to be, you know, 150 to 200."

22:13

Okay, so once we have this, basically

22:15

what we do is we just make this our

22:16

Claude.md.

22:18

You know, just so we're on the same page

22:19

here, Claude.md is just the prompt

22:21

that's injected at the top of every new

22:23

conversation. And so, what I'm going to

22:24

do is I'm just going to rename this and

22:26

just call this old Claude.md. And this

22:29

one here is going to be the new

22:30

Claude.md or just Claude.md. Any

22:33

[snorts] file in your root directory

22:34

that contains the capital c a c l a u d

22:38

e dot lowercase m d will automatically

22:40

be prepended and and added to the

22:42

prompt. And so, what we do is basically

22:44

by by doing this,

22:46

every workspace where it is just

22:47

automatically going to know what skills

22:49

are. If you have other stuff in your

22:50

Claude.md, you can also just copy this

22:52

and then paste this um as well.

22:54

Although, you know, at least for the

22:55

purposes of creating skills, I recommend

22:56

just being as short and and

22:58

straightforward, and basically having

23:00

this in as few lines as humanly

23:01

possible. Next up, to build your skill,

23:03

just open up a new agent window. So,

23:05

I've just done that here with Claude

23:06

code, and then just tell it what you

23:08

want it to do. I'm going to use a voice

23:09

transcription tool, Whisper flow, just

23:11

to put in my own SOP.

23:14

What I want to do, at least for this

23:15

demo, is just build a simple inbox

23:17

cleanup tool that just goes through my

23:18

inbox, and then

23:20

opens up all of the unread messages, and

23:23

then just immediately reads all the ones

23:26

that are pointless and sort of, I don't

23:28

know, invoice reminders or follow-ups

23:30

about whatever or simple templates.

23:32

And then I want it to highlight, like

23:34

realistically, the high priority emails

23:36

in my inbox, so that I just have a short

23:37

list of everything. So, it's pretty

23:39

simple and straightforward. I'm just

23:40

going to hold this little key down, and

23:42

then say, "I'd like to build a Claude

23:45

code skill that goes through my inbox,

23:49

identifies all unread messages, reads

23:52

all of the unread messages, and then

23:55

marks as read all of the ones that

23:57

aren't

23:58

important to me or high priority."

24:01

My definition for important is basically

24:03

anything that isn't automatically

24:06

generated. If the email is automatically

24:08

generated by, like, a service or it's a

24:10

simple notification email or whatever,

24:13

it's not important. If the email is

24:15

written by, like, some cold email

24:17

copywriting fellow who's trying to reach

24:19

out and get my business, it's not

24:20

important. The only stuff that is

24:22

important are emails that are

24:24

personalized, customized, and that give

24:27

off the vibe that they were written

24:28

basically just for me. Once we're done,

24:30

we're going to feed that right in. Then

24:32

we're going to go ahead and build it.

24:34

The very first thing it's going to do is

24:36

look at all of the existing skills in

24:38

any Gmail code inside of my workspace

24:41

to see if there's anything that it could

24:42

use. And it's doing this because, you

24:44

know, as human beings go, we don't

24:46

really want to rebuild the wheel if we

24:48

don't have to, right? So, this is it

24:49

just reading everything right now. You

24:51

can see that it's also changed to plan

24:54

mode. That's why that little thing in

24:55

the bottom left-hand corner has changed

24:57

alongside that red bypass permissions

24:59

color to blue. This happens more or less

25:02

anytime you try and build something that

25:03

it would consider to be even slightly

25:05

complicated. It wants to go into plan

25:07

mode so that it can plan out the build

25:09

of the skill. Now it correctly went

25:11

through and found that I had a couple of

25:12

configuration files that allowed it to

25:14

use different emails here. And for the

25:16

purposes of this demo, I'm just going to

25:17

use this one. Obviously, if you didn't

25:19

have this, it would just ask you what

25:21

email do you want to set up. Now what

25:23

it's going to do is actually create the

25:24

skill the old on MD. It's also going to

25:26

create a script for me, which looks like

25:29

it's going to call inbox_cleaner.

25:32

Then afterwards, it's going to test it

25:33

end to end. Why? Because that's just

25:35

what's in our spec sheet. We basically

25:37

tell it how to do all of this stuff

25:38

natively.

25:40

Now what it's going to do is create the

25:42

script. You could see that because I

25:43

have a pre-existing skill, that

25:45

follow-up one that I was showing you

25:46

guys, it gets to borrow based off of

25:48

that. And you can see that it's actually

25:50

gone ahead and wrote the script.

25:52

If I go to inbox_cleaner

25:54

here and actually look at the skill.md,

25:57

you can see it right over here. If we

25:58

just make this a little bit bigger,

26:01

let's move this here so we can focus on

26:03

this.

26:04

Basically, what we have is a

26:06

step-by-step guide for a future agent on

26:10

how to do the task that I just asked it

26:11

to. You now see that it's now been

26:13

organized in a very particular way.

26:15

For instance, there are these three

26:16

dashes up at the top, three dashes

26:18

underneath the section. There's a name

26:20

key that says inbox cleaner, a

26:23

description key that says clean up key

26:24

mail inbox by reading all unread emails

26:26

using add identifier which ones are

26:27

generally important and mark them the

26:29

rest as read. User cleaning inbox,

26:31

triaging email, or clearing unread

26:32

notifications. Then it also allows it to

26:34

use some tools. Now you may be

26:36

wondering, you know, I think these two

26:37

are pretty self-explanatory, but why is

26:39

it allowing certain tools? Well, Claude

26:42

and all other LLMs basically have access

26:44

to some little pieces of software under

26:46

the hood. Like they can read files, they

26:48

can grep, glob, or bash. And these are

26:51

just various like command line utilities

26:53

that allow it to look through files,

26:55

look for specific sections, and so on

26:57

and so forth. And so, what we've done

26:58

with this skill, okay, it's almost like

27:00

a sub agent. We've basically given it

27:01

the ability to do these sorts of things

27:04

when we invoke or instantiate this.

27:06

Aside from that, we have the title, we

27:08

have the goal, what counts as important,

27:10

what gets marked as red. Notice how it

27:12

basically took everything that I have

27:14

provided it in just a few lines of voice

27:16

transcription, and then turn this into a

27:18

pretty coherent and then consistent SOP.

27:21

Now, going back to the actual building

27:23

thread here, it's actually gone ahead,

27:25

wrote the script, and now it's doing the

27:27

classification. We give this button a

27:29

quick little click, you could see that

27:30

it's now doing it in batches of 10,

27:33

which I didn't even ask it to, okay?

27:35

It's identified which ones it considers

27:37

important, which ones are not important,

27:38

and now it's saying, "Hey, do you want

27:40

me to mark these 97 emails as red now?"

27:43

I don't actually want it to mark the 97

27:44

as red. What I want it to do is I want

27:46

it to show me what they are so that I

27:47

could tell it which ones are right. So,

27:49

I'll say, "No, I'd actually like you to

27:51

show me all of the 97 that you marked as

27:54

red so that I could take a look and tell

27:56

you if there are any exceptions." Now,

27:58

what it's going to do is give me a big

27:59

list of all of the emails, and as you

28:02

can see here, it has correctly

28:03

identified that 79 of the emails I got

28:07

were from a broken make scenario. So,

28:09

that's pretty interesting. Um obviously,

28:11

these are more or less exactly the sorts

28:12

of emails I don't really want to One is

28:14

some normal commission notification from

28:17

referral stack, another is a

28:18

subscription renewal for that voice

28:20

transcription flow. Another's from

28:22

Bright Data, another's from whatever

28:24

company. I got a bunch of cold outreach

28:26

over here, okay? I have sponsorship

28:28

pitches, one word yes reply to lead

28:32

magnet. I guess what I'm trying to say

28:33

is this did a really good job. There

28:35

isn't a single email here that I

28:37

actually really care about. So, I'm just

28:39

going to say, "Nope, mark all as red."

28:41

That's pretty sweet, right? Now, at any

28:43

point in time, I could open up a new

28:45

Claude instance, and we have to go new

28:47

just because of how skills work, okay?

28:50

Then we can go {slash} inbox cleaner,

28:52

and then we can run it. And because we

28:54

are running based off of this SOP, it's

28:56

always going to run in the exact same

28:59

way. It's going to be repeatable,

29:00

consistent, and dependable. Also, if it

29:03

runs into any issue, let's say the

29:05

script doesn't work, let's say there's

29:06

an API rate limit or something like

29:08

that,

29:09

it will identify the problem and then

29:11

automatically go through fix it and then

29:12

rewrite its own skill. In my case, I've

29:14

got a lot of unread emails. So, I think

29:16

what I'll do is I'll say, "Hey, I've got

29:18

a ton of unreads. Could you actually go

29:20

through and fetch a thousand instead of

29:23

a hundred?" And now I have the ability

29:24

also to modify the way that the skill

29:27

works just a little bit, so that instead

29:29

of the base 100, maybe I can do a

29:30

thousand. Maybe I could pass in a flag

29:32

like {dash} A, and that stands for

29:34

amount, and then I can do You can see

29:36

it's actually what's going on under the

29:37

hood. It's passing the the a number

29:39

1,000 to said script. Now that you guys

29:41

see how these skills actually work in

29:43

practice and how to easy it is to build

29:46

one as long as you have the right spec

29:47

sheet, I just want to really quickly

29:49

deconstruct the various parts of this

29:51

file, make sure that you guys understand

29:53

how all of this stuff works and the what

29:55

each of these parts are for.

29:57

Okay, so you guys have probably already

29:59

noticed these three little dots here are

30:01

really different from all the formatting

30:03

elsewhere.

30:04

What this basically is, in at least

30:06

markdown speak, is something called

30:08

front matter.

30:11

Front matter is a highly optimized way

30:13

of basically putting a tiny summary at

30:16

the beginning of any markdown file.

30:18

Remember how there's different fields

30:20

and colors like keys,

30:22

headings, there's sort of more headings.

30:26

I mean, there's a lot of different

30:27

things here. But, you can just think of

30:28

front matter as being the same idea.

30:30

It's just a different like variable or

30:32

type. And the way that you start it is

30:34

with these three uh dashes, and then you

30:36

end it with these three dashes. And so,

30:38

this little summary is is doing you a

30:41

massive service

30:43

by significantly reducing the number of

30:45

tokens that you need to load into your

30:46

context window at any point in time. If

30:48

you think about it, what we could be

30:50

doing every time we load this skill in,

30:52

if I just copy this whole thing and go

30:54

to a free word counting service, is we

30:56

could be adding 373 words, which is

30:59

approximately 500 tokens into context,

31:01

okay?

31:02

But with front matter, what we do is

31:04

instead of storing the entire script

31:06

into context and making it accessible to

31:07

the model, we do is we store a much

31:09

smaller summary, which is closer to like

31:11

60 or 70 tokens, and then we say, "Hey,

31:14

if the user calls inbox cleaner

31:16

specifically, then and only then do I

31:18

want you to load the other you know, 350

31:21

words or so, okay?" And so, what this

31:23

means is in practice, if I were to show

31:26

you guys all of the different skills

31:28

that are currently loaded into context,

31:30

they basically all look like this.

31:32

And so, my prompt at the very beginning,

31:34

just assuming I have these three skills,

31:37

is always basically going to be my

31:39

claw.md up here.

31:41

Underneath, we're going to have our

31:43

skills, so there's going to be one, two,

31:46

three.

31:47

And then underneath it'll be your

31:48

prompt, which is basically whatever the

31:50

heck you want to say. "Hey, I want to do

31:52

XYZ."

31:54

And so, this is more or less the

31:55

structure that every conversation with

31:57

Claude, in my case, but obviously any

31:59

LLM in yours, whether it's gemini.md,

32:02

agents.md, so on and so forth, is going

32:04

to realistically look like. You'll have

32:06

your prompt down here, but before then

32:08

you'll have a bunch of hidden stuff. And

32:09

then what's cool is, you know, if you

32:11

say, "Hey, I want to do

32:13

um follow-ups," what it's going to do is

32:15

it's going to say, "Follow-ups, wait a

32:16

second. I know that we have some

32:18

follow-ups mentioned earlier on under

32:20

the skills section. Okay, great. That

32:22

means this must be a standardized

32:23

skill." And then it'll go and actually

32:25

load the whole follow-up nurture

32:27

directly into its context, which will be

32:29

the rest of this, and then it'll

32:30

basically stick the rest right here, and

32:32

then resubmit the prompt, and now it

32:34

knows everything that it needs to do in

32:35

order to obviously get that right. So,

32:37

the agent would go, "Okay, great. I have

32:40

the skill spec right here. Let me follow

32:42

each step." And then it'll go and, you

32:44

know, start with number one, which is

32:46

load pending leads. Number two, for each

32:49

pending lead, and so on and so on and so

32:51

forth. Now, this actually has a term.

32:53

This is called skill matching. Anytime a

32:56

user types a request like, "Hey, get me

32:58

50 dental leads." It'll automatically

33:00

scan those descriptions or that front

33:03

matter for whatever the most relevant

33:06

is. It says find business leads. Here,

33:08

it says find business leads. Here, it'll

33:10

say, "Oh, this must be the one that they

33:11

want." Then it'll load the full skill.md

33:14

in the context before finally calling

33:16

some scripts, okay? And then giving you

33:18

guys an output. And where you put those

33:20

scripts don't really matter. The basic

33:22

skill definition, I think, just bundles

33:24

it all into one folder. You could put

33:25

the script somewhere else if you want to

33:26

keep them organized. And if you have

33:28

other assets like PDFs or whatever, you

33:29

can build whatever scheme you want to

33:31

keep those files handy. The reason we do

33:33

this, of course, is both for efficiency

33:35

because the less context in a model's

33:37

context window at any point in time, the

33:40

higher the quality of the output, but

33:42

also for costs. Providers like Anthropic

33:44

and so on and so forth actually don't

33:45

want you to spend an arm and a leg,

33:47

believe it or not. Um they want you to

33:49

continue using their software, and in

33:51

order to do so, they need to make it

33:52

like reasonably cost-efficient for you

33:54

and deliver a high ROI to you um at the

33:56

same time. And so, this concept of

33:59

progressive disclosure is now not only

34:01

really being applied to skills, but a

34:02

lot of other things as well. And all

34:04

this is again the pursuit of reduced

34:05

cost, reduced overhead. Okay, let's

34:07

build three more skills with what we

34:09

know now. And just for simplicity and to

34:11

make this as fast as humanly possible,

34:13

both for myself and for you guys, what

34:15

I'm going to do is I'm going to open up

34:17

three separate Claude code little

34:19

plugin, which it's here.

34:21

And in the first, I'm going to switch

34:23

all these to bypass permissions.

34:26

I'll make this a little bit smaller so

34:27

you guys could see.

34:29

And then in the first, I'm going to

34:30

paste in skill number one.

34:33

In the second, I'll paste in the skill

34:34

number two.

34:36

In the third, I'll paste in the skill

34:37

number three.

34:38

What I'm going to say is create skill

34:40

one, create skill two, and create skill

34:42

three. And we're just going to trigger

34:44

all three of these and see how they

34:45

operate.

34:46

So, what skill one is is it's a simple

34:49

way to turn meeting notes to action

34:50

items. We basically just paste in a

34:52

meeting transcript and get a structured

34:54

action item with owners and deadlines

34:56

and so on and so forth. The idea here is

34:58

to show you guys that a skill can be

35:00

really nothing more like an SOP which

35:02

doesn't even include Python scripts or

35:04

anything like that.

35:06

The second one is an invoice data

35:07

extractor, which is basically going to

35:09

be skilled on MD plus some Python

35:11

script. So, we're going to take a PDF

35:12

invoice then return structured JSON in

35:15

the form of a vendor, amount, date, line

35:17

items, and tax. And this is to help you

35:19

guys see how skills can delegate

35:20

deterministic work to code. AKA, we can

35:23

use Python scripts and whatnot like you

35:24

guys have already seen.

35:26

And then the third skill is going to be

35:27

a content repurposer, which is going to

35:29

let us take a transcript and then output

35:30

a tweet thread, a LinkedIn post, and

35:33

then a newsletter draft all in parallel.

35:35

And the idea here is we're going to have

35:36

templates. I'll show you guys some brief

35:38

examples. And I'll also show you guys

35:40

how this works with some instructions.

35:42

And so, before I was even finished

35:43

reading this freaking thing, we're

35:44

almost already done two out of the

35:46

three. Isn't that wild?

35:48

Anyway, the first skill pretty

35:49

straightforward just called meeting

35:50

notes. It just processes meeting notes.

35:53

So, what we can do here if we want is we

35:55

could say, "Hey, I want you to output

35:56

specific elements of the meeting." In

35:58

this case, it has some decisions, open

36:01

questions, and so on and so forth. But I

36:03

also want you to find and identify any

36:05

contact information. So, I'll say, "Hey,

36:07

this is great. I want you to update the

36:09

skill also to extract any contact

36:11

information that's mentioned. I'm

36:13

looking for things like email addresses,

36:15

websites. I'm looking for phone numbers

36:17

and so on and so forth. Anything that

36:19

somebody offhand mentions during the

36:21

call." Sometimes we also specifically

36:23

ask for this information for follow-up

36:25

reasons. So, it would be nice to have it

36:26

in structured sort of way. Over here,

36:28

it's now created both files of the

36:30

invoice data extractor. So, we could see

36:31

there's a skill.md here, which basically

36:34

takes the PDF invoice, returns

36:35

structured JSON with vendor. So, in

36:38

order for me to really appreciate how

36:39

this works, I'm actually going to go and

36:40

grab myself a brief little invoice, uh

36:42

just feed in it in an example, and then

36:44

we'll see how it works. I see a couple

36:45

of services here that have sample

36:47

invoices. This one looks pretty good.

36:49

Why don't I download this?

36:50

I'll say example_invoice.

36:53

What I want to do is I just want to feed

36:54

this in right over here. And I'll say,

36:56

"Great. Use this on

36:57

example_invoice.pdf."

37:01

Then over here, it looks like this is

37:02

now done. And what I'm going to do is

37:03

I'm going to go find some of my own

37:04

content and just feed that in just as an

37:06

example. So, we'll go on my YouTube

37:08

channel and I'll find something that is

37:10

probably not 4 hours because that would

37:12

take a lot of tokens for no purpose.

37:14

This 10-minute one looks pretty good. I

37:16

said,

37:16

"Let's get my fat ugly head to shut the

37:18

heck up."

37:19

I'll scroll down here to where it says

37:21

show transcript. And then right now,

37:23

just cuz it's an example, I'm just going

37:24

to copy all the stuff in manually, but

37:26

obviously you guys could do whatever you

37:27

want with this.

37:28

Going back here, I'll then paste this

37:30

in.

37:31

And what I want to do is I basically

37:32

just want to see whether or not it can

37:34

do all of those three things. I'm also

37:36

going to take a quick peek here at the

37:37

script. And um this is what I wanted to

37:40

happen actually, which is nice. It ran

37:42

into an issue with one of the summary

37:44

rows and the subtotal. So, what it's

37:45

doing now is it's actually going to fix

37:47

the script's filtering logic so that it

37:49

doesn't catch the subtotal or the credit

37:51

terms or something like that. Okay,

37:53

cool. On the right-hand side, it's

37:54

extracted this transcript. Looks pretty

37:56

good. And now what it's going to do is

37:57

spawn all three formats in parallel,

38:00

which is its way of saying it's going to

38:01

rewrite my uh main transcript and turn

38:03

this into like blog posts and Twitter

38:05

threads, whatever the heck it's going to

38:06

do. While all of this is happening, this

38:08

is me pictured. I'm just manifesting all

38:11

of the skills. I actually have to do too

38:13

much. I just kind of close my eyes and

38:15

wait, and then they appear. Taking a

38:17

look at this tweet thread over here.

38:19

Let's just make this look a little bit

38:20

prettier.

38:21

We now have a bunch of tweets that are

38:23

divided, and this is automatic, which is

38:25

pretty cool. A 16-year-old posted a

38:27

prompt on Twitter. Former professional

38:28

web designer copy-pasted in a Gemini.

38:30

The AI produced a better site than he

38:31

could in 5 hours in minutes. Design is

38:34

commoditized. Should you guys have seen

38:35

these sorts of threads all over the

38:37

internet? Let me tell you why. It's

38:39

because people have built very simple

38:41

repurposing pipelines like this. And

38:43

although that one just took me 5

38:44

seconds, the content's reasonable. Not

38:46

going to say it's going to win any

38:47

awards. It's pretty LLM-y, but hopefully

38:49

you guys could see with at least a few

38:52

neurons between your two ears, you guys

38:54

could repurpose, change the tone of

38:55

voice, and so on and so forth, and make

38:57

it something actually pretty cool.

38:58

Likewise, we also have LinkedIn posts,

39:00

and then we even have a newsletter draft

39:02

for me. So, that's pretty sweet. You can

39:04

see that its design decision was to do

39:06

this via Sonnet sub-agents. You guys can

39:08

modify this SOP at any point with

39:10

literally just a line. Finally, in the

39:12

middle here, skill two is all good to

39:13

go. Great job. It's gone through and

39:15

it's actually updated the main skill as

39:17

well, which is quite neat. If you guys

39:19

were paying attention, you would have

39:20

noted that every time that we add a new

39:22

skill, or change skills, or whatever,

39:24

there's a top left folder over here

39:27

that's {dot} Claude {slash} skills that

39:30

changes. And this is essentially the

39:32

format and file directory structure of a

39:35

skill. So, it's worth us pointing it

39:36

out. Now, in case you guys have never

39:38

seen this convention in the top

39:39

left-most corner, you see how there's a

39:41

little dot in front of a Claude folder?

39:43

Well, that's basically just the kind of

39:45

universal file explorer convention for

39:47

hidden. Now, if I open up this exact

39:49

folder, the skills example folder, in my

39:52

macOS native file explorer,

39:55

you notice that it looks pretty

39:56

different from what we're seeing over

39:58

here.

39:59

Notice how on the left-hand side we have

40:00

{dot} Claude {dot} tmp, then we have one

40:02

second copy config data. And notice over

40:04

here that the list actually starts at

40:05

one second copy, then goes Claude.md,

40:08

then it goes config, and then it goes

40:09

data. So, I mean, aside from the fact

40:11

that this is organized a little bit

40:11

differently, generally speaking, we

40:13

always have folders organized first in

40:15

the file explorer here. So, if we kind

40:16

of match that up one for one, you'll

40:18

notice that the only things that are

40:19

missing are basically the files and the

40:21

folders with little periods in front of

40:23

them.

40:24

So, the first thing to note is like most

40:26

people just have no idea where this

40:26

thing is because when they go to the

40:27

file explorer, like it's always hidden.

40:29

Well, in macOS it's pretty easy to

40:30

reveal. You just go shift command uh

40:33

dot period basically and then you can

40:35

show all hidden folders. They'll be

40:37

present. It's just they'll be a little

40:38

bit um more translucent. And then we can

40:41

actually open it up and then go through

40:42

all the skills.

40:43

Okay, so that's the very first thing to

40:45

know. On a Windows, which you guys may

40:46

be using, it's it'll be a different

40:47

hotkey. Just Google it. There's uh

40:49

plenty of information on there about

40:50

hidden files. I think you can also just

40:51

right click and go like show hidden

40:52

files or something cuz I used to have a

40:53

PC and that was pretty straightforward.

40:55

But uh yeah, essentially inside of every

40:57

main workspace in any sort of IDE, if

41:00

you do have skills, they're probably

41:02

going to be hidden from you, which is

41:03

kind of difficult and and intimidating

41:05

to to kind of understand.

41:06

Okay, so then after that, the way that

41:08

it's organized, which is not super

41:10

plainly clear here, so to make it a

41:12

little bit clearer for you guys, is you

41:13

have the dot Claude folder, right?

41:15

And then underneath the dot Claude

41:17

folder, you have the skills folder.

41:20

Then underneath the skills folder, you

41:21

actually have the specific skill folder

41:23

that you want. So, let's just go, you

41:25

know, inbox cleaner.

41:28

That's another folder and then inside of

41:30

that folder, you actually have the skill

41:32

file itself. So, then you have the

41:34

skill.md. So, notice how nested this is.

41:37

I mean, it's a massive pain in the butt.

41:38

I don't know why they do it like this,

41:39

but um they make it pretty difficult for

41:41

most beginners to understand. Um and

41:42

they do so in this sort of like

41:43

hierarchy that begins again with dot

41:45

Claude, then go skills, then go you

41:47

know, the specific name of the skill and

41:48

then the skill.md itself. And then over

41:50

here, okay, and this is sort of

41:52

optional, but this is how Anthropic

41:53

typically does it. Here, you can put

41:55

your other stuff.

41:57

What is your other stuff? Well, your

41:59

other stuff is going to be things like

42:00

your scripts. So, hypothetically, if you

42:02

had like scripts that helped you do the

42:03

invoice cleaner inbox cleaner or

42:05

whatever, maybe an inbox uh dash

42:08

cleaner.py,

42:09

you know, you'd probably put it

42:10

somewhere in here. I personally like

42:12

doing it in a different folder called

42:13

execution. Sue me. I just think it makes

42:15

more sense, a little bit cleaner. Uh

42:17

likewise, if you have, I don't know,

42:18

like your Gmail off tokens or something,

42:21

you know, you might include them over

42:22

here. If you have, I don't know, some

42:24

other file like example.txt,

42:27

um you'd include it over here. And so

42:29

this is just like the base way that all

42:30

skills are organized. And yeah, I think

42:32

it's just unfortunate that it's usually

42:33

a hidden folder, which is kind of

42:34

intimidating. I should note that the

42:35

skills live right alongside a bunch of

42:37

other hidden folders like agents and

42:38

stuff like that. Um I can't really talk

42:40

about this now, but if you want more

42:41

contacts on that, just check out my

42:42

full-length Cloud Code course. I got a

42:43

ton of juice for you in there. Okay,

42:45

last thing I really want to do is just

42:46

talk a little bit about what skills are

42:49

actually worth making.

42:51

You know, I do a lot of business

42:52

consulting now. Uh somebody that started

42:55

in door-to-door sales, I saw the

42:57

importance of focusing on the levers

42:59

that actually increased revenue first

43:01

and foremost above all else. And so for

43:03

me, it was always door-to-door. But then

43:05

transitioning into marketing and then

43:07

broader through things like uh content

43:10

creation, articles, and now videos. I

43:12

think a lot of people are very

43:14

misaligned on what like a high revenue

43:17

SOP even looks like to begin with. And

43:19

the reality is with agents nowadays, you

43:21

can do anything. But that doesn't mean

43:24

that you should do everything.

43:26

These things are so damn good. They can,

43:29

of course, design whatever crazy

43:31

back-end fulfillment pipeline you want.

43:33

But I find most of the demos on the

43:35

internet that talk about stuff like that

43:37

are really miss the mark because we've

43:39

been able to design these pipelines

43:41

forever. And most people that do these

43:43

sorts of things still don't make any

43:45

money.

43:46

The difference between people that use

43:48

new, upcoming, and trend-breaking

43:50

technology to make money and actually

43:52

have big, you know, success outcomes

43:54

versus people that

43:56

play shiny object syndrome all day and

43:58

just collect a bunch of Pokémon cards

44:01

are the former group focuses primarily

44:03

on the front end of their business. So

44:04

they They on the acquisition of

44:06

opportunities. They focus on the

44:07

generation of leads. They focus on

44:10

mechanisms that improve the quality of

44:12

the sales experience for their leads.

44:15

They focus on selling closing mechanisms

44:18

and so on and so forth.

44:19

And then the latter people just over

44:21

complexify the hell out of everything

44:22

and then make every excuse under the sun

44:24

not to focus on sales and marketing. So,

44:26

this is all just like a pretty

44:28

meandering and long way of saying, if

44:29

you're going to design skills, I highly

44:31

recommend you focus the design of those

44:33

skills primarily on front-end tasks.

44:35

Like most of the people that are going

44:36

to be watching this video, you know,

44:38

they're probably going to have some sort

44:39

of side hustle going on or they're going

44:41

to be looking to get into that realm.

44:43

The simplest and easiest way that you

44:45

can move the needle in your own business

44:46

is if you're going to design skills and

44:48

stuff like that, spend your time

44:50

designing them on things that help get

44:51

you sales, on things that help, you

44:53

know, you do your marketing faster and

44:55

better. And then don't just have them

44:57

sit around in your folder. Actually use

44:59

them. You know, when I was growing my

45:01

business, I was doing somewhere between

45:03

50 to 100 cold calls every single day.

45:05

When I was going door-to-door, it was

45:06

something like 80 knocks on physical

45:08

doors per day. I wish I had a hundredth

45:11

of the technology we have today. I'm not

45:13

even that old

45:14

to go back and then automate that

45:15

process for me. I don't. But it blows my

45:18

mind how many people do and then they

45:20

choose not to use it on things that

45:22

actually make money like those laborious

45:24

door-to-door sessions or or cold calls

45:26

or whatever. Okay, so ultimately things

45:29

that I have seen work really, really

45:30

well.

45:31

Content repurposing pipelines. These

45:33

genuinely can significantly improve your

45:35

reach assuming you're growing a brand.

45:37

That's for inbound. Lead generation

45:39

systems. Things that do stuff like

45:41

scrape leads for you. Those are really

45:42

big. Skills that use Chrome DevTools MCP

45:45

to post on forums automatically for you.

45:48

To, you know, do product research

45:50

quickly and then tell you which threads

45:51

are saying bad things about your

45:53

product. These things are valuable.

45:55

Skills that, you know, quickly go

45:56

through a bunch of books and identify

45:59

which things are business expenses and

46:00

can be written off versus things that

46:02

aren't. These sorts of skills are

46:03

valuable. The skills that are not super

46:05

valuable are like skills that help you

46:08

build other skills or skills that

46:10

invent some new design framework that

46:13

assists you in the building of AGI,

46:15

right? These things are not ultimately

46:18

the stuff that I want you to take away

46:20

from this video. I want you to focus on

46:21

real practical use cases that actually

46:23

move the needle for your own business or

46:25

the businesses that you're working with.

46:27

Cuz at the end of the day, that's the

46:28

stuff that's going to make the economy

46:29

more efficient. That's the stuff that's

46:30

going to make you more money as you know

46:32

AI swallows up more and more knowledge

46:34

work. All right? So hopefully I didn't

46:36

bore anybody to death. Guys, I'd like to

46:39

make a big ask. If you guys like my

46:40

content, please subscribe. I realized

46:42

the other day that 69 point something

46:45

percent of all of the people that

46:46

regularly watch my content are not

46:47

subscribed. That means about two out of

46:49

the three people that I'm talking to

46:51

right now for whatever reason haven't.

46:53

If you like the sort of content that I

46:54

make,

46:55

you know, the algorithm really does like

46:57

it if you subscribe and then it pushes

46:59

my YouTube channel to a bunch of new

47:00

audiences. But if I don't get enough

47:02

subscribers, then none of that stuff

47:03

happens and then most of my videos bomb.

47:05

So I really appreciate anybody that has

47:08

taken the time and energy to subscribe

47:10

and I'm not going to do a big cry

47:11

session here. Although as a newbie

47:13

YouTuber, I always wondered why

47:14

everybody was pitching me on subscribe

47:15

this, subscribe that. And now I think I

47:17

get it. Most people just never do.

47:19

But yeah, I would really appreciate it.

47:21

Aside from that, if you guys like this

47:22

sort of thing, just leave a comment down

47:24

below with any sort of question or

47:25

recommendation as to future content and

47:27

I will happily take that into

47:29

consideration. I have skills that now

47:31

scan my YouTube comments and then use

47:32

that to help me ideate new videos to

47:34

make and so on and so forth. So yeah, a

47:36

lot of cool stuff in the works for you

47:38

guys, but I definitely love to know what

47:40

direction to take it. Thank you very

47:41

much for watching. Have a lovely rest of

47:43

the day.

Interactive Summary

The video offers a comprehensive guide on building and implementing AI agent 'skills'—specialized, automated routines that outperform simple personal assistants by focusing on revenue-generating business tasks. The presenter, who manages a highly profitable business using these agents, demonstrates practical use cases including automated lead follow-ups, thumbnail generation, LinkedIn lead scraping, cold email campaign management, website building, and miscellaneous personal automation like desk bookings and online shopping. He explains that skills are effectively evolution of standard operating procedures (SOPs) represented in markdown files and are designed to be 'self-healing' by agents. Finally, the video provides a walkthrough of creating these skills using frameworks like Claude Code, emphasizing that viewers should prioritize automating front-end business activities—such as sales and marketing—to maximize their return on investment.

Suggested questions

4 ready-made prompts