Ross, Mike, welcome back to the pod. By

the end of this episode, what are people

going to learn?

>> I hope I'm going to share some wisdom on

how you can use the agents better.

There's a lot of information going on

right now. I disagree with most of it,

and that's what we're going to talk

about. So, at the end, whether you're

building something, [music] using an

agent for some sort of work, you have

the best outcome possible.

>> And is this going [music] to be a

technical dive or, you know,

non-technical person can

>> Anyone can watch this. There's going to

be a lot of diagrams. That's all.

>> [laughter]

>> You're going to make it clear to

understand the concepts, right?

>> Easy.

>> Okay.

>> Basics.

>> Let's go.

>> So,

>> [music]

>> the first thing that I want to announce,

previous episodes, we probably disagree

with this point, but now

what's true is the models are good.

The models are exceptionally good. Opus

4.6 is amazing. GPT 5.4 is amazing. I

know there's like two sets of camp

where, especially when it comes to

programming, people are like, "Oh, Opus

is the better UI designer. GPT 5.4 is

the better back end." Generally

speaking, we've reached a point We're

not at AGI yet. Well, we reached a point

where the models are good.

But, context still matters, and you have

the power to steer the models in a

direction where you can get quality or

you can get slop. And that's what I

really want to talk about. But, before

we get into all that, and feel free to

cut me off cuz this topic excites me. Um

we need to learn how context works. And

context is the model assembling

information that it needs to execute an

action. And the way the context is

assembled, let's say in a coding agent,

but really in any sort of agent, is

there's this general system prompt,

usually by the model provider. So, for

example, Claude code leaked recently,

and one of the cool things that, um

especially as a developer, I got to do

is I got to read the system prompt. So,

they have this general system prompt

that guides the model on how to act,

what to do, what not to do. The system

prompt is very important. And then you

have a lot of people have agent.md files

or cloud.md files. Now, I'm just going

to say off rip,

95% of people don't need this.

The reason being is, again, you have to

assume that the models are already good,

right? Now, imagine I told you, Greg,

every time we're about to shoot a

podcast, Greg, you need a microphone.

You know you need a microphone, right?

You've done this plenty of times, right?

So, if I'm building, like, let's say a

website with, uh, cloud code, and I'm

telling cloud code, "This code base uses

React." I don't need to, because it has

the code base in context. It can check

the code, right? So, there is this

disparity where a lot of people are

putting a lot of onus on the harness and

the context building, and I'm low-key

starting to strip things off. Like, I'm

going super, super minimal, because,

again, not to sound like a Anthropic or

OpenAI shill. Unfortunately, I have not

been acquired. None of them are paying

me.

Um, but the models are really, really

good.

>> Wait, so 95% of the time I don't even

need a bot bother with an agent.md file?

>> You don't. Like, it unless this is some

sort of proprietary information.

>> Yeah, what is the 5% of of time I should

care about it?

>> Proprietary information that, like,

maybe specific to your company or some

methodology that is specific to you that

has to be referenced in every single

conversation, cuz the annoying part with

an agent.md file is every time you go

back and forth with the agent, it's

added in the context, right? The cool

thing about skills, and I'm going to

talk about skills in a second, the way

skills are designed, the skills are used

in a way that's called progressive

disclosure, meaning, when you have a

skill file, the entire thing isn't added

to context. It's just the title and the

description. So, the agent has the title

and description in the context, and when

you, let's say you have a notion report

skill, right? And you tell your agent,

"Hey, I want you to create a notion

report." It's then going to check its

context and be like, "Oh, I have this

skill. Let me check out the entire

document." So, it's not in the context,

what's in the context is the name and

the description, but that's enough for

the agent to be like, "Oh, this is a

skill I need. Let me go use it." Which

is fantastic. I'm a skills maxi, and I'm

going to show later in the episode like

how you craft the perfect skills. But,

with agent.md and claw.md files, its

context being added at every turn,

right? So, let's say you have like a

thousand line file claw.md, and let's

say that's like 7,000 tokens. You're

spending 7,000 tokens on every run. Now,

do you need to? Most likely not. It

probably should be a skill, but if you

have some sort of company proprietary

information, or like there's something

specific that you do that the model

needs to know at every single turn, then

you use it. The thing is 95% of people

don't have that, right? So, I'm not a

fan unless that's the case. So, and and

and the reason being is we're wasting

tokens, right? It's in every single

turn.

But, this is where the beauty of skills

come. Um I'll show my screen here.

The your skill, again, this is not like

word for word how it looks, but a skill

basically looks like this. There is a

name, there is a description,

and then underneath

is a bunch of information. I'm going to

put bunch of info.

What When you create a skill.md file,

what gets added into the context is

actually just the name and the

description,

right? The bunch of info doesn't get

added. So, imagine you have two

sentences versus an agent.md that has

like a thousand lines that get added

into the context. We're talking

thousands of tokens compared to a couple

hundred. And the agent only gets the

bunch of info when it realizes it needs

this skill. So, if I have, let's say, a

certain way of generating a report, a

certain way of structuring my code,

why would I put that in the agent.md

file when I can have the agent call on

it progressively when it needs it,

right? So, this is why skills are

honestly, like I'm a shill, I'm a maxi,

but people do it wrong and I'm going to

share the right way on how do we create

skills. So, so far we have the system

prompt, the agent.md, the skills, and

then we have the tools, right? So, if

you're using cloud code, there's already

built-in tools that read tool or write

tool. Like there's many tools that it

uses. This has to be added into the

context because the model the model

doesn't call the tools. It like it's the

agent harness around it that allows it

to call the tools.

And then in this case, we also have our

code base, right? Like whatever if we're

building a web app, a mobile app. I know

most people here won't care for the

specific framework and honestly, we're

getting to a point if you're not

technical, you really shouldn't.

Um and then we have the user

conversation. So, this is what

the complete context window is filled

with, right? And this can total up to

let's say like at the beginning this

could be like 20,000 tokens and as the

conversation continues to grow, you

might reach your limit of 25 250,000

tokens and that's when you see both

cloud code and open AI codex they

they'll compact, right? So, beautiful so

far, right? This is how context works.

Why skills are important and how you

should generate skills.

Let's say I have a specific workflow.

For example, for my YouTube channel, you

know, we're at a point right now Greg

where we get sponsors now. Crazy. When I

first joined this not when I first came

to the pod not a thing. We get sponsors

now. It was just your mom sponsoring the

channel. Yeah, yeah, yeah, it was just

her showing love, feeding me. Uh but now

we get sponsors. I get a lot of emails

and some are good, some are bad and it's

a lot of time I'm sure you're aware to

comb through and to check. So, I have an

open cloud agent that has its own email,

right? I I I have it I don't I given it

access to my email, uh cuz there's like

attack vectors and I've been hacked

before, so I'm very careful with these

things, but it has its own email. And

every time I get an email from like a

sponsor, I forward that email to the

agent. Now, the first time I told my

Open Cloud agent, "I'm going to forward

you emails. Check every 15 minutes when

you have an email.

Um and when you check the email, do

research on the sponsor and tell me if

they're worth it."

That's all I told the agent.

Every sponsor email I sent it, it was

like legit, legit, legit, perfect,

perfect, perfect. There was no like the

There was no rejection. There's no this

is bad or these guys are a scam or this

product's not good. Like there was no

deep research being done by it. So, then

I realized, "Huh, okay. The model needs

a step-by-step guide."

This is when I create a skill. But

here's the problem. A lot of people will

I'll just write it down here will

identify

uh identify they have a workflow, right?

You have some sort of workflow. And then

they'll jump to create the skill right

away.

This is the Let me click hide here. This

is the worst thing you can do. I'm just

going to draw arrows to signify

that this is bad. You don't do these.

And the reason why you don't do this is

imagine

you hire an employee or you're mentoring

somebody.

Um correct me if I'm wrong.

You're probably going to tell them what

to do.

And if they ask you questions on how to

do it, you'll help them. You would

ideally like them to fail and then you

want to then tell them, "No, this is how

you do it." Like there needs to be some

sort of experiential learning. The way

I've been creating skills, Greg, and I

have like a 100% hit rate now when I

tell my agent to do something specific

is I actually walk with it step-by-step

on doing the workflow. So, in the case

of my YouTube uh analysis, I told the

agent, "Okay, I just sent you an email.

Tell me about the company." Company's

this, this, that, and that. Okay, their

Twitter, check their YouTube, check

their Trustpilot, check if they raised

any money. If two of these are have not

If two of these don't exist or not in

good standing, automatic rejection. It

checked and it was like, "You're

absolutely right." I was using Opus.

Um these uh this is not a good company.

And then it would just we would We have

a spreadsheet in Google Sheets. It'd be

like, "No contact."

>> It's so frustrating too, right? Cuz

you're like you give it a task and it

seems like so binary, like right or

wrong. And then when you tell it, "Hey,

like why didn't you look at the

Trustpilot? Why didn't you see if

they've raised money?" "You're

absolutely right."

>> absolutely

>> It's like, "What?"

>> And And the thing is the reason why this

is the case is the models uh actually

don't think. They're predictors of

tokens, right? So, when you give it

English, when I give it English, it maps

it on this vector graph and then it

looks for the closest resemblance and it

says, "This is the response," right? So,

when you say, "What is the capital of

France?" It maps it again on this graph

and it says, "Oh, Paris is pretty close

by." Then it gives you Paris. It has no

It doesn't think. It doesn't understand.

It feels like it understands. It feels

like it thinks. Heck, it even feels like

it has emotion. That's because it's been

trained on so much data. But it actually

does not know how to think. And this is

where a lot of people be frustrated um

with like, "Why is it not understanding

me?" You have to walk with it. So, I

told it, "Okay, this is how you

research." And it's like, "Okay." It

researches. And guess what? This is part

of the context. And I'm like, "Okay, now

that you're done researching, when it's

a good company, these are the qualities

you look for. And then when it's really

good, send me an email."

And then once we had a successful run

and we did it again and again, then I

converted it to a skill.

Or the reason being is a lot of people

create the skills themselves or I I

mean, they'll use the AI to create the

skill, but it doesn't have the context

on what a successful run looks like.

Right? Cuz most of the time, especially

if you're using Open Claw, it's probably

going to fail at the API call. It's

probably going to call the data wrong.

Like there's so many places it's going

to get wrong and I see a lot of people

saying, "It's just so frustrating. This

is terrible technology. Why doesn't it

work?" It's cuz you don't understand how

an agent works, right? It will mimic you

perfectly, but you've given it nothing

to mimic, right? So, I will

do the workflow myself. So, the the

updated version is identify the

workflow,

go back

and forth and teach it. So, like I'm

doing it like I'll be like, "Okay, first

do the research." Here's the result. And

I'll be like, "What do you think about

this?" "Oh, these guys are terrible."

You're absolutely right. "Okay, what do

you you should go to the Google Sheet

and mark this as bad company."

I've done that. Once I've had that back

and forth, then I tell the AI,

uh

"Review what you did

and then create the skill." So, now it

has actual context with how it worked

and it's going to create the skill

beautifully. I don't handwrite skills. I

don't think you need to. You can use AI

to do it. They even have a skill to

create skills. Skill inception.

But, you should have the context of what

a successful run looks like. And this is

why, by the way, I don't install skills.

Like I've seen people like, "Oh, this

Notion skill, this social media skill,

whatever." I'll I'll I'll review it.

I'll check it out. I'll even give it to

my AI and be like, "Oh, what are some

things we can learn from this?" But, I

don't download skills because your agent

needs the context of a successful run,

which you then turn to skills, right? Um

and this is the big thing I see. You see

skills marketplaces. You see download

this and that. First of all, it's a easy

way to attack somebody. So, I would be

very, very careful with downloading some

random person's skills.

But, second of all, again, it's all

about context, right? It's all about and

you know, Open Claw has a memory layer

and all these type of things. You want

it to do the right thing and the only

way it can do the right thing is if you

give it the proper context. And to me,

the best way to create a skill is to

work with it in your specific workflow.

Once you have a successful run, tell it,

"Okay, review what you just did. This is

the skill you need to create." I'll

pause here.

>> I mean, it makes sense, right? Cuz

if you hired an employee, you would do

the same thing.

>> Yeah.

>> You wouldn't You wouldn't just be like,

"Okay, go do this thing. Good luck."

>> Yeah.

>> Uh and by the way, this is how you're

going to go do things forever. You would

map out a workflow. You would identify

what right and wrong is. You would

uh do it iteratively.

And then, once you've gotten to that

point, you would codify it.

>> 100% and I think like that's the thing.

Like, we should treat models and these

agents like very new employees versus

like these black magic boxes that like

know everything, right? They know

everything because they've been trained

on a lot of data, but they don't know

your workflow, your steps, right? So, I

see a lot of people who have you know,

15 like right off the they'll set up

open claw and um 15 sub agents, 30

skills.

Yet, you haven't even set up your own

workflows, right? And these things are

cool right off the bat and and there's a

perfect time to use sub agents. I use

sub agents a lot.

But, the way you build like I call it

scaling for productivity, not scaling

for what looks cool, right? Like, I've

seen like for example, paper claw. Paper

claw looks awesome. Cool. I used it. I

loved it, right? But, I think people

would be more productive if they built

up from scratch their own version.

Meaning like, okay, you have your own

like

um

you know, like editor, right? Content

creator.

>> So, you're You're asking people to do

the work, basically.

>> 100% 100% and cuz the thing is, it's

like

look, I'm in the position where like

people using like these beefed-up things

make a lot more sense for me. And the

reason being is like I could build a

product like that. Like, I know what

your audience wants. I know what my

audience wants. Like, you know, heck, I

could spin up agents and build this

thing, right? But, if I'm going to be

completely honest, if you want to scale

for productivity, it starts with one

agent and you building up the skills.

And then, okay, now you've built up some

skills and now you add a sub agent and

your one agent manages multiple agents.

Right? Like, imagine this. Like, imagine

I start a company and off rip, I have 10

employees.

Never managed a team in my life. Heck, I

don't even have a really big family. So,

like, I'm a little Like, you know what I

mean? So, it's like you have to sort of

Yeah, it's not sexy. Um and I apologize

if this is not the cool thing people

wanted to hear. But, you sort of have to

put in the work and build it up. And I

And I personally believe you're building

skills, like, your personal human

skills, not

skill that MD files, that when the

models get better, when the agents get

better, you will be more valuable cuz at

the end of the day, as long as there's

no new paradigm for models, LLMs just

predict tokens.

They don't understand or know the way

you and I do, right? And this is why

although like yeah, the job scene and

all this stuff is scary, I genuinely

believe anyone who knows how these tools

work and like knows how to build agents

and like craft skills and like knows how

to make them productive, we're in it for

a good run. Mhm. So, you're saying that

if you know how to do this, you won't

join the permanent underclass.

>> The permanent underclass. [laughter]

So, is the permanent underclass

basically like I've seen this these this

this on Twitter a lot. Is that basically

AI has replaced you, so now you're just

>> From what I understand, it's

once AGI comes,

all these white-collar workers are going

to lose their jobs.

And if you don't know how to build

skills, use AI,

people say you're joining the permanent

underclass. That's That's the term.

>> It's permanent, too. That's scary.

>> [laughter]

>> So, I just have a little bit of time

left. Yeah, by the way, like

it's ridiculous to call it a permanent

underclass.

>> Yeah, cuz that's terrifying. [laughter]

>> understand underclass, but permanent

permanent it's like

>> Like you're saying there's no hope like

>> No

>> Yeah, um I mean, we are in like

knowledge that took 20 people 20 years

to acquire is now like 20 bucks a month,

right? So, there is like a huge shift,

right? People who are non-technical are

I I think I saw yesterday like some guy

hit like a hundred million dollars um

and he vibe coded the whole app. I think

it was him and his friend.

>> 1.8 billion

>> billion?

>> Yeah.

>> So, you know what I mean? Like it is the

there is a shift, right? And I think

this idea of like well, I'm not

>> how you were like billion. You were

about to just leave this podcast and

just be like

>> No, you know what it is? I just

realized, man, I overthink things. Like

I just need to drop the thing, release

the thing and there's like wisdom in

that like

there needs to be this level of

delusion, which I don't have. Like I'm

trying to work on where you're like this

is just going to work out. We're just

going to launch the product. It's going

to succeed and if it doesn't, onto the

next one cuz 1.8 billion

>> Yeah, dude.

>> Like B?

>> B

>> USD?

>> We're Yeah, we're not talking Monopoly

>> [laughter]

>> Cuz it was Canadian.

Uh it's it's uh

>> We're not talking carny coins.

>> [laughter]

>> We're talk we're talking real Benjamins.

>> Yeah.

>> Yeah, that makes sense. That makes

sense. But yeah, like I I hope this like

understanding of like again, I

personally don't think you don't need an

agent.md file unless you have something

proprietary.

Um skills are valuable. Build your own

though. Build build your own. Like you

know like when you ask your mom when you

were a kid, oh, can we have McDonald's?

And she's like we have food at home. We

have food at home. Build your own

skills. For coding perspective, from

coding wise,

um

a lot of the companies model companies

have realized that the agents are really

good at writing code, particularly

TypeScript. And this is why there's been

like you see this advancement with like

Claude co-work and like even open claw.

Really what they're doing under the hood

is they're writing code, right? They're

writing code calling APIs and all this

stuff. So, when it comes to building a

project um you actually don't need

skills or like you don't need an agent

MD file specific to the tech stack you

use. Like I remember we used to I'm

using React and you know, Convex or I'm

using Next.js and Supabase I'm using

this and I'm using that and you put that

in the agent MD file and you have like

all these lines.

For the most part, unless again you have

a specific specific workflow

unnecessary. And the reason being is

code itself has become context now. So,

the more the more important thing is

starting with a solid foundation.

Templates used to be big back in the

day. People made lots of money with

templates. I believe templates are going

to have a renaissance because if you

have a solid like template, right? Like

whether it be like for web app or mobile

app

because that becomes context for the

agent, it's going to build on top of

that, right? And again, I didn't need

some large agent.md file. I didn't need

any large cloud.md file. What I needed

was again, minimal context usage and

skills. So, if there's anything

anyone can learn from me is build your

own skills. Build your own skills. And

there's this methodology I don't know if

I've shared this with you, recursively

building skills. So, let's say you've

built your skill, right? I have I'll

draw a diagram cuz why not?

Let's say I have a workflow

and after you like setting up my

workflow with an agent, I've decided,

you know what? I'm going to turn this

into a skill, right? So, this is my uh

skill.md.

Now, here's the thing. Even though you

have the skill.md, the agent at some

point is still going to mess up because

there's probably gaps in the information

it has in the skill. So, when it messes

up, I'm going to work with it again. How

do I work with it? You messed up.

Try calling the API again. Try doing

this again. Or even ask it when it tells

you, "Oh, I failed. I couldn't do this

task." Believe it or not, when you tell

the agent, "Why did you fail?" When you

ask it, like, "What's the error that you

got?" It will tell you descriptively,

"Oh, I got a 505 error. You uh, you have

insufficient credits." Like, "Oh, okay.

So, it's a credit issue. Fine." So, I

would tell it that. And then,

I would pass that failure back to the

agent. So, let's say uh, it did

something wrong. We identified the

failure. All I did was asking it. I will

give that failure back to the agent.

I'll be like, "You failed here. This

didn't work. Fix this."

It's going to fix. It's going to write

code. It's going to do whatever it does.

Once it fixes it and it's done it right,

now you tell it with the new fix,

"Update the skill so this doesn't happen

again."

I have, like, for my YouTube channel, I

have like a report generator. It calls

Notion, Dub Analytics, YouTube

Analytics, Twitter Analytics. Pulls from

my It pulls from like eight data

sources. There's no way you're going to

one prompt and the agent's going to do

it. But, every time I tell it to do that

workflow, it takes like 10 minutes. It

executes it flawlessly. Why? I went

through five loops of this.

Five iterations of recursively building

the skill. And that skill is so good. I

genuinely think if anyone's going to if

like skills marketplace is going to be a

thing, there's going to be people who

sell skills. Like, really well-defined,

like, step-by-step skills because people

are just creating them without having

built out the workflow with the agent,

right? So, use the workflow by hand,

like, telling it each step. Once it's

done it completely, create the scale out

MD file, continue to use it. It's going

to mess up. When he messes up, you thank

God you don't complain cuz a lot of

people are like, "Oh, I messed up. I'm

angry." No, this is a moment where you

identify the error, tell it, "This is

the error, fix it." It'll fix it itself,

and then you tell it to update the skill

file so that this doesn't happen again.

>> So, that's a little bit about shifting

your expectation, right? Cuz people just

assume uh

it's going to work in the beginning.

You're saying basically it's not going

to work initially. There's going to be

two, three, five, six hiccups. Um and

over time, it should

be good.

>> So, this is most people's expectations.

Right?

>> Yeah.

>> And

the way I've personally experienced is

it's like this.

So, there's like this early area of

investment that you have to make that

sucks, that nobody will tell you,

especially Agent Harness's company cuz

they wouldn't raise as much money if

they did. But like this maybe I would

give it 2 weeks cuz it took me 2 weeks

like OpenClaw when I first set up

OpenClaw, I thought the same thing. I'm

like, "What What is this garbage? Right?

Like it doesn't understand anything.

It's confusing." Then I realized like,

"Oh, like

let me go lower level." The models and

the agents like they they don't think

like you and me. Right? Like I could I

could tell you, "Hey,

um Greg, we need a report on like, you

know, the financials in Notion."

Because you're probably were in the same

business, we worked together, you would

understand based on the context you have

of the business what that means. But

imagine a new guy joins like, "Yeah, I

need a report on the financials."

So, where do I even start?

>> reminds me? I wonder if we can put this

clip in.

But in the office, you watch The Office?

>> I am not an office watcher,

unfortunately.

>> There's a clip that

uh there's a new boss

and

the new boss goes to Jim, one of the

main characters. Yeah, and he asked for

a rundown.

So go go The Office

The Office rundown.

>> I don't know.

>> Basically, Charles

the whole episode is about

Jim trying to ask around and be like,

"What What is a rundown? Like what is a

rundown?" He's like calling his dad,

like "What is a rundown?" You know what

I mean? He's just Um he didn't have the

context.

>> Yeah. He didn't have the context.

>> Yeah. And and and it goes back to my

initial point, the models are really

really good now, but the context matters

more than anything, right? So when you

see like these large agent like

companies and sub agents, and again, I'm

not saying those don't work, but I'm

saying

probably won't work for you off rip

because you haven't built it up to get

to that point, right? So let's say like

for me for example, I started with um

one agent. Let me draw this. I started

with one agent. And this was like my

main agent. This did everything, right?

This checked my spreadsheet, this

checked my sponsors email, and all these

type of things. And once I had like

predefined workflows, let's say for like

working with sponsors, then I can

actually have a sub agent. What's the

purpose of the sub agent? The sub agent

does all the marketing stuff, right? But

I'm not creating the sub agent for the

sake of creating it. It's going to have

skills, it's going to have context, and

it actually makes sense for me to have

sub agents, right? So I've built out my

thing to like now I have five sub

agents. I have one for marketing, one

uh for business, one for personal, and

and that's it. And I'm willing to bet if

I went open claw to open claw with

anyone, my system is more productive

because I didn't scale for what looks

cool, I scale for productivity.

>> That was a bar.

>> That was a huge bar. We got to clip

that. I was just thinking that clip,

that's going to rip.

>> Yeah, that was a bar. Um what else do

you want to leave people with or is this

this is the main point? Yeah, like

here's like the we've got to a point

where the models are good. The models

are really good. The context matters

plus the harness, right? So, for

example,

there was this benchmark, although I'm

not 100% supporting it, that there was a

difference between the quality of output

that cursor generated versus Claude code

versus Codex, right?

Um So, what that tells me is that we've

reached a point where the models are

really really good. They're probably

going to get better. The next iteration

is probably going to get better, but the

harness and the tools that you surround

it, the context that you give it is

going to matter even more. And just like

in everything in life, less is more,

right? Like building up step by step,

making it productive for you first

before you add the shiny new thing. Like

cuz I tried all these tools all the time

like especially paper paperclip blew up

and a lot of people are talking about

and it's fantastic, but I'm willing to

bet if people took 2 weeks to build up

to the version cuz you can prompt open

Claude to do all that stuff. If they

built up their own version of paperclip

in 2 3 weeks where like they're building

things that they actually need, their

productivity level will skyrocket

through the roof.

>> It's a hot take.

>> It's a hot take.

>> Might get me in trouble.

>> No, it won't get Who's it going to get

you in trouble with? Maybe paperclip

raises a billion dollars and they don't

acquire my podcast.

>> [laughter]

[gasps]

>> I think

Listen, you're you're out there, you're

trying things and you're just sharing

what you're learning in real time. So,

if you're just

You're not

>> Things can change by the way. Hey, like

2 weeks from now it could be like no

give the agent everything. There's this

new memory paper that Google released

and like now like it has the ability to

index information and stuff, but

as it as it pertains to real life, less

is more, simple is better, right? If you

can't explain it in in a few sentences,

you probably don't really understand it,

right? And I find that the models are

trained on so much information,

especially when it comes to programming,

building, and like and um what do you

call like day-to-day work, like

financial work, or like any sort of

like, you know, checking contracts and

stuff. Like they the model companies are

focusing on that, like on white-collar

work. The models are really, really

good. What matters more is the harness

and the tools you provided. And the one

thing that you and I have that the

models don't have is my specific

workflow, my specific taste, my specific

strategy of doing things. And those can

be codified in skills, right? This is

why like skills make sense when you

build them. Not if you download my

skill. Like I have this one skill.

Um like again, don't download it. Do I'm

telling you now, do not download it.

Don't use it. I just put it so I can get

some GitHub stars. Um

I have this one skill, and it's

literally a code structure skill.

And I'll put the markdown so people can

see it.

Um it's 116 lines. It's basically after

AI has generated a bunch of code, I like

it structured in a certain way, so it's

easy for me to review it. And like I

mentioned earlier with skills, the only

thing that gets added into context is

the name and description. So when I look

at the name, it's code structure. When I

look at the description, use when

multiple workflows duplicate the same

operational logic when deciding that

blah blah blah blah blah some nerd

stuff. So when I tell the agent, I want

to

clean up the code structure, it checks

the skills it has, it sees the name, it

reads the description. It's like, oh,

this makes sense. Then it progressively

discloses, meaning once it realizes it

needs this skill, then it adds the rest

of this, right? Versus if this was my

agent.md file, imagine every single

time, and we can actually check how many

tokens this is.

Let me check. Um

what was it? OpenAI token tokenizer.

If I go to this,

So, this is 944 tokens. So, if this was

an agent.md file, every single time I

have a chat, I'm adding 944 tokens.

Tokens ain't cheap now.

>> No.

>> But, if I just have the name

and the description, it's just 53

tokens.

>> And it's not even cheap. It's just like

you're not trying to

hit the limit quicker than you need to

hit the limit.

>> Cuz the model will get dumb as the

context window closes, right? So, if you

have like a context window, and I can

draw this out. If this is your context

window,

and like the optimal is you're between

like there's always like maybe like 10%

is already filled with all the

system prompt and all that stuff. You

want to be between like

you know, fresh to like 70% cuz the

closer you get to 99, 100% like 99, 90,

80%, it starts to get dumb, right? And

you can think of this like a human. Like

imagine you throw a bunch of information

again and again and again and again. And

this is why like when I like was in

school, like last minute studying never

worked for me cuz like I didn't pay

attention the entire year. Now I have to

learn about polynomials, and I have to

do these graphs, and there's this weird

notation. It's impossible for me to

catch up, right? And it's the same way

with the agents. You want to keep your

context window You want to save your

context window cuz hey, it saves you

money. But not only that, it makes a

more performant

um agent. So, less is more. Less is

more. Rely more on the model's strength,

and what the model needs is what's

unique and special about you, your

workflow, your business, not general

knowledge. Don't tell the model use

React.

It knows to use React. Don't tell the

model um you know, things that like

should already be known uh for the uh

like you know,

task. Like for example, like let's say

I'm doing a financial report, and then

the agent.md file, I say um

to denote money use a dollar sign.

It's going to use a dollar sign. Right

now, if you have a specific currency,

then you like, oh, use this currency.

This is the You know, like for something

that the agent won't do manually, like

won't know manually, that's when you

have like your agent.md's, Claude.md's,

but honestly, these are a farce. You

don't need them. Um, skills skills

skills skills skills is what it's at.

>> Thanks for keeping it real. I appreciate

you, man.

>> That's all I'm going to do. Thank you,

man.

>> it.

Uh, like always, I'll include links

where you can follow

Ross Mike on YouTube and X and other

places in the show notes in the

description, so go follow him there.

Always clearly breaking down things. We,

uh,

>> [sighs]

>> I have to be real with you. You weren't

going to come on the show today.

>> I wasn't, and I'll be honest, I I told

Greg, and I'm just going to be frank.

I'm like, I don't have that banger, you

know, something new dropping, let's

review it, cuz if we going to be honest,

there's not that many tools dropping

nowadays. Like, unfortunately, the big

dogs are running the show.

>> Yeah.

>> Um, the Clauds and the

the Anthropics and the Open AI,

especially when it comes to general

purpose and

and coding,

they sort of run the game, so they're

releasing updates, and like all the

stuff has already been covered. So, I

was like, Greg, I don't know if I have

anything valuable to add.

>> And what did I say?

>> You're like, the people, you know, you

got to think about impact. You got to

think about what, you know, this could

apply to someone's And you showed me

like a a text someone, right?

>> I sent a text to you.

>> Yeah. I'm going to pull it up.

Uh, I sent a text to you of someone who

saw a video that we did together,

and it that video got him into coding.

Now, he's running a cake business, and

he's making $150,000 a year and growing.

And he said,

"The Greg and Ross Mike

episode in November last year is what

got me into coding. I've recommended to

everyone asking how to start out. And I

just sent you that text and I said,

"It's not about the numbers. It's not

about, you know, cuz you said in the

text

>> You don't see it sometimes, right?

>> everything we do to get to 200k views

minimum.

>> yeah, yeah, yeah.

>> And I'm just like

I hope this gets 200k views or more, so

like and comment to to juice those

algorithms, but if it gets 2,000 and two

people end up taking this information

and changes their business, their

productivity, how they think about

things, then you know, I think that's

why I think that's why you and myself

have been put on this planet Earth is to

inspire people to get their creative

juices flowing. And so I thank you for

for coming on and and taking time out of

your day.

>> And I appreciate the motivation and

yeah, I hope this helps somebody and I

can't wait to be back with more.

>> Absolutely. All right, catch you later,

dude.