So Stanford has a research method called

storm, which has actually been shown in

peer-reviewed testing to produce

articles 25% more organized than the

next best method. So I put all of those

storm principles into my own Claude

skill, which I'm going to give you guys

for completely free, and you end up with

the result that looks like this. It is

an HTML briefing that has been put

together by five different perspectives

of agents, and it has been verified.

Meaning if I scroll down to the bottom,

you can see that the different

perspectives are giving analysis on each

parts of the report. But at the very

bottom, you can see that we have

different sources that have been

confirmed, corrected, or demoted.

Meaning on the first pass, the briefing

would have had information in here that

just wasn't correct. But because our

skill works in all this verification, on

V2, we can have a lot more faith in this

output. So the whole idea of storm is

that instead of just shooting off one

prompt and having one angle of research,

we are utilizing a bunch of different

angles. Because if you just send off one

prompt to Claude, there's going to be a

bunch of blind spots in that research

plan. So storm utilizes these five

perspectives. We've got a practitioner,

an academic, a skeptic, an economist,

and a historian. And each angle finds a

hole that the other angles miss. And

this whole idea of having different

agents kind of like role-play their own

personalities and their own, you know,

backgrounds with different areas of

expertise, is really, really beneficial.

If you've seen other videos where I've

talked about something like the roast

skill, or how I like to use agent teams

to basically be a council, it's really,

really helpful to identify different

perspectives and, like I said, find

holes that the other angles are going to

miss. And so let me just show you a real

quick example of why that's so

beneficial. So Claude code natively has

a feature called deep research, which

launched with the dynamic workflows. So

if you come into Claude and you do a

deep research command like this, you

will basically be able to enter a

research topic and it will spin up a

dynamic workflow, which will kick off

hundreds of agents in the background. I

think in this example, there was 103

different agents running. So this will

give you a pretty solid deep research

report. As you can see here at the

bottom, it didn't actually give me any

output, it just internalized all that.

So I said, "Where's the report?" It gave

me this markdown file, which is decent,

but it's really not that thorough, and

there's not as many sources as we'd

like. There's only two up here, and then

there's a few more unconfirmed down here

at the bottom, as well as some open

questions. And then I took this exact

prompt that I asked in the deep

research, and I put it into a Storm

skill. So, I said, "Hey, Storm research,

do this." And it said, "Okay, cool.

Here's the topic. I'm going to run the

Storm pipeline now. I ran these five

agents." As you can see, the

practitioner, the academic, the skeptic,

the economist, and the historian were

converging all of that stuff together,

we're seeing where they disagree, and

then we're going to run six more agents,

which are going to verify all those

facts that you just found.

Verification's done, and now you have

this HTML report, which is consistently

going to look like this every time with

a 60-second summary key findings. And

all of these key findings are also

ranked by reliability. You can see right

here, reliability high, nine out of 10.

This one was supported by the academic

and the skeptic, and it was challenged

by the practitioner and the economist.

And it goes like this throughout the

rest of the entire HTML report here. It

also calls out the assumption that this

briefing rests on and the missing six

lens. All five lenses look at the firm

from the owner's chair, adoption rates,

productivity, ROI. None of them sat in

the seat of the customer or the

frontline employee. So, that's the

missing sixth lens here, and I would

then just say, "Okay, cool. Spin up that

sixth lens, and run a V3 of this HTML

report." And then it gives us really

practical takeaways here. And what's

cool about this is compared to something

like the deep research, which is just

going to basically give you a brain dump

of a bunch of stats it found, the Storm

research can really be tailored towards

you. You can go into the skill and say,

"Hey, here's what I'm doing. Here's my

business. Here's what our goals are."

Every time you run a Storm research

report, make it tailored towards us, you

know, what do we actually want to do

differently now that you've understood

all of this new data and research. And

so, in this specific example with the

deep research and the Storm, I put this

into Codex, so a completely different AI

model, and I said, "Hey, which one's

better?" And it came back and said the

HTML briefing is better. It's got better

evidence quality, it's much stronger,

it's got much stronger source diversity,

it's got a much stronger thesis, It's

more actionable. It's got better risk

control, and it's better for video and

content. So, in all six of these

categories here, Codex thought that the

HTML briefing was better, and I don't

know the exact metrics here on cost, but

the storm research was faster to run,

and it was 100% cheaper because in this

case we ran about What was this? Maybe

12 agents total, whereas the deep

research report this time, this ran like

over 100 agents. Maybe I should take a

little easy on the steep research run

because it did get hit by API rate

limits, but that's also another point of

like if you're going to spin up that

many agents at one time, you might get

rate limited. Whereas with the storm,

you know it's always going to be your

five personas. So, anyways, I think you

guys now understand the value of this

report. Let me show you real quick how

this actually works and how to get the

skill. So, there's basically four

prompts. The first one is where we tell

it to spin up the five different

angles, right? We've got these five

which I've talked about. That's prompt

one. You would just enter in your

research topic. And then when that comes

back, you would enter in prompt two,

which is the contradiction map. So, it's

saying, "Hey, where do the perspectives

contradict each other? Which one has

good evidence? Which one has weak

evidence?" And basically makes them

analyze each other's outputs. And so,

what we're doing here is we're basically

just chaining together four prompts in a

row, and then we're getting synthesis,

and then we're getting the peer review.

So, what I decided to do was I ran that

on its own. It worked great. And I said,

"Cool, package all of that into a skill

so I can literally just give you a

prompt, give you a topic, and you do

that entire thing for me, and you're

going to give me a consistent template

so that every time I run this you're

going to give me an HTML report that

always looks like this." So, what that

now looks like is in my dot Claude, I've

got a bunch of skills as you can see.

And if I go to my storm research skill

and I open up the skill.md, this is what

we've got. So, the storm research, it

turns one topic into a verified

multi-perspective HTML briefing. It

simulates five expert lenses on the

topic, maps where they contradict each

other, synthesizes everything into a

single self-contained HTML report, then

adversarially peer reviews its own

outputs, and verifies every citation

against its primary source before

delivering. You'll also notice that in

the skill we have a report template

HTML, so you guys I will also give you

guys this for completely free. This is

referenced in the skill and says, "Hey,

once you find all the information, just

put it in HTML and make sure it always

looks like this." So, that's just for

consistency on on my end, and I really

enjoy that. So, I'm going to keep going

down and explaining how this works, but

if you guys do want to go ahead and grab

these two resources, just head over to

my free school community. The link for

that is down in the description. All you

have to do is get in here, click on

classroom, and click on all YouTube

resources, and you'll be able to find

every single YouTube video and all of

the resources that I've dropped

associated with them. Once again, that's

completely free to join. Once you have

that skill, all you have to do is

you can give that markdown file and the

HTML file to Claude and say, "Hey,

Claude, this is a skill called storm

research. Put this in the .Claude

folder, and then

you're pretty much set up." And if you

guys don't know what a skill is, it's

basically just a prompt. This is

basically just a master prompt that

every time I say, "Hey, Claude, do storm

research for me," it's going to invoke

this skill, it's going to read the whole

thing, and then just run it for you. So,

it's very hands-off once you've

basically installed them. And yes, this

skill can work with codex or any other

different type of agent you want. It's

just that in Claude, it specifically has

to be in the .Claude folder. But, you

can see here I've got a folder called

.codex or .agents, and you can put

different skills in different types of

folders based on the coding agent you're

using. This currently is just a Claude

code tutorial. So, anyways, from there,

phase zero is to scope the topic.

Sometimes, if you don't give it a

specific enough topic, it will ask a few

questions before it goes ahead and kicks

off the storm. Then, it spins up the

five expert lenses in parallel, and then

we go into mapping the contradictions,

synthesizing the report, and then the

adversarial peer review verification,

and that's where we get our output. So,

let me just open up the Claude desktop

app and start a new session here. And

I'm just going to say,

"Hey, Claude, please run a storm

research for me on voice AI agents."

And so, what you'll notice here is I

didn't use a slash command, so it will

still invoke the skill. And what you'll

also notice is that

this isn't very specific, so it might

ask us some questions. Right here you

can see it says, "Okay, running the

skill storm research." So, that's how it

went ahead and looks through storm

research. And the argument that it's

currently aware of is voice AI agents.

It comes back and says, "Okay, so here's

the topic, here is the reader." And it

knows that I am an AI educator and I am

deciding on potentially whether voice AI

agents are worth a video or if it's just

hype. So, the pipeline is now running.

If I open up this, you can see it is

going to kick off those five agents, the

practitioner, the academic, the skeptic,

and all of the other ones that we need.

And what's really cool is you can click

in and see what they're doing. So, if I

click on the economist, for example,

this is the prompt that our main session

kicked off to this subagent. So, now we

can see the subagent down here is

browsing the web. It's using a tool.

It's doing research. We can click on the

academic. We can see this is the

academic prompt. And once again, the

academic subagent is, you know, doing

all the stuff down here. Now, while this

is running, let me quickly explain the

difference between having subagents and

having agent teams. So, subagents is

basically where we have one main

session. So, this session right here,

this is Claude. This is who we're

talking to. And all of these subagents

are working for this main session. So,

the main session talks to these five,

but these five cannot talk to each

other. And that is an important

distinction because that's what you

actually have in the agent team world.

You can spin up teams of agents or

councils of agents that can not only

talk to your main session, but they can

also talk to each other. And that's

really cool because what I like to do is

I like to spin up agent teams when I

need help deciding on certain ideas or

topics. And I'll have them not only do

research for me, but then I'll have them

debate with each other. So, they'll

literally argue with each other until

they reach some sort of consensus. Agent

teams are much more expensive than

subagents though. So, important

distinction. I'll bring more videos on

agent teams later, but if you do want to

check out a deep dive, check out this

video that I've tagged right up here.

And also, if you want to check out

another video where I've deep dived even

more on subagents, then you can check

out this video right up here. Now, you

can see all of these subagents ran on

Opus 4.8. If you don't want to do that,

you don't have to. You can have all of

these sub-agents run on Haiku or Sonnet

if you like. But in this case, I liked

for them to run on Opus. But all five

lenses are in, so now it's going to go

ahead and look at the contradictions. So

you can see it's reading that file,

which is the report template. It's

running these agents in the background,

and now it's going to start verifying

all of those different citations and

stats and the different things that our

initial passive agents had come up with.

Also, I know in this video I have

switched between the Claude desktop app

a little bit with VS Code. If you guys

have been watching me for a while, you

know that I typically do like to do most

of my work in VS Code. Um Claude

basically works the exact same way in

both. It's just a difference of UI,

really. But the reason I chose to show

some of this video today in the desktop

app is because I thought it's cool to

show the actual agents running in here.

But you can see that our report has come

back, so let me actually just open this

up in a browser. You can see this is the

V2 version, so everything has been

verified. If I scroll all the way to the

bottom, you can see the sources were

either demoted, corrected, or confirmed,

so that is great. We've got our

60-second summary. We've got our key

findings, which obviously once again are

ranked by reliability. So what I would

recommend for you guys to do is go grab

the skill, put it into your own Claude,

and play with it a little bit. Make it a

little bit more tailored towards you.

Maybe you can play with the HTML report

if you want it to look a certain way.

But then do it on a topic that you do

know a lot about and that's important to

you in your business. And then just read

through it and see where you need to

improve it or change it up a little bit.

And maybe you even want to add a sixth

lens or a seventh lens. Maybe for me and

my workflow, it would be helpful to add

like a beginner in AI because that's a

lot of people that we're teaching our

beginners in AI. Or maybe it would be

good for me to add to the skill a

content creator or something like that.

So I guess the reason why I'm saying

that is because I think what you should

take away overall from the video is,

yes, go grab the Storm skill and test it

out, but it's also less about this

specific skill and this specific

Stanford method being the best for

everybody, but I think the theories that

you can pull out of it like the idea

that the more perspectives you have

doing research and contradicting each

other, the better and more holistic

research you're actually going to get.

Basically, just the whole idea of if you

don't have subject matter expertise, see

if you can borrow it in some way. See if

you can go ahead and kill your own blind

spots, find the gaps in your knowledge,

and go use agents to create little

experts all over so that you've got this

council of agents that have different

expertise and different knowledge that

that have your back, no matter what

you're doing. So, I know this was a

quick one today, but hopefully you guys

enjoyed it or you learned something new.

If you did, please give it a like. It

helps me out a ton. And as always, I

appreciate you guys made it to the end

of the video, and I'll see you on the

next one.

Thanks, guys.