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·YouTLDR

7 Ways to Use Claude So Well It Feels Illegal

19:312,959 words · ~15 min readEnglishTranscribed May 25, 2026
AI Summary

Claude should not be treated as a basic copy-paste chatbot, but as a team of five distinct agents: Think, Remember (Projects), Execute (Co-work/MCP), Build (Code), and Browse (Chrome). Applying the PRIME framework (Purpose, Research, Interview, Mechanics, Examples) transforms Claude into a high-leverage strategic partner that levels the playing field for non-technical creators and solo founders.

As generative AI shifts from simple text generation to agentic, multi-tool workflows, understanding how to construct structured contexts, use local sandboxed execution, and interface with external tools determines who achieves massive scale and who gets left behind.

Section summaries

0:00-1:00

Introduction & The Five-Agent Spectrum

watch

Establishes the foundational shift from basic chat to a multi-agent workspace.

1:00-4:00

Agent 1: Think (How to prompt better & build while flying)

optional

Covers prompt engineering tips which may be redundant for intermediate to advanced AI users, but has a solid parallel learning strategy.

4:00-7:00

Agent 2: Remember (Claude Projects for Career Pivot Setup)

watch

Excellent practical demonstration of structured system prompts and leveraging project contexts over global account settings.

7:00-12:00

Agent 3: Execute (Claude Co-work, MCP, and Sandboxing)

watch

Crucial technical discussion on the Model Context Protocol, connecting to external workflows, and local directory security.

12:00-14:00

Agents 4 & 5: Build (Claude Code) and Browse (Claude Chrome)

watch

Highlights non-technical software generation and real-time document extraction directly from the active browser window.

14:00-18:00

The PRIME Framework & Closing

watch

Explains a highly actionable prompt blueprint (PRIME) that integrates interview prompts and clear mechanics.

Key points

  • The Five-Agent Taxonomy of Claude — To maximize Claude, you must segment your interactions into five specialized modules: Claude Chat (collaborative thinking), Claude Projects (long-term memory and customized contexts), Claude Co-work (desktop-level execution on local files), Claude Code (terminal-based rapid prototyping), and Claude Chrome (real-time browsing context).
  • Shifting from Account-Level Customization to Project-Level Contexts — Setting global, account-wide instructions limits Claude's utility because varied tasks require conflicting cognitive frameworks. Instead, isolate distinct domains—like career transitions, financial modeling, or personal trip planning—into independent Claude Projects populated with relevant background documents, tone constraints, and tailored system prompts.
  • The Model Context Protocol (MCP) as an Agentic Bridge — MCP serves as a standard open protocol that gives Claude the keys to interoperate with external tools, APIs, and media generation engines like Hicksfield. Instead of just outputting text, Claude uses MCP to coordinate actions across applications and drop finished, high-fidelity files directly into local directories.
  • The PRIME Prompting Framework — High-performing outputs require structuring prompts via PRIME: Purpose (establishing explicit goals), Research (grounding outputs with validated external data or user-supplied constraints), Interview (prompting Claude to ask clarifying multi-choice questions before executing), Mechanics (declaring format, style, and density), and Examples (providing high-quality few-shot templates).
Give Claude to two people. One will use it to build a better email. The other will use it to help build a hundred million dollar company. Same tool, different users. Srinivas Rao
If you are patient and curious, you can literally build your engine while you're flying the plane. Srinivas Rao

AI-generated from the transcript. May contain errors.

0:00

Give Clot to two people. One will use it

0:03

to build a better email. The other will

0:06

use it to help build a hund00 million

0:08

company. Same tool, different users. And

0:12

that gap between people who use AI and

0:16

people who wield it is about to reshape

0:20

careers and companies and families and

0:23

lives over the next decade. If you're

0:27

new here, I've been a CEO, board member,

0:30

investor in technology companies worth

0:33

billions. And today I want to share with

0:35

you how to use Claude better than 99% of

0:38

people from beginner to advanced. And

0:41

it's way easier than you think. Claude

0:44

is not just one app. It's a whole stack

0:46

of tools built for a very different kind

0:49

of work environment for businesses.

0:52

There's chat for thinking, clot co-work

0:55

to get work done, clot code to build

0:58

things, clot chrome to browse with a

1:01

brain, clot skills to make it all

1:03

repeatable, and lots of tools. Once you

1:06

understand how this team of agents work

1:09

together, your output can change

1:11

dramatically. The best way to visualize

1:13

it is this five activities. Think,

1:16

remember, execute, build, and browse.

1:19

Let's go through each one of them. First

1:21

is think you go to claw chat and this is

1:24

what most of us do when we think about

1:26

chat bots. We input a prompt, we get a

1:28

response, you bring a messy problem, a

1:31

fuzzy idea or a rough draft and work

1:35

through it. But many of us just use AI

1:38

to do all the work so they can copy and

1:41

paste. We've all seen those LinkedIn

1:43

posts. So, if you go to claw chat and

1:46

type, write me a LinkedIn post about

1:50

leadership, you'll get a very polished

1:52

paragraph that says nothing. And we've

1:55

talked about how to prompt better with

1:57

things like aim, before actor, input,

2:00

mission. Try this prompt instead. You

2:03

are a business school professor. I am

2:06

trying to explain why some leaders sound

2:10

credible and others don't. I'm attaching

2:12

my notion page with a rough idea that

2:16

talks about leadership and authenticity,

2:19

leadership and humility. Your job is to

2:22

push back on what's weak and sharpen

2:25

what's real. Find me research that helps

2:27

me create a strong insight and then we

2:31

can write a LinkedIn post. You make

2:34

Claude your thinking partner. Now, of

2:37

course, like all AI, it will not do what

2:40

you tell it to do. Not the first time

2:42

around, at least. And sometimes it's

2:44

going to be super frustrating because

2:46

you'll give this detailed prompt and

2:49

just crap will come back. So, there are

2:51

three things that you can do that can

2:54

become your power moves when that

2:55

happens. First, give it rich context as

2:59

much as you can. Connect the chatbot to

3:01

your Google Drive, your email, your

3:03

calendar, your notion app, anything else

3:06

you can. That way you can attach files

3:09

to that chat session. It will read it.

3:11

It'll get context from it. Second,

3:14

ground your insights with research. You

3:16

can ask claw to go out on the web and do

3:19

deep research. It has already learned

3:21

the entire internet during its training.

3:24

So why not use it? But when you get the

3:26

research back, always ask one more time.

3:29

Is this verified? And third, use AI to

3:33

build your AI skill in real time. If

3:36

you're patient and curious, you can

3:39

literally build your engine while you're

3:41

flying the plane. For instance, let's

3:43

say you have no background in corporate

3:45

finance and you're building a financial

3:47

model. You get stuck on how to use a

3:50

specific spreadsheet feature or even a

3:53

financial concept like IRRa or free cash

3:57

flow. No problem. Just start another

4:00

chat in another tab and ask away. So you

4:03

can learn and do. Do and learn. The

4:07

cycle just continues. Now let's go meet

4:09

our second member of your team. This one

4:12

helps you remember and it's called

4:15

clawed projects. We all know when we're

4:18

creating something new or solving a

4:21

complicated problem, the work doesn't

4:23

end in one session or even in one chat.

4:28

And that's why all three AI platforms

4:30

nowadays have gotten better at

4:32

maintaining memory across different chat

4:35

sessions. Claude remembers your world

4:38

through projects. A project is where you

4:41

give the chatbot your files, your

4:44

instructions, your tone, your ongoing

4:47

work. You're not starting from zero

4:49

every time you open it. And of course, I

4:52

would be careful about sharing

4:54

confidential documents from your office.

4:57

But let's say you're actively or

4:59

passively looking for a career change or

5:02

a new job opportunity. You can create a

5:05

project. You drop in your resume, your

5:08

LinkedIn profile, the two or three job

5:10

descriptions that you like or the

5:12

company you're targeting, your writing

5:14

samples, your professional bio, the

5:17

other résumés that you like, anything

5:19

you can think of. And you can customize

5:21

this project with exactly what you need.

5:24

So you can add something like you're the

5:27

world's most badass recruiter and resume

5:31

writer who has placed candidates in top

5:34

companies in my industry. I am a brand

5:37

marketer with 5 years of experience at a

5:39

large agency called WPP. Your job is to

5:44

help me create a great story for my next

5:47

adventure, for my next company, and make

5:49

me desirable for the next role. I write

5:52

in a direct confident tone. I don't like

5:55

corporate fillers. I hate buzzwords.

5:58

When I ask you to tailor something, mash

6:00

the job descriptions language without

6:03

losing my voice. When I ask you to do

6:05

deep research, make sure you deliver

6:08

only the relevant and verify data. Don't

6:12

make it up. And when I ask you for

6:14

feedback, be honest. Tell me what's weak

6:17

and what I need to work on. Be my

6:20

constructive partner. and strengthen

6:23

those areas. This is one way to provide

6:26

instructions, but you can see that there

6:28

are 100 ways to do it. And that's the

6:29

kind of instruction that makes any

6:31

project your own. Not a prompt that

6:34

you're copying from some YouTuber, but a

6:38

brief that you write for someone you

6:41

actually know very well, yourself.

6:44

From that point on, every time you come

6:46

back, Claude already knows what you want

6:49

and who you are. You can ask it to

6:52

tailor a cover letter, craft a specific

6:54

bullet of your resume for a specific

6:56

role. A project turns Claude from a

7:00

one-off conversation into an ongoing

7:03

relationship between you and your AI.

7:06

This is also why I don't customize

7:10

Claude at the account level. I like

7:13

customizing it at the project level

7:15

because that way I can give it specific

7:17

context because using AI to plan your

7:20

vacation is very different from using it

7:24

to plan your retirement. Now let's go to

7:26

execute and for that we have our third

7:29

team member Claude Co-work. Chat is

7:32

where the work begins. Co-work is where

7:35

it gets done. You start in a prompt

7:38

window but finish it on your desktop.

7:41

Co-work is a desktop application for Mac

7:44

or Windows. Unfortunately, it's

7:46

available only on Claude's paid plans

7:49

right now. But with Co-work, instead of

7:52

asking a question, you give it a task.

7:55

When do you use co-work versus chat?

7:57

Well, you use co-work when you have a

7:59

lot of assets already on your computer's

8:01

hard drive, when the task needs multiple

8:04

steps, and when you need that output to

8:06

be on your local drive as a local file.

8:09

So, for example, you can tell co-work to

8:11

do the following. Take all of these

8:14

customer interview transcripts from this

8:16

folder, these spreadsheets of accounts

8:18

and notes from last week's product

8:21

meeting. Find top three reasons on why

8:25

the customers are churning, why are they

8:27

leaving? Provide all the supporting

8:29

data. Create a very clean slide deck

8:31

that I can use tomorrow. Put that slide

8:34

deck in this folder. And here's what

8:36

makes co-work even more interesting. It

8:39

can reach out to other AI tools through

8:42

a connector called MCP, the model

8:45

context protocol. Think of MCP as giving

8:49

Claude a set of keys to other AI tools.

8:53

It can knock on their door, unlock the

8:55

capabilities of those tools, act with

8:58

them, act through them to give you

9:00

results. Let me show you what that means

9:02

in a real example. Imagine you run a

9:05

business selling handcrafted candles.

9:08

You have a small business. You have a

9:10

terrific product, but you're

9:12

bootstrapping your business, right? And

9:14

you don't have a huge marketing budget.

9:16

In the old world, that would mean that

9:18

you couldn't create any ads that looked

9:21

super polished or professional. But now

9:24

look at what you can do when you can

9:26

plug Claude into a creative AI tool

9:29

called Hicksfield. They are the sponsor

9:31

for this video. Now, Hicksfield is used

9:34

by 18 million creators backed by tier 1

9:36

VCs like Excel and Menlo Ventures, and

9:40

they've already crossed the billion

9:41

dollar valuation. And they were the

9:43

first creative platform to ship an

9:46

official MCP connector for Claude.

9:49

Here's how you connect it. You have to

9:51

do it once and that's it. Go to

9:53

settings, connectors, plus button, paste

9:56

the Hicksfield URL, and you're done.

9:59

That's it. Now you can go into co-work

10:01

and you tell it to do whatever you need

10:03

to sell more products. For instance, you

10:06

could say, "Generate 20 beautiful ad

10:09

creatives for my new lavender candle

10:12

line. Three ideas for Instagram, three

10:15

editorial close-ups for the website, and

10:17

a vertical video for the launch. Write a

10:20

tagline for each and that's it. It just

10:23

runs. Claude Co-works the prompt and

10:27

passes it on to Hicksfield." Hicksfield

10:29

generates the images and the video and

10:32

the entire set of files land in your

10:35

local folder without you needing to hire

10:38

a creative agency and pay them thousands

10:40

of dollars. That would have taken you 3

10:43

weeks of a professional shoot, a

10:45

photographer, a stylist, and weeks of

10:48

post-prouction and of course thousands

10:50

of dollars. But now you can do it in a

10:52

single session with Claude and

10:55

Hicksfield. This is how AI is leveling

10:58

the playing field. A solo founder with

11:01

the right set of tools today can now

11:04

produce the kind of creative output that

11:06

used to require a large team and a large

11:09

budget. There is a link in the

11:10

description below. They have a free

11:12

tier. Take it for a spin. Try it. And

11:16

you could build something very cool and

11:17

interesting this weekend. Two things to

11:20

keep in mind. First, the output will be

11:23

a starting point. You'll still have to

11:25

go through each and every slide and make

11:28

sure it's good, but a lot of heavy

11:30

lifting is done by Claude Co-work

11:33

already. Second, give explicit

11:35

permission for Claude Co-work to access

11:38

only specific directory and specific

11:41

files. Claude is very conscious about

11:43

security, but please be very mindful

11:46

about what you give access to. And I

11:48

usually create a subfolder and move all

11:51

the files and data into that folder. And

11:54

that's all Claude has access to. It's

11:56

called sandboxing. So the rest of your

11:58

hard drive remains secure. Claude can't

12:01

get to it. Fourth is build. And this is

12:04

where Claude code comes into play. This

12:07

is the part that makes a lot of us

12:10

nervous. It made me nervous. The moment

12:13

we hear code, we're like, h I don't

12:17

know. We assume that all that stuff is

12:20

only for engineers. But that assumption

12:23

is one of the biggest missed

12:25

opportunities in AI right now. If you

12:28

can type in English, you don't need a

12:30

computer science background to code and

12:33

build something cool and useful. Let's

12:36

say you have a uh consulting business or

12:39

a side hustle. Simple example. Just go

12:42

to claude code and prompt. I want a

12:45

dashboard where I can drop in my sales

12:48

pipeline and meeting notes and instantly

12:51

see which deals are at risk, what's

12:54

stuck, and what my next move should be.

12:58

That's all you need. You don't need to

13:01

think like an engineer to start using

13:03

clot code. You just need to be clear

13:06

about the problem you want to solve and

13:08

the thing you want to build. And of

13:11

course, you have to have the right data

13:14

so that dashboard you build is useful.

13:17

And finally, the fifth team member is

13:20

for browsing the internet. And for that,

13:23

you can use Claude Chrome. And you're

13:25

going to go, "Wait, what?" Don't worry.

13:28

Claude has this little extension that

13:30

you can install in your Chrome browser.

13:33

Google already has something like ask

13:35

Gemini button baked into the browser now

13:37

but now you can let cloud see what

13:39

you're looking at as well help you

13:41

process it and act inside your workflow

13:44

in real time and I think about this a

13:47

lot nowadays because most of my work

13:51

happens inside the browser right my

13:53

files are on Google Drive or Microsoft

13:56

one drive my emails my scheduling my

13:59

team meetings my research filling out

14:02

forms ers, making purchases, planning

14:04

business trips, all of it is taking

14:06

place using the browser. And now Claude

14:09

is right there with you for all of it.

14:12

You're on a job listing site, Claude can

14:15

read it and help you tailor your

14:16

outreach. You're reading a 40page

14:19

industry report. Claude can pull the

14:21

three insights that matter the most in

14:23

real time. So that is your team. There

14:26

are other team members, but these five

14:29

are the most interesting and useful.

14:31

This is your stack. But even with the

14:35

full team working with you, one gap can

14:38

make all the difference between the

14:40

average and the elite mode. That's where

14:44

we go next. Any AI's results depend on

14:48

you. Even with the full team of agents

14:50

working for you, Claude is only as good

14:53

as the input you give it. But the super

14:56

users who get exceptional output from

14:58

Claude, they direct Claude the way they

15:02

would direct a smart person they've just

15:04

hired. And the easiest way to do that is

15:06

a framework I call prime. P is purpose.

15:10

When you prompt Claude, give it a

15:12

precise goal. Tell it what you need it

15:15

to do. Like, help me turn this messy

15:18

proposal into a fivepart organized

15:21

document that looks like a sharp client

15:24

memo. R is research. We talked about it

15:26

before. In many cases, you may need

15:29

external research to ground the

15:32

response. Ask it to go out and fetch it

15:34

for you. Ask it to verify it. And

15:37

sometimes the raw material may come from

15:39

you, your notes, transcripts, files,

15:42

examples, background constraints,

15:45

anything that Claude needs so that it

15:48

can stop hallucinating or guessing. I is

15:51

for interview. This is the hidden gem. I

15:54

really like how Claude does it. In a lot

15:57

of cases, you'll see that it will start

15:59

asking you multiplechoice questions and

16:03

you pick the right choice and based on

16:05

what you clicked, it refineses its

16:08

approach to a specific way of responding

16:10

to you. M is for mechanics. Here you

16:13

tell Claude how the output should look

16:17

like. Do you want bullets or a

16:20

paragraph? Do you want a document or a

16:23

table? Do you want it concise or you

16:25

want detail, strategic or

16:27

conversational? Anything you choose. And

16:30

finally, E is for examples. Show Claude

16:33

what good looks like. A format you liked

16:36

or a tone reference or an outline that

16:40

worked before. Examples are one of the

16:42

fastest ways to quality. Let's go

16:45

through an example. You have an

16:47

important presentation coming up

16:48

tomorrow. Run it through prime purpose.

16:52

What is this meeting really for? Do you

16:55

need an approval alignment? Are you

16:57

asking for resources? What is the

17:00

outcome? You really want research. Give

17:02

Claude the context. What's the audience

17:05

like? The risks, the data, what your

17:07

team cares about, external resources,

17:10

internal docs, anything you can give.

17:12

Interview. So tell Claude, interview me

17:15

before you respond. Now it will ask you

17:18

questions that sharpen its own scope and

17:21

your thinking mechanics. Now you know

17:23

the output of that deliverable. You want

17:26

a 10 slide deck and talking points. And

17:28

finally examples. Give it a past deck

17:31

that you liked or style you admire. So

17:34

that is prime. Once you start doing that

17:38

AI stops being a tool and starts

17:40

becoming your edge. And by the way, if

17:43

you want the frameworks like these in

17:45

your inbox, subscribe to my newsletter.

17:48

The link is below somewhere. I mean,

17:50

it's free. The real edge is the human

17:53

using it. Everyone watching this feels

17:56

like someone else is getting ahead

18:00

faster, that they are smarter or they're

18:03

richer or they have better resources. I

18:06

know I feel like that sometimes. That is

18:09

the default condition of ambition. The

18:12

question is not whether you are

18:14

outgunned. The question is how you

18:17

outshine when you are. You have been

18:19

carrying labels for years. I am not

18:22

technical.

18:24

I'm not a designer. I don't have an MBA.

18:28

But those are just labels. For $20 a

18:32

month, you can hire something that is

18:35

already better than most MBAs and PhDs.

18:38

No, you can think more sharply with it.

18:41

You can design better. You can code. You

18:43

can build. But do you have the curiosity

18:46

to keep learning, the the tenacity to

18:50

get through that machine friction, the

18:53

patience to build real capabilities,

18:57

or will you slowly replace real effort

19:00

with convenience and lose your instinct

19:04

to wonder? AI will give you a lot of

19:08

things, but what AI can't give you is

19:12

that innate curiosity that made you

19:15

press play on this video.

19:19

And you already have it. As one of my

19:22

mentors used to say, you were the one

19:25

you've been waiting for.

19:27

Thank you and I love

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