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I think cowork will be the
place where most business

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people will park it and say.

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“Wow.” Well,

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hello and welcome to another edition
of the eCommerce Evolution Podcast.

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I’m your host, Brett
Curry, CEO of OMG Commerce.

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And today I have a returning
guest, a multi-time guest,

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maybe like fourth or fifth time.
My good friend for a long time,

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fellow Missouri resident, Russ Hinnaberry.

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And for those who don’t know, Russ,
Russ led some teams at Digital Marketer,

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used to help run the Traffic
and Conversion or TNC Summit

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back in its glory days, which that
was just a rich, fun time- RIP. …

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in this industry. RIP
to TNC, it’s so true.

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But you and I met in 2010 or something
at a marketing conference in St. Louis,

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Missouri, The Lou, And
really connected then.

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But more recently, you are
the founder of the Click.ai.

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You’re also the co-author of
Digital Marketing for Dummies.

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And when I have AI questions,

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when I want to know what are people doing
with AI inside of agencies and inside

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of marketing orgs, I talked to Russ
Henneberry. And so with that, Russ,

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welcome back to the show. And how’s
it going? Real good, man. How are you?

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Dude, I’m doing good. Doing good.

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Just feel like every
day is going to unlock

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something new on the
AI front and exciting,

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disorienting, scary, but
mostly exciting. And so-.

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I mean, I didn’t know how bored I was
with marketing until we got like this.

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Yeah. Yeah. This technology
has reinvigorated me for sure.

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Yeah.

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And it’s also one of those interesting
things where obviously AI is progressing

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very rapidly. I heard someone say on a
podcast just yesterday, they were like,

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“No,

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2026 is going to be the year of the most
rapid disruption ever on AI.” And I’m

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like, okay. Yeah.

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And then there’ll be more disruption
this year than all the AI years past or

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whatever. So buckle up,
which is fun for sure.

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So I want to dive into a few
things. I want to talk into

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agentic AI and kind of how things are
flowing and then just some of the latest

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news. But also you’re plugged into
agencies, marketing orgs, brands,

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and you’re seeing how they’re using
AI and what you’re doing with AI.

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But I think maybe the
first place to start,

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because I know this is something you
were just absolutely bullish on as MI,

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and that’s Claude cowork.

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And so it’s just absolutely
ripping right now.

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All my business friends are using it.

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I just started testing it
actually just this past Saturday,

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started tinkering with it and holy
cow. So for those that don’t know,

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what is Claude Cowork? And then
let’s dive into some applications.

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Well, so there’s a few
things about Cloud Cowork.

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We’ve probably all used
regular ChatGPT, regular Cloud,

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regular Gemini or whatever. The
new thing about Cloud Cowork,

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so it’s a desktop app right
now only available on Mac.

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And the big three differences
I think to think about with

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Cowork is first that it
is far more agentic. So

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it makes plans and

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unfolds those plans right
in front of your eyes.

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So you can ask it far more ambitious
for far more ambitious tasks

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than you could with a regular chatbot.

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And the reason it’s able to pull this off
from watching it work is that it works

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with your local files.
So it can create files,

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it can delete files, it
can move files around.

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And one of the most important types
of files that it produces is called a

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skill.md file or a skill file.

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And that skill file,

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you can think of it like you
would think of a custom GPT

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or a Gemini Gem,

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but it’s just a set of instructions
as to how you want something executed.

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And here’s the crazy part about this is
that when you’re working inside a cloud

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cowork and you do something,

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or you can even describe
something that you want done,

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it can build that skill
file and then just save it

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into your directory.

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So it starts to organize
this entire set of folders

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and files.

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And one quick tip on this is that when
you do go to start to play with this,

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go slow and just kind of think
through how you want that

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folder set up, that structure set up.

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Because if you’ve worked with something
like ChatGPT before and you create a

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custom GPT that does X, like let’s say
it writes hooks for ads or something.

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So it’s a custom GPT that’s
really good at writing ad hooks.

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Maybe it’s personalized for your business
and your persona and all these things.

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So it’s an excellent GPT.

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But the problem is with it is
that it’s saved in the cloud and

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if it’s not performing properly, you
have to go back over there, edit it,

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and you got to go in there, figure out
where it’s messing up and change it.

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Well, you don’t do that in Claude cowork.

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So if it produces an output
and you say, “You know what,

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you’re being way too hypey with those
hooks. Those hooks are way too hype.

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I like this one because it’s a little
more down to earth and that’s a little

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more on brand.” It’ll go back and edit
the skill. So it’ll ask you for it.

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Say,

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“You want me to go and adjust the skill
so that I just nail this for you every

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time?” And so these skills are
almost like self-healing, right?

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They build themselves pretty much. They
ask you, “Do you want me to build a.

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Skill?” So self-improvement
or recursing at most.

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Yeah. Right. And it all is happening on

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your local machine. In other words,

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there’s a version control
part of this as well.

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So one of the things I’ve always
recommended with AI is that the very first

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piece of information that you need to
feed any AI when you’re doing anything

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about marketing or business
growth is a persona document.

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You need to know who you’re talking to.

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So it always boggles my mind
when people are like, “Oh,

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my AI doesn’t give me very good
output.” And it’s like, well,

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does it know anything about who you’re
trying to reach or who you’re talking to,

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who you’re writing to,
who you’re planning for?

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The second document that
I always recommend is a
document that clearly outlines

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your offer. So what do you sell? What’s
the cost? Do you have a guarantee?

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What are the deliverables, et cetera.
Those two pieces of information,

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and most of us have kind
of caught onto that,

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that we could feed the AI this and
we feed it that and it gets much,

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much better. The problem has been that
there’s a version control problem.

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So you build a GPT and you attach
these persona and offer over here,

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and then you build another GPT,

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you got to attach the second one and
the third one. But in Claude Cowork,

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since you’re working from a file system
and it’s basically just plugging a brain

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onto Claude cowork,

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there’s a single persona.md
file, a markdown file,

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or it could be any, I guess it would
be a text file if you wanted it to be,

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but Claude Bill’s markdown files that

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you can adjust that one place.

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And anytime it needs that persona
or it needs that offer or it needs

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this skill or it needs this
spreadsheet or it needs whatever,

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it just goes and finds
it. It’s very, very,

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very good at understanding when it
needs a particular piece of context

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that’s located somewhere in your brain.

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It’s amazing. Amazing.

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I think it’s still a little bit trippy
for people and they’re still maybe not

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fully wrapping their heads
around it. But I mean,

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Claudco work can really become your
personal assistant in a lot of ways,

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your research assistant, your
marketing assistant, your copywriter,

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all those things. But more than just a
chatbot, it’s just like doing things,

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right? It’s just running things.

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And so maybe you could talk through some
specific examples, like either where,

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how have you used Claude Cowork?

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I’ll explain what I was experimenting
with this weekend as well,

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but how have you used it?

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What are some of the best use cases
you’ve seen from agencies and brands?

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What can this do for us?

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Right. So one of the other
things about Claude is that,

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and I think this is the
Cloud ecosystem in general,

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is how good they’ve gotten at
connecting to external sources.

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So for example, I’ve
connected my notion to it,

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and so Claude Cohort can just
go fetch something out of …

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So for example, when I
start a Zoom meeting now,

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my Notion starts to transcribe
those notes using Notions AI,

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which is cool. But at the same
time, do I do anything with that?

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Do I do much with it?

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And so my workflow now though that
I’ve got Cloud connected to Notion is,

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I jump on a Zoomie. I did a webinar today,

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a training today with
some people and 90 minutes

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on ChatGPT projects and I was
going through that and then

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Notion’s transcribing,

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and then at the end I can run a skill
through my Claude cohort that just says,

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“Go grab that transcript
and do X to it. ” So

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I think that’s really the unlock here,

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is to understand that we have to have

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sources of material.

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Where is the source of some idea,

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some data, some source,

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and how can we plug that in and
then what do we want to happen?

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And if we know those two things,

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what do we have to put into the AI and
then what do we want to happen from

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there? Even if we can just describe it,

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the AI will figure it out from
there and then it’ll ask you,

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“Do you want me to just build a skill
that just does this every time?” So you

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talked about, before we jumped on,

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like doing things with your
financials and stuff like that.

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So dropping some source
material into your claude

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brain, if you will, spreadsheets,

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et cetera, and then pointing Claude
cowork at it and saying like,

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“I want you to transform this into
whatever.” It could be charge graphs,

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insights, whatever. And
then at the end saying,

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“Write that up as a skill
or even a full routine.”

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So I mentioned about trying to get a
little more ambitious with what we’re

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asking.

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You. What’s the reason
why a skill and a routine?

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Can you talk about that real quickly?

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Well,

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a skill would be the technical
term for it inside of Claude,

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but I do think about these things
as routines. So for example,

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when I arrive at my desktop,

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I just open Claude co-work and I say good
morning. And that triggers a routine,

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but it’s really a skill. So
it’s written into a skill file,

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but I think of it as a routine
because what it does is it greets me,

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it puts my manifesto out, which is like
this thing that I like to read each day.

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And so it’s got steps and then the next
step pulls my weather because I’m always

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wanting to know what the weather is when
I’m sitting inside at my desk all day.

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Isn’t that funny, but Will, but
we both live in Missouri, right?

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So typical Midwest,

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it’s like it’s going to be 70
degrees a few days from now.

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It was like negative five a
couple weeks ago. It’s just crazy.

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But like it matters. We’re sitting
in the AC or the heat, so we’re fine,

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but we still want to know. But yeah,

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you want to kind of run this skill
or this routine, right? So yeah,

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what else does it do
for you in the morning?

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It goes and grabs everything out of
my calendar and displays that for me.

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And then it pulls top, I don’t know,

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five headlines off of several
sources about things that I’m

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interested in and pulls them
in and gets my news and stuff.

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But not that this is
tremendously groundbreaking.

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What it is is it’s a routine. It’s
something that I told, do this, then this,

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then this, then this and this, right?
And it just writes it into a skill file,

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sits it into my clog brain there.
And then anytime I say good morning.

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So the same deal with my newsletter.
So I write a newsletter each week.

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It’s quite involved. It
has several parts to it.

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And I used to have to have like 15
GPTs going and like different deep

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research prompts that I had to keep
copying and paste. Instead now,

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once I ran through the process
one time, the way I wanted it,

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I just said, “Create skills for that.
Create skills that format this into this,

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create skills that do this deep research.”
And so now it’s just more or less

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like, “Hey, I’m building the
newsletter.” It’s like, cool,

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where do you want to start? And
it’s like, let’s start with this.

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And it goes out and does the research.

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And the thing is you can spin up
multiple tasks at the same time.

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So it’s like it goes off, does the
deep research, open a new task,

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start something else up.
And the way Claude is built,

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the way Cloud cowork is built
is that it can work in parallel.

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So it does things a heck of a lot faster
than you would think it would be able

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00:14:01,369 –> 00:14:05,249
to do something because
it’ll spin up four, five,

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00:14:05,329 –> 00:14:10,009
six agents at the same time. Each one,
this might get a little technical,

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but each one has its own context
window. So in other words,

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this one’s out there doing this.
It’s literally like running

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five clouds at the same time. Right.

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00:14:20,929 –> 00:14:21,889
Which this is actually important.

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So let’s talk about Context
Window a little bit,

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00:14:23,520 –> 00:14:26,909
because I first heard about this on
the Andrew Ferris podcast recently,

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but what I think a lot of people don’t
know is if you give Claude a really big

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file or maybe like a transcript
from a really long call,

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00:14:35,449 –> 00:14:38,589
it’s not necessarily
crawling all of that, right?

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00:14:38,789 –> 00:14:42,089
It’s maybe looking at the end and the
beginning and maybe summarizing some

230
00:14:42,109 –> 00:14:42,942
things.

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And if you give Claude a whole bunch
of stuff like all in one prompt or

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something,

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00:14:49,549 –> 00:14:54,509
it’s going to take shortcuts potentially
instead, But having multiple agents,

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00:14:54,569 –> 00:14:58,930
you can have a lot more context
that you’re feeding the AI.

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00:14:59,790 –> 00:15:03,010
Hey, thanks again for tuning in. This
episode’s brought to you by OMG Commerce.

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00:15:03,150 –> 00:15:04,930
That’s my agency. Hey,

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00:15:05,070 –> 00:15:08,970
we’re specialists at creating
omnichannel growth for brands

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00:15:09,530 –> 00:15:14,490
profitably. Now, the greatest brands
we know are no longer just D2C.

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00:15:15,350 –> 00:15:16,550
Yes, they’re masters of D2C,

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00:15:16,670 –> 00:15:20,710
but they’re also growing and scaling
on marketplaces and in retail stores.

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00:15:20,890 –> 00:15:25,750
And we understand the complexities of
how to grow in all of those channels from

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00:15:25,790 –> 00:15:30,210
a campaign strategy, a creative strategy,
and a measurement strategy. In fact,

243
00:15:30,270 –> 00:15:34,890
we recently won a Google Agency Excellence
Award for helping Arctic coolers

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00:15:35,090 –> 00:15:39,490
grow their retail sales
in Walmart using YouTube.

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00:15:40,110 –> 00:15:45,090
We’ve helped add almost eight
figures in growth on Amazon for

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00:15:45,130 –> 00:15:50,010
brands, and we’ve even helped a
brand go from nine to 10 figures.

247
00:15:50,070 –> 00:15:52,690
And so we want to help you grow.

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00:15:53,090 –> 00:15:55,890
So if you’re not satisfied with your
growth in any of those channels or you’re

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00:15:55,910 –> 00:15:58,770
looking to unlock new growth,
we should probably chat.

250
00:15:59,290 –> 00:16:02,850
Visit us at omgcommerce.com.
Click that Let’s Talk button.

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00:16:03,470 –> 00:16:08,210
We love to schedule a strategy session
with you. With that, back to the show.

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00:16:09,090 –> 00:16:13,590
Yeah. And the thing is, right
now we have Opus 4.6. We’ve got

253
00:16:15,330 –> 00:16:18,870
Gemini three or whatever. We’ve
got … These models are all very,

254
00:16:18,930 –> 00:16:19,763
very intelligent,

255
00:16:20,210 –> 00:16:23,890
but CloudCowork really isn’t a
breakthrough in intelligence as much as a

256
00:16:23,990 –> 00:16:27,070
breakthrough in sort of
architecture of how the tool works.

257
00:16:28,590 –> 00:16:32,291
It’s not that the tool is
that much smarter, although
it’s a little bit smarter.

258
00:16:32,371 –> 00:16:36,911
These tools get incrementally
smarter every couple of months.

259
00:16:37,231 –> 00:16:42,151
They release something that’s smarter,
but it’s the UI that’s different,

260
00:16:42,211 –> 00:16:42,451
right?

261
00:16:42,451 –> 00:16:47,311
And it’s sort of the what’s under the
hood that’s different about Claude

262
00:16:47,351 –> 00:16:48,871
Cowork. And it does take a little bit of

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00:16:50,751 –> 00:16:54,551
getting the hang of how it
works, but once you get going,

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it’s actually super good at kind
of walking you through like,

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00:17:00,071 –> 00:17:02,031
“Do you want me to do this?
Do you want me to do that?

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00:17:02,480 –> 00:17:04,851
” And so if you’re going to
play around with CloudCowork,

267
00:17:05,331 –> 00:17:09,891
I would just say start with a simple
use case and just start to type

268
00:17:10,471 –> 00:17:15,471
and watch it start to build something
out for you. It’s pretty amazing.

269
00:17:16,231 –> 00:17:20,011
The other thing that’s really interesting
about these skills is that they’re

270
00:17:20,031 –> 00:17:22,731
extremely shareable. So for example,

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00:17:23,091 –> 00:17:27,371
I’ve built out an entire workflow
around building my newsletter and in my

272
00:17:27,431 –> 00:17:31,271
membership, I’m just going to give
it to my people. So it’s like,

273
00:17:31,351 –> 00:17:32,211
here’s a zip file.

274
00:17:33,051 –> 00:17:37,831
It’s got all the skills in it and
all the context in it that it needs.

275
00:17:37,911 –> 00:17:40,371
And so just upload it, zip it, upload it,

276
00:17:41,251 –> 00:17:46,211
and now you have that
skill. So Pretty cool too,

277
00:17:47,431 –> 00:17:50,891
and there’s little marketplaces
springing up that are

278
00:17:51,991 –> 00:17:56,331
thousands of skills, like anything you
could think of that are already there,

279
00:17:56,392 –> 00:17:57,872
you just download the zip, Zip

280
00:17:59,692 –> 00:18:04,412
uploaded inside of Claude as a new
skill. And I think I’d be a little.

281
00:18:04,572 –> 00:18:08,852
Careful about that. It’d be good to
go with the song there. Yeah. Be a.

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00:18:08,932 –> 00:18:13,092
Little careful about downloading other
people’s skills because people do stupid

283
00:18:13,172 –> 00:18:17,552
stuff with the instructions
and stuff like that. But

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it’s a different way of

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00:18:24,612 –> 00:18:29,192
working with AI that I think OpenAI

286
00:18:29,792 –> 00:18:34,452
sort of dropped the ball with not
updating how custom GPTs work all this

287
00:18:34,512 –> 00:18:35,345
time.

288
00:18:36,172 –> 00:18:40,792
And now skills have come along and
cloud coworks come along and the two

289
00:18:40,812 –> 00:18:43,992
together, it’s a
combination that’s hard to.

290
00:18:44,032 –> 00:18:45,472
Beat. It’s a winning combo. Yeah.

291
00:18:45,532 –> 00:18:48,812
So a couple of things I want to unpack
and I’ll kind of talk through a little

292
00:18:48,832 –> 00:18:51,892
bit of what I did this weekend and where
I think this is going to unlock some

293
00:18:51,912 –> 00:18:56,052
pretty cool stuff for my agency.
You talked about connections.

294
00:18:56,252 –> 00:18:57,452
And so basically what I wanted to do,

295
00:18:57,912 –> 00:19:01,272
we got this very detailed financial
dashboard that’s got everything in there,

296
00:19:01,332 –> 00:19:03,892
client revenue, cost of employees,

297
00:19:03,952 –> 00:19:08,072
cost of various costs of
different service items.

298
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We kind of group our expenses
into delivery or all the team,

299
00:19:11,612 –> 00:19:15,152
all the tools that deliver
services into growth.

300
00:19:15,232 –> 00:19:19,712
So sales and marketing expenses and
tools and payroll and then ops, right?

301
00:19:20,012 –> 00:19:24,413
So all the tools and overhead and
employees and stuff that fit there.

302
00:19:25,333 –> 00:19:29,073
But I wanted to analyze some
things. And so this is kind of hard,

303
00:19:29,193 –> 00:19:32,873
like what do we dump into
what spreadsheet or whatever?

304
00:19:32,933 –> 00:19:35,173
And so basically I gave
Claude, I was like, “Hey,

305
00:19:35,873 –> 00:19:39,253
this is a framework that I want to
work within. Here’s some of our goals.

306
00:19:39,333 –> 00:19:42,593
Net revenue retention is a number we’re
going to start tracking regularly.” We

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00:19:42,733 –> 00:19:43,653
did this in the past,

308
00:19:44,113 –> 00:19:46,873
but the calculations are actually kind
of difficult and building that on a

309
00:19:47,053 –> 00:19:48,973
spreadsheet is also kind
of a pain of the butt.

310
00:19:49,033 –> 00:19:52,333
But basically that’s where you’re looking
at starting revenue for a beginning

311
00:19:52,393 –> 00:19:54,113
period of time. And so we just
take the beginning of the year,

312
00:19:54,473 –> 00:19:58,633
what’s our starting revenue?
Over time then minus any churn,

313
00:19:58,893 –> 00:20:02,653
so logo churn or clients
a churn minus contraction.

314
00:20:02,713 –> 00:20:04,873
So maybe a client didn’t
churn, but they reduced scope,

315
00:20:04,933 –> 00:20:06,013
so now they’re spending less.

316
00:20:06,893 –> 00:20:11,353
So it’s beginning revenue minus those
two things plus expansion, meaning, yeah,

317
00:20:11,413 –> 00:20:15,113
but some clients actually add the scope
and actually do more work with us.

318
00:20:15,213 –> 00:20:18,353
And so then what is that
that’s net revenue retention?

319
00:20:19,873 –> 00:20:23,373
Basically I started like, “Hey,
Claude, this is what I want to do.

320
00:20:23,383 –> 00:20:24,993
” Cloud cowork. It’s
like, “Oh, cool. Well,

321
00:20:25,053 –> 00:20:28,013
do you want me to connect with
QuickBooks so I can connect directly to

322
00:20:28,033 –> 00:20:28,866
QuickBooks?” I’m like, “Well,

323
00:20:29,040 –> 00:20:31,613
why don’t you just look at this Google
Sheet first?” And then it’s like, “Oh,

324
00:20:31,693 –> 00:20:35,313
this is a gold mine of information.” And
so then it starts spinning stuff out.

325
00:20:35,753 –> 00:20:38,853
And then I started talking about some of
the sales goals and stuff and looked at

326
00:20:38,873 –> 00:20:41,973
our sales pipeline and the sales goal
sheet that I put together and I started to

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00:20:42,013 –> 00:20:42,973
say, “Hey, this is good.

328
00:20:43,033 –> 00:20:47,673
Here’s where you maybe have
some weaknesses.” And so
spit out these different

329
00:20:47,693 –> 00:20:49,673
analyses and I’m like, “Holy crap,

330
00:20:49,833 –> 00:20:54,213
this is awesome.” And so right now I’ve
just got to looking at our Google Sheets

331
00:20:54,233 –> 00:20:59,214
because you can do the browser plugin
where it looks at the Google sheets and

332
00:20:59,234 –> 00:21:00,067
can read it,

333
00:21:00,494 –> 00:21:04,934
or you can upload a Min Excel file
or you can plug it into QuickBooks.

334
00:21:05,094 –> 00:21:08,614
So there’s different
ways you can run this.

335
00:21:08,834 –> 00:21:10,694
And so yeah,

336
00:21:10,774 –> 00:21:14,474
it’s going to be a real
unlock for financial insights

337
00:21:16,314 –> 00:21:19,994
because we don’t have a huge finance
team. And so it’s going to be very,

338
00:21:20,054 –> 00:21:20,887
very powerful. Yeah.

339
00:21:21,634 –> 00:21:22,467
Yeah. I mean,

340
00:21:23,080 –> 00:21:27,814
I think it’s a good bet
that every day that goes

341
00:21:27,894 –> 00:21:28,727
by,

342
00:21:30,074 –> 00:21:33,734
the people doing work at computers are
going to spend a little bit less time

343
00:21:34,014 –> 00:21:37,554
outside of an AI tool
than the day before. So

344
00:21:39,694 –> 00:21:43,934
as AI tools like Claude
Cowork keep developing

345
00:21:44,014 –> 00:21:48,474
connections to other outside tools and
they’ve already got that protocol in

346
00:21:48,534 –> 00:21:53,474
place called MCP and everybody’s pretty
much on board with it and starting to

347
00:21:53,554 –> 00:21:54,794
connect everything together,

348
00:21:55,814 –> 00:22:00,694
it’ll just become sort of a push
and pull type of a situation

349
00:22:00,714 –> 00:22:03,954
where I’m able to just
pull this from here.

350
00:22:04,574 –> 00:22:08,754
And the nice thing is that you got
this sort of central terminal with

351
00:22:08,794 –> 00:22:10,074
intelligence inside of it,

352
00:22:10,814 –> 00:22:15,754
and you can pull from disparate
sources and pull things together and

353
00:22:17,474 –> 00:22:22,294
either create new things or get
new analysis out of those connected

354
00:22:22,314 –> 00:22:24,955
things. And what it does is
it’s opening up things that

355
00:22:26,835 –> 00:22:31,655
you never would have had time
to do without these tools. So

356
00:22:35,815 –> 00:22:40,775
a small company now can do things
that large companies have been able to

357
00:22:40,815 –> 00:22:43,415
do for a long time because they
have a whole team of financial,

358
00:22:44,055 –> 00:22:44,888
you know what I’m saying?

359
00:22:46,200 –> 00:22:48,675
Yeah. Yeah. You have a
whole finance department.

360
00:22:48,815 –> 00:22:49,395
To go pull this out.

361
00:22:49,395 –> 00:22:52,695
A department there that’s running all
this analysis and doing all this stuff,

362
00:22:52,775 –> 00:22:53,608
but

363
00:22:54,815 –> 00:22:58,915
because they got to pull from all this
stuff and it takes like human effort to

364
00:22:59,215 –> 00:23:03,035
get through all that. But what
I would encourage you to do,

365
00:23:03,135 –> 00:23:04,575
and you probably did do,

366
00:23:04,795 –> 00:23:08,555
is as you’re working
through something manually,

367
00:23:09,535 –> 00:23:11,355
you can always pause
and stop and say, “Okay,

368
00:23:11,455 –> 00:23:15,195
I got this kind of how I
wanted it sort of manually,

369
00:23:15,335 –> 00:23:17,535
but even using the AI, so
it’s not completely manual,

370
00:23:17,595 –> 00:23:21,035
but you understand you’re just kind of
prompting through and you get to this

371
00:23:21,075 –> 00:23:22,195
sort of end state and you’re like,

372
00:23:22,295 –> 00:23:26,115
that’s what I wanted.” That’s when
it’s a good time to pause and reverse

373
00:23:26,155 –> 00:23:29,695
engineer into a skill or
even if you’re using ChatGPT,

374
00:23:29,855 –> 00:23:33,435
you reverse into a custom GPT, say,

375
00:23:34,415 –> 00:23:37,595
“I want you to take a look at everything
we did here in the end output and I

376
00:23:37,635 –> 00:23:42,395
want you to codify this and create
the instructions to get here

377
00:23:42,535 –> 00:23:47,355
like that. ” And the nice
thing about cowork is it knows

378
00:23:49,480 –> 00:23:50,280
if you said something like,

379
00:23:50,280 –> 00:23:54,456
“I want to run the financial analysis
again,” or give it some other kind of

380
00:23:54,536 –> 00:23:57,036
name, it’ll know to go grab that skill-.

381
00:23:57,336 –> 00:23:57,880
Shows what to do.

382
00:23:57,880 –> 00:23:59,556
… and then it has a lot more autonomy.

383
00:24:00,236 –> 00:24:04,976
It’ll go and run several steps up ahead
and it might hit a point where it’s

384
00:24:04,996 –> 00:24:09,816
like, I need some input back from Brett,
and so it’s going to come back and say,

385
00:24:10,276 –> 00:24:13,996
“Do you want me to do this this way?”
And you just select that and sometimes

386
00:24:14,036 –> 00:24:17,236
it’ll write that into the skill
so it doesn’t need to ask again.

387
00:24:17,296 –> 00:24:20,856
And so it’s really quite
intuitive in that way.

388
00:24:20,976 –> 00:24:25,716
And it’s just a massive step
change from what we’re used to with

389
00:24:25,796 –> 00:24:27,016
regular just chatbots.

390
00:24:27,516 –> 00:24:32,256
Totally. And then I want to get your
take on OpenClaw in a second as well,

391
00:24:32,316 –> 00:24:33,256
and then a few other things.

392
00:24:33,336 –> 00:24:38,076
But you also said something that
because tools like Cowork and

393
00:24:38,176 –> 00:24:42,736
there’ll be others, I’m sure,
they’ll connect to almost anything.

394
00:24:42,836 –> 00:24:43,456
And over time,

395
00:24:43,456 –> 00:24:46,416
they’re going to connect to basically
every piece of SaaS you use,

396
00:24:46,476 –> 00:24:47,556
every other piece of tool, whatever.

397
00:24:48,436 –> 00:24:53,116
There is a realistic future where
most of the interaction we have

398
00:24:53,716 –> 00:24:58,716
on our desktops or on our phones is
with an AI and it’s the one connecting

399
00:24:58,756 –> 00:25:03,536
to all the tools and pulling things
together, doing what we want it to do.

400
00:25:05,016 –> 00:25:06,976
And so yeah, just really,
really fascinating.

401
00:25:07,636 –> 00:25:10,476
What’s your take on OpenClaude for
those that have been following the news?

402
00:25:10,736 –> 00:25:14,116
There’s a tool that’s had what, like
three or five names in the last week.

403
00:25:14,176 –> 00:25:17,816
It was Claude, C-L-A-W-D,
bot. Then Claude,

404
00:25:17,896 –> 00:25:19,296
who we’ve been talking about
was like, “Don’t do that.

405
00:25:19,356 –> 00:25:22,956
That sounds just like our name.” And
then it was Molt bot and then now I think

406
00:25:22,976 –> 00:25:24,636
they landed on OpenClaw.

407
00:25:24,736 –> 00:25:26,416
Who knows by someone else to
this maybe something different,

408
00:25:26,600 –> 00:25:29,677
but what’s your take on that?
Because that has been wild.

409
00:25:30,517 –> 00:25:32,877
It’s been such a big deal.

410
00:25:32,977 –> 00:25:37,837
Even my 23-year-old son
who’s in the roofing business

411
00:25:38,017 –> 00:25:39,757
in sales, he bought

412
00:25:42,317 –> 00:25:43,817
an Apple Mac Pro or whatever,

413
00:25:46,000 –> 00:25:50,017
a Mac Pro and he’s running it on a local
machine and it’s doing some business

414
00:25:50,397 –> 00:25:53,357
development stuff for him. But
what’s your take on OpenClaw?

415
00:25:54,677 –> 00:25:55,817
Where is this taking us?

416
00:25:57,077 –> 00:25:59,557
Well, for the people listening to this,
I would probably be listening to this,

417
00:25:59,617 –> 00:26:01,397
right? I mean, the person who’s

418
00:26:03,117 –> 00:26:07,917
hardcore and you want pure control
and you want all that stuff,

419
00:26:07,977 –> 00:26:10,617
you’re probably not
listening to this show.

420
00:26:12,657 –> 00:26:16,017
But if you’re a normal business person,

421
00:26:16,297 –> 00:26:19,717
you’re running a company or
you’re in marketing or whatever,

422
00:26:19,917 –> 00:26:24,677
I think that there are essentially
sort of four steps here

423
00:26:25,057 –> 00:26:28,937
that we can think about. So
you’ve got your sort of chatbot.

424
00:26:29,177 –> 00:26:32,437
So regular ChatGPT 5.2 or whatever,

425
00:26:32,997 –> 00:26:37,677
regular Claude still available,
that’s level one, right?

426
00:26:38,077 –> 00:26:42,657
Level two would be to kick up the cowork.
And I think by the end of this year,

427
00:26:43,057 –> 00:26:46,537
everybody will be in the
working knowledge workspace,

428
00:26:47,297 –> 00:26:50,137
working on a computer, you’ll be
working in something like cowork.

429
00:26:50,197 –> 00:26:53,037
It may not be cloud cowork, but
it’d be something like it. Yeah.

430
00:26:53,217 –> 00:26:57,398
Google’s version of it or
OpenAIs, version or whatever.

431
00:26:58,358 –> 00:27:02,378
Then the third level would be something
like ClaudeCode or over at OpenAI,

432
00:27:02,458 –> 00:27:05,298
it’s called Codex, where you’re
going straight to the tap,

433
00:27:05,878 –> 00:27:10,858
you’re kicking past any
sort of UI user interface

434
00:27:11,018 –> 00:27:15,278
and you’re just going
straight to the source. And

435
00:27:17,338 –> 00:27:20,378
you’re already starting to get into
pretty hardcore when you’re doing that

436
00:27:20,398 –> 00:27:23,018
because you’re working in terminal and

437
00:27:24,738 –> 00:27:25,798
you’re having to use

438
00:27:27,738 –> 00:27:32,438
some coding languages and stuff
like that, but it’s doable.

439
00:27:32,818 –> 00:27:34,098
If you really committed to it-.

440
00:27:34,498 –> 00:27:36,278
It’s vibe coding, right? So I mean,

441
00:27:36,618 –> 00:27:39,518
you don’t have to have a ton of
programming knowledge, but maybe some,

442
00:27:39,718 –> 00:27:42,218
or you’re understanding
prompts in a different way.

443
00:27:43,178 –> 00:27:47,458
Could the average person just jump into
Claude code or something similar or

444
00:27:47,598 –> 00:27:48,838
that’s going to take a little bit of.

445
00:27:48,858 –> 00:27:50,058
Work? Yeah, I think you could.

446
00:27:50,278 –> 00:27:53,978
It would be a longer learning
curve than Claude Cowork.

447
00:27:54,218 –> 00:27:56,298
Because what Cloud cowork is,

448
00:27:56,778 –> 00:28:00,838
is it’s Claude code with a UI
sitting on top of it. Yeah, I got it.

449
00:28:01,058 –> 00:28:05,478
And what happens when you do that
is it puts some restrictions on you.

450
00:28:06,660 –> 00:28:10,558
You’re not going straight to the source
where it’s just like you can do anything

451
00:28:10,598 –> 00:28:11,431
in here

452
00:28:12,798 –> 00:28:16,398
because you’ve got the restrictions of
that sort of harness that’s sitting over

453
00:28:16,418 –> 00:28:17,898
the top of Claude cohort.

454
00:28:18,938 –> 00:28:22,419
So going straight to Claude
code is like level three.

455
00:28:22,478 –> 00:28:26,259
And then you get into the open
source stuff where your son

456
00:28:28,019 –> 00:28:31,799
wants to buy an extra computer
because he doesn’t want that

457
00:28:33,359 –> 00:28:34,192
open source

458
00:28:36,359 –> 00:28:40,779
sort of no guardrails AI
to be on his own machine,

459
00:28:41,099 –> 00:28:41,999
you want to create a.

460
00:28:42,119 –> 00:28:43,879
Combined space. We’re
pointing into his email.

461
00:28:43,979 –> 00:28:46,939
He’s creating a separate email and a
separate browser and a separate machine,

462
00:28:47,739 –> 00:28:48,659
but- Yeah, people are.

463
00:28:49,439 –> 00:28:52,600
Daisy chaining 10, 200

464
00:28:54,759 –> 00:28:59,719
Macs together and creating armies
of employees that don’t exist

465
00:28:59,959 –> 00:29:01,859
with Slack accounts and

466
00:29:03,719 –> 00:29:08,019
email accounts and all these things.
I would say the average person,

467
00:29:08,779 –> 00:29:11,059
level four is, forget about it.

468
00:29:13,119 –> 00:29:17,719
It’s so powerful and it really is.
It’s not that it’s not powerful,

469
00:29:17,779 –> 00:29:21,079
but it’s precisely because
it’s so powerful that you
shouldn’t rush to install

470
00:29:21,119 –> 00:29:21,952
it.

471
00:29:22,779 –> 00:29:27,299
Just pump the brakes a minute because
what’s going to happen is some

472
00:29:30,059 –> 00:29:33,519
more secure company is
going to release something.

473
00:29:33,579 –> 00:29:38,119
And Claude Code is already just insanely
powerful if you just go straight to

474
00:29:38,199 –> 00:29:42,699
Claude code and you still have
a lot of guardrails there.

475
00:29:43,619 –> 00:29:44,339
The thing that I would.

476
00:29:44,339 –> 00:29:47,459
Point out though- There’s all kinds of
unlocks, all kinds of stuff you can do,

477
00:29:47,639 –> 00:29:51,139
a whole world open up to you in those
levels one through three that you don’t

478
00:29:51,159 –> 00:29:54,959
need, or one through four, you
don’t need to go open claw just yet.

479
00:29:56,300 –> 00:29:57,133
And I think

480
00:29:58,680 –> 00:30:03,500
cowork will be The place where
most business people will park

481
00:30:03,580 –> 00:30:07,200
it and say, “Wow, this is quite a.

482
00:30:07,320 –> 00:30:11,500
Lot of power.” And just so you
know, we’re not sponsored by Claude.

483
00:30:11,840 –> 00:30:14,740
We get no kickback from co-work.
We’re just like, this is awesome.

484
00:30:15,020 –> 00:30:18,460
We’re geeking out about it using
it. And so it’s phenomenal. Yeah.

485
00:30:18,660 –> 00:30:20,160
The one thing I wanted
to point out though,

486
00:30:20,280 –> 00:30:23,640
the other comment about
OpenClaw that it raised is that,

487
00:30:25,040 –> 00:30:29,920
so in the summer I started to
realize I was doing so much

488
00:30:30,520 –> 00:30:35,360
hefty work with AI tools
and running Zoom and

489
00:30:35,560 –> 00:30:38,900
other things that my laptop was a beast,

490
00:30:39,020 –> 00:30:41,200
but it wasn’t able to keep up. And

491
00:30:42,880 –> 00:30:47,320
I do think that we as business people
need to be thinking about our own

492
00:30:47,780 –> 00:30:51,220
tech the way that a lab thinks
about how many GPUs they have.

493
00:30:53,180 –> 00:30:57,620
Starting to think about what is the
processing power of your company,

494
00:30:58,400 –> 00:31:00,200
of any individual in your company.

495
00:31:01,360 –> 00:31:06,340
So I went ahead and bought
a pretty hefty Mac Mini

496
00:31:06,800 –> 00:31:08,440
because I was like,

497
00:31:09,660 –> 00:31:12,600
“I don’t want to be constricted by

498
00:31:14,740 –> 00:31:19,441
my computer.” So that’s kind of
interesting that you start to think about

499
00:31:20,261 –> 00:31:21,681
your own … I mean,

500
00:31:21,741 –> 00:31:23,981
you always think about you don’t want
your computer to be slowing you down,

501
00:31:24,120 –> 00:31:24,953
but at this point,

502
00:31:25,081 –> 00:31:29,521
it’s sort of like you’re going
to see Apple just pick up a

503
00:31:29,661 –> 00:31:32,081
giant windfall from like- Yeah. Well.

504
00:31:32,201 –> 00:31:36,481
Their stock is already up just because
so many people are buying Mac Minis.

505
00:31:36,920 –> 00:31:38,321
Yeah. All the hardware that’s needed.

506
00:31:38,601 –> 00:31:43,001
That Apple silicon is what
everybody’s after. Yeah,

507
00:31:43,281 –> 00:31:44,601
it’s wild to think about

508
00:31:46,101 –> 00:31:51,041
somebody like your son who’s young
and starting out in a business,

509
00:31:52,021 –> 00:31:55,501
having essentially desks
with nobody sitting at them,

510
00:31:55,641 –> 00:31:57,281
but there’s people working.

511
00:31:57,761 –> 00:32:01,381
And he just ended up, he’s in
roofing sales and so he’s like, “Dad,

512
00:32:01,521 –> 00:32:04,401
I’m going to reach out to all these
insurance agents and I want to get them an

513
00:32:04,441 –> 00:32:06,341
email here and then I’m going to drop
by their office and get them donuts.

514
00:32:06,600 –> 00:32:07,400
I’m going to do these things.

515
00:32:07,400 –> 00:32:12,201
And then I want this to be able to respond
via email over here and pull together

516
00:32:12,221 –> 00:32:15,301
my calendar and I’ve got these Notion
apps.” I’m like, “Love it. ” I’m like,

517
00:32:15,441 –> 00:32:16,274
“This is awesome.

518
00:32:16,461 –> 00:32:20,521
This is great.” And also I’m glad you’re
doing it on that machine because I’m

519
00:32:20,581 –> 00:32:24,881
not ready for Open Claw, not for
OMG. Heck no. But I want to see it.

520
00:32:25,141 –> 00:32:29,021
And yeah, I’m all in on
coworking and figuring that out.

521
00:32:29,081 –> 00:32:31,541
And so one quick thing though,

522
00:32:34,982 –> 00:32:35,815
using AI,

523
00:32:36,042 –> 00:32:40,362
still the ROI can be amazing
and it’s low cost compared to

524
00:32:41,042 –> 00:32:42,862
what it should be based
on the power of the tool.

525
00:32:42,922 –> 00:32:46,582
But we start using CoWork
or OpenCall or whatever,

526
00:32:47,122 –> 00:32:50,402
you can start to, you’re
spending more on these tools.

527
00:32:50,522 –> 00:32:53,882
This is not necessarily the $20
a month subscription, right?

528
00:32:54,282 –> 00:32:57,282
What are you seeing since
you’re leaning hard into cowork?

529
00:32:57,982 –> 00:33:00,782
What has that done to your monthly fees
and your usage and what kind of plans do

530
00:33:00,802 –> 00:33:02,382
you have to be on to make this work?

531
00:33:03,222 –> 00:33:07,422
Well, I use the $100 a
month max plan, but the fact

532
00:33:09,702 –> 00:33:13,022
they do have cowork now
available at that $20 a month,

533
00:33:13,662 –> 00:33:16,642
you probably will find
that heavy users of it.

534
00:33:17,560 –> 00:33:22,102
They’re going to need that
$100 a month plan. But I think

535
00:33:25,142 –> 00:33:29,722
if it’s being used right, it’s just
a no-brainer for 100 bucks a month.

536
00:33:30,480 –> 00:33:32,362
A month for an assistant.
Okay. Yeah, plus.

537
00:33:32,680 –> 00:33:36,562
Yeah. I think that with the proper
setup and structure … See,

538
00:33:37,842 –> 00:33:40,922
I’ve always said that these
AI tools are extremely

539
00:33:43,182 –> 00:33:43,762
useful,

540
00:33:43,762 –> 00:33:48,742
but even going back to my last time
on this show where I was talking so

541
00:33:48,802 –> 00:33:50,583
much about context,

542
00:33:51,323 –> 00:33:56,323
And I mentioned that a little bit today
about how if you’re not giving it any

543
00:33:56,423 –> 00:33:58,103
context about your offer, your persona,

544
00:33:58,843 –> 00:34:01,163
don’t be surprised if you’re just
not getting anything out of it.

545
00:34:01,923 –> 00:34:05,343
And that sort of blows up when you
start to think about how something like

546
00:34:05,743 –> 00:34:10,683
Cowork can access really any context when

547
00:34:10,723 –> 00:34:14,903
it thinks it needs it and it can find
it. It can find it in your machine.

548
00:34:15,323 –> 00:34:18,223
So when you go back to your
example around the finances,

549
00:34:18,383 –> 00:34:23,243
when you talked about your sales goals
and all these different documents,

550
00:34:23,303 –> 00:34:26,423
I know how organized you guys
are at OMG. It’s impressive.

551
00:34:26,983 –> 00:34:31,383
And you guys document a lot of things
and you have goals and you have rocks and

552
00:34:31,403 –> 00:34:34,323
you have quarterly and yearly
plans and all that stuff.

553
00:34:35,083 –> 00:34:39,963
And that kind of stuff all can be
brought into your Claude cowork space.

554
00:34:40,840 –> 00:34:45,363
And the way to do this, honestly,

555
00:34:45,563 –> 00:34:48,463
is when you’re playing with it, is to ask.

556
00:34:49,163 –> 00:34:52,963
Take something like a
quarterly plan or something,

557
00:34:53,163 –> 00:34:57,983
drop it in and say,
“Here’s the quarterly plan,

558
00:34:59,183 –> 00:35:02,443
where do you think this should be
most properly structured inside.

559
00:35:02,503 –> 00:35:03,023
Of.

560
00:35:03,023 –> 00:35:04,503
Claude?” And

561
00:35:06,663 –> 00:35:09,924
before you go and decide where
it goes and where to put it,

562
00:35:10,644 –> 00:35:15,564
ask it to think it through. So to go
analyze that file and start to connect it,

563
00:35:15,624 –> 00:35:19,984
well, and I see this skill over here
where you run a financial analysis,

564
00:35:20,104 –> 00:35:21,184
I see this skill here,

565
00:35:21,904 –> 00:35:25,024
and maybe the best thing would be to
organize it this way and it’ll ask you,

566
00:35:25,144 –> 00:35:25,977
“Does that sound good?”.

567
00:35:26,324 –> 00:35:26,924
Yeah.

568
00:35:26,924 –> 00:35:28,554
And it starts to build out …

569
00:35:29,684 –> 00:35:34,224
There’s a file at the very
central core of Claude called the

570
00:35:34,304 –> 00:35:37,864
Claude MD file, claude.mdfile,
which is basically,

571
00:35:38,744 –> 00:35:42,524
you could put anything in there, but
what you do is you just tell Claude,

572
00:35:43,684 –> 00:35:47,504
keep updating that Claude MD file
because what it’s doing is it’s telling

573
00:35:47,544 –> 00:35:51,864
Claude, how does this structure
work? It’s sort of like

574
00:35:53,760 –> 00:35:58,544
a central plan as to how
Claude is supposed to

575
00:35:58,604 –> 00:35:59,640
interact with your …

576
00:36:00,024 –> 00:36:03,684
So anytime you use Claude and it can,

577
00:36:03,744 –> 00:36:06,344
it will access that claud.md file. So

578
00:36:09,224 –> 00:36:13,504
that’s the thing is that
the more you give it, and

579
00:36:15,464 –> 00:36:19,184
there’s definitely an unreasonable
amount of stuff you could give it,

580
00:36:19,264 –> 00:36:21,344
but things like that, it’s like, “Well,

581
00:36:21,404 –> 00:36:25,765
that’s really something that I consult
my own brain when I work on my finances.”

582
00:36:26,305 –> 00:36:27,138
You might consider,

583
00:36:27,185 –> 00:36:32,085
should I drop this into the Claude Cowork
space so that it has access to that?

584
00:36:33,005 –> 00:36:35,085
And you should be shocked at like, wow,

585
00:36:35,785 –> 00:36:39,785
it realized it needed to go look at
that and then go grab the skill and then

586
00:36:40,625 –> 00:36:44,365
connect over here to HubSpot and then
… You know what I mean? Right, right.

587
00:36:44,425 –> 00:36:44,685
And.

588
00:36:44,685 –> 00:36:48,665
That’s what I mean when I say
agentic, right? So agentic.

589
00:36:49,285 –> 00:36:50,445
It’s amazing. Let’s do this.

590
00:36:50,525 –> 00:36:54,085
I know you talked about a couple workflows
that you built for content creation,

591
00:36:54,145 –> 00:36:56,005
and I think this maybe is
around your newsletter,

592
00:36:56,080 –> 00:36:57,120
but do you want to actually share that?

593
00:36:57,280 –> 00:37:00,640
We had to talk through it for those
people that are just listening and not

594
00:37:00,680 –> 00:37:04,120
watching, but would that be
worthwhile to kind of dig into? Yeah.

595
00:37:05,720 –> 00:37:08,440
I’m curious while you’re doing
that, are you using Gemini at all?

596
00:37:08,600 –> 00:37:11,280
And are you leaning into
Gemini gems or Gemini as a.

597
00:37:11,360 –> 00:37:14,080
Tool? Yeah. Yeah. So I use Gemini

598
00:37:17,760 –> 00:37:19,800
almost purely for image generation. Oh.

599
00:37:19,880 –> 00:37:20,713
Nice.

600
00:37:20,760 –> 00:37:21,040
Yeah.

601
00:37:21,040 –> 00:37:21,800
A banana.

602
00:37:21,800 –> 00:37:26,400
That nano banana model is still-
It’s pretty insane. … the thing.

603
00:37:27,680 –> 00:37:31,000
But yeah, let me run
through this workflow.

604
00:37:31,120 –> 00:37:33,640
Maybe it’d be helpful to a
lot of people to see how …

605
00:37:34,720 –> 00:37:36,640
Is that going full screen for you? Yeah.

606
00:37:37,120 –> 00:37:40,160
Totally see it. Yep. So it’s full
screen. So for those watching on YouTube,

607
00:37:40,240 –> 00:37:41,480
they’ll see it. For those listening,

608
00:37:41,600 –> 00:37:44,960
we’ll do our best to describe it and
make it come to life in your mind’s eye.

609
00:37:45,360 –> 00:37:46,193
Yeah.

610
00:37:46,400 –> 00:37:47,233
Well.

611
00:37:48,040 –> 00:37:50,760
So this is really about

612
00:37:52,360 –> 00:37:56,680
creating any content or copy
of any kind. It could be

613
00:37:58,480 –> 00:38:03,360
text, images, video, audio.
Any kind of content is …

614
00:38:03,920 –> 00:38:06,280
I started to realize, as you know,

615
00:38:07,240 –> 00:38:11,440
if I had to be pegged to any one
digital marketing discipline,

616
00:38:11,560 –> 00:38:12,920
it would probably be content marketing.

617
00:38:13,440 –> 00:38:17,920
And it’s the biggest reason why I hopped
on AI so fast because I saw it creating

618
00:38:18,120 –> 00:38:22,520
content and I was like, wow, this
thing can actually create things. So

619
00:38:24,480 –> 00:38:26,640
as the years have gone
by, I mean using this,

620
00:38:27,200 –> 00:38:31,400
I’m getting better and better and
better at creating content and copy

621
00:38:32,280 –> 00:38:34,600
with AI tools.

622
00:38:34,960 –> 00:38:38,880
And I started to realize there’s
this underlying process that

623
00:38:40,040 –> 00:38:44,880
constantly gets used over and over and
over again, and it’s really this source,

624
00:38:45,440 –> 00:38:48,000
structure, format,
polished, sort of steps.

625
00:38:48,920 –> 00:38:51,760
And the way it works is that
the first step is the source.

626
00:38:52,320 –> 00:38:56,640
So if I’m going to create a piece of
copy, like a sales page, an email, an ad,

627
00:38:59,040 –> 00:39:02,080
or a content like a video or
anything, it doesn’t matter.

628
00:39:02,600 –> 00:39:04,320
There’s got to be some source.

629
00:39:05,640 –> 00:39:10,160
And most people that are failing with
content creation, copy creation with AI,

630
00:39:10,920 –> 00:39:13,960
they start with the AI and
they start to say, “Well,

631
00:39:14,000 –> 00:39:18,160
come up with the idea and then write
the idea or come up with the idea.” And

632
00:39:20,507 –> 00:39:24,527
so it’s like, well, where
are you in this scenario?

633
00:39:24,807 –> 00:39:29,667
Where is your voice? Where
is your brand? Where are you?

634
00:39:30,867 –> 00:39:31,700
And so

635
00:39:33,647 –> 00:39:38,107
when we think about setting up any
sort of workflow to create something,

636
00:39:38,467 –> 00:39:40,007
the first step is to figure out, well,

637
00:39:40,067 –> 00:39:42,327
where am I going to get
this source material from?

638
00:39:43,167 –> 00:39:46,307
And that source material can either
come from you, in other words,

639
00:39:46,387 –> 00:39:49,827
your brain or you’re from
internally in your organization,

640
00:39:49,887 –> 00:39:54,087
or it could come from outside.
It’s the same as before, before AI.

641
00:39:54,587 –> 00:39:55,087
Yep.

642
00:39:55,087 –> 00:39:57,827
So from a standpoint of you,

643
00:39:59,547 –> 00:40:03,547
you might rant into
your phone or something,

644
00:40:03,607 –> 00:40:07,267
some idea that you have, or you might,

645
00:40:07,747 –> 00:40:10,427
maybe you do podcast interviews
like this one, right?

646
00:40:11,147 –> 00:40:15,648
Or maybe you shoot videos
or maybe you do webinars

647
00:40:16,668 –> 00:40:20,118
or you write or something.
There needs to be …

648
00:40:20,208 –> 00:40:22,828
So if it’s going to come
from you, at some point,

649
00:40:23,168 –> 00:40:27,128
some ideas got to come out of your
brain and essentially your mouth.

650
00:40:28,608 –> 00:40:31,628
If it’s going to come from
elsewhere, that’s great too.

651
00:40:31,708 –> 00:40:35,238
You can go and grab source
material from all over the …

652
00:40:35,488 –> 00:40:39,348
I’ve said many times that the web
doesn’t necessarily need more content.

653
00:40:40,348 –> 00:40:45,108
There is a great service to be
done in curation of content, right?

654
00:40:45,488 –> 00:40:48,548
Like this is good. I read 10 articles.
Here’s the one you should read.

655
00:40:49,768 –> 00:40:53,108
And so you can go and
curate from elsewhere,

656
00:40:53,168 –> 00:40:57,628
but you’ve got to have something
that the AI is starting with. Now,

657
00:40:57,748 –> 00:41:00,588
step two is to structure
that in some way. So

658
00:41:02,688 –> 00:41:05,388
the fact is, if you go and
rant into your phone an idea,

659
00:41:05,648 –> 00:41:08,588
that’s a great way to create a source,

660
00:41:09,488 –> 00:41:13,028
but it’s not in any
structure that you can do.

661
00:41:13,048 –> 00:41:17,888
Something- Not usable, not valuable,
not shareable really. It’s just brain.

662
00:41:17,948 –> 00:41:21,698
Dog. Yeah. So typically a
workflow might look like …

663
00:41:23,148 –> 00:41:27,428
First I get this raw input, let’s
say it’s a rant into the phone,

664
00:41:27,548 –> 00:41:31,688
and then I take that and I put
some kind of structure around it.

665
00:41:33,009 –> 00:41:37,549
The two best ones, in my opinion,
are a set of bullets or into a table.

666
00:41:38,569 –> 00:41:42,609
And so you just tell the
AI, “Hey, take this input,

667
00:41:43,329 –> 00:41:47,929
whether it’s a rant, a transcript,
somebody else’s YouTube video,

668
00:41:48,049 –> 00:41:50,109
somebody else’s article, it
doesn’t matter if it came from you,

669
00:41:50,169 –> 00:41:54,149
but it’s got to have a source and
then take that and organize it in this

670
00:41:54,229 –> 00:41:57,229
structure.” And that’s a
second pass with an AI.

671
00:41:57,769 –> 00:42:02,769
So the first pass is
ingest this or go get this

672
00:42:03,509 –> 00:42:06,269
source. The second pass with the AI is,

673
00:42:06,589 –> 00:42:09,449
now organize it in some structured format.

674
00:42:10,529 –> 00:42:14,609
Then the third is to
literally format thing into

675
00:42:15,469 –> 00:42:18,749
whatever structure you
want, that piece of content,

676
00:42:18,809 –> 00:42:20,329
whatever’s going to
come out the other side.

677
00:42:20,829 –> 00:42:25,609
So if I have a rant into a phone
that’s just me rambling and rambling,

678
00:42:25,669 –> 00:42:30,329
rambling as I’m driving up to the gym
or something and I save that and then I

679
00:42:30,409 –> 00:42:31,209
drop it into the A.

680
00:42:31,209 –> 00:42:35,869
The first pass is to ingest
it and then take it and

681
00:42:36,629 –> 00:42:39,009
organize it into a table
or into a set of bullets.

682
00:42:39,209 –> 00:42:40,549
And then the third pass might be,

683
00:42:41,049 –> 00:42:45,429
“And here’s how to take that and
organize it into a LinkedIn post

684
00:42:46,029 –> 00:42:50,470
for me. ” That’s a third pass
with an AI. So it’s not one pass.

685
00:42:53,650 –> 00:42:57,290
It needs separate instructions
at each step along the way.

686
00:42:57,970 –> 00:43:02,430
And then that last step is to polish.
So bring it up to publish quality,

687
00:43:02,490 –> 00:43:07,490
and that could be a
combination of you and the AI,

688
00:43:07,550 –> 00:43:08,383
or it could be just you,

689
00:43:08,450 –> 00:43:12,350
or it could be just AI for those of us
that are wanting to automate our lives

690
00:43:12,410 –> 00:43:17,230
completely away and just are publishing
things to LinkedIn and elsewhere that

691
00:43:17,230 –> 00:43:17,850
…

692
00:43:17,850 –> 00:43:22,750
But I have found that this structure
reoccurs no matter what I’m

693
00:43:22,830 –> 00:43:25,450
building, is that I need to figure
out where’s the content coming from,

694
00:43:25,670 –> 00:43:29,150
where’s the idea? How do I
organize it in a way that’s useful?

695
00:43:29,710 –> 00:43:32,340
How do I then transform
it into whatever …

696
00:43:32,930 –> 00:43:36,150
Do I want a script to come out
of that? Well, that’s fine.

697
00:43:36,610 –> 00:43:39,610
Do I want a written post?
Do I want a cartoon?

698
00:43:40,370 –> 00:43:43,850
Do I want a slide for a
presentation or a set of slides?

699
00:43:44,610 –> 00:43:47,370
Anything is possible. I take the source,

700
00:43:47,490 –> 00:43:49,730
I give it some structure to
organize it so I can look at it.

701
00:43:50,350 –> 00:43:53,170
Oftentimes there’s some curation
that happens here, by the way.

702
00:43:53,730 –> 00:43:58,720
You get it into a table and you’re
like, just take ideas three, 10, and 12,

703
00:44:00,150 –> 00:44:04,991
and then move it on to step three,
which is, how do I take this? I mean,

704
00:44:05,071 –> 00:44:09,631
you almost think about this just a set
of rules that you keep moving things

705
00:44:09,711 –> 00:44:10,544
through.

706
00:44:10,751 –> 00:44:15,671
And then that last step could be
add a brand voice to it using AI

707
00:44:15,791 –> 00:44:20,391
or do like we have always done. Type.

708
00:44:22,151 –> 00:44:22,671
Actually.

709
00:44:22,671 –> 00:44:25,371
Edit the thing. Wait a minute.
We’re in there typing and editing.

710
00:44:26,191 –> 00:44:29,631
What’s up with that? What is this?
So what does this look like then?

711
00:44:30,211 –> 00:44:34,751
Is this maybe a four step process just
inside of our favorite chat interface?

712
00:44:35,791 –> 00:44:38,031
Are we pulling something together
that’s a little more agentic?

713
00:44:38,831 –> 00:44:39,931
What are you recommending here?

714
00:44:39,991 –> 00:44:44,291
Well, and that’s going to depend
on the tool and the actual process,

715
00:44:44,371 –> 00:44:47,871
but take a look at this. This is just
how I put my newsletter together here. So

716
00:44:49,851 –> 00:44:51,831
the step one is deep research.

717
00:44:51,911 –> 00:44:55,431
That’s a great place to go get a
whole bunch of source material.

718
00:44:55,771 –> 00:44:59,831
So you tell an AI, “Hey, I want you to
go out there.” This is for a newsletter,

719
00:45:00,251 –> 00:45:01,084
this example.

720
00:45:01,211 –> 00:45:04,271
So I want you to go out there and
find the 10 best stories about X.

721
00:45:04,571 –> 00:45:06,711
They’re most popular. I
want you to check Twitter.

722
00:45:06,831 –> 00:45:10,731
I want you to check here and it comes
back and I want you to structure that.

723
00:45:10,931 –> 00:45:12,871
As- Do you have a favorite tool
there? So for deep research,

724
00:45:12,931 –> 00:45:14,251
I know they’re all getting
better. They’re all good,

725
00:45:14,311 –> 00:45:15,491
but what are you using there, John?

726
00:45:15,591 –> 00:45:19,311
I use ChatGPT for that,
but now with cowork,

727
00:45:21,692 –> 00:45:26,051
it doesn’t ever call it deep research.
It just goes into research mode.

728
00:45:26,691 –> 00:45:29,452
You know how in the past it’s been like,

729
00:45:29,932 –> 00:45:33,032
I am now entering deep
research. You know what I mean?

730
00:45:33,092 –> 00:45:36,532
When you select it, I want you
to do deep research. Go. Yeah.

731
00:45:36,732 –> 00:45:39,932
Yeah. No, I mean, they sort
of evaporated that because

732
00:45:42,880 –> 00:45:47,852
it’s just over there doing things
and it’ll just enter into more

733
00:45:47,872 –> 00:45:51,352
of a deep research mode where it might
be gone for 10 minutes. Like I said,

734
00:45:51,412 –> 00:45:55,112
I spin up another task and work on
something else. But in this case,

735
00:45:55,192 –> 00:45:58,752
I use deep research. You can use any
tool pretty much has deep research now.

736
00:45:59,432 –> 00:46:03,532
You create a prompt and you could
create a prompt and save that prompt if

737
00:46:03,632 –> 00:46:06,532
something you use over and
over again, have it come back.

738
00:46:06,792 –> 00:46:10,252
And my big thing about deep research
is that it usually brings you back this

739
00:46:10,352 –> 00:46:12,112
report that’s like, “Okay,

740
00:46:12,572 –> 00:46:15,952
I guess there’s my afternoon
to read this freaking report.”.

741
00:46:15,972 –> 00:46:16,992
Take four hours to read that.

742
00:46:17,652 –> 00:46:21,332
So what I’ll do is I’ll tell the AI,
“Don’t bring me back this big long report,

743
00:46:21,432 –> 00:46:25,892
structure it into a table.”
I love tables, right?

744
00:46:25,952 –> 00:46:28,592
I love organizing- Scannable.
… especially things that come.

745
00:46:28,632 –> 00:46:30,032
Back. Easy to digest. Yeah.

746
00:46:30,652 –> 00:46:35,312
Yeah. So imagine in this
scenario that I have 10 stories

747
00:46:35,872 –> 00:46:39,372
from various news outlets, not my ideas,

748
00:46:39,433 –> 00:46:43,792
this is other people’s ideas that I went
and had the AI go and grab together.

749
00:46:44,813 –> 00:46:49,013
And then this next step represents
a set of rules as to how

750
00:46:49,793 –> 00:46:53,213
this particular story needs to be
transformed. So I just pull up,

751
00:46:54,133 –> 00:46:58,853
I use Beehive for my newsletter and
you can see this is a story that I

752
00:46:58,873 –> 00:47:02,853
ran last week, put this
Jerry Seinfeld gift,

753
00:47:03,373 –> 00:47:07,713
OpenAI is putting ads in ChatGPT
because GPUs don’t pay for themselves.

754
00:47:08,353 –> 00:47:11,113
And there’s a structure
to how this story works.

755
00:47:11,613 –> 00:47:15,393
It’s the facts and then why I
think this matters to my audience.

756
00:47:16,113 –> 00:47:20,413
And so all I do is create
another pass of the AI that says,

757
00:47:20,593 –> 00:47:21,426
“Go in here,

758
00:47:21,433 –> 00:47:26,093
grab whichever story that Russ
wants.” So Russ curated story three,

759
00:47:26,193 –> 00:47:29,133
let’s say, and apply
this set of rules to it.

760
00:47:31,133 –> 00:47:35,793
And that set of rules then
spits out on the other side a

761
00:47:35,953 –> 00:47:38,773
formatted piece of content.

762
00:47:39,633 –> 00:47:44,573
And then that last step is to polish it,
edit it, get it right, check the links,

763
00:47:44,653 –> 00:47:48,793
fact check the story in this case,
right? It’s always different,

764
00:47:49,093 –> 00:47:53,753
but the same deep
research is used to create

765
00:47:54,173 –> 00:47:57,574
another block of my newsletter called,

766
00:47:58,494 –> 00:48:01,214
it’s actually called By the Numbers,
but I used to call it Stat of the Week.

767
00:48:02,474 –> 00:48:04,434
And all I do is I take a story in here,

768
00:48:04,614 –> 00:48:08,734
let’s say Story five in the list
has a good stat in and I’m like,

769
00:48:08,794 –> 00:48:12,234
“That’s good to share.” And I say, “Okay,

770
00:48:12,354 –> 00:48:16,954
run Stat of the Week
rules on Story five and it

771
00:48:16,994 –> 00:48:20,194
outputs a different output.”
Does that make sense?

772
00:48:20,514 –> 00:48:24,054
Totally, totally. Yeah. And then it
ultimately ends. We’re telling it then,

773
00:48:24,394 –> 00:48:27,214
take these ideas, run this process.

774
00:48:27,274 –> 00:48:31,974
It’s the source structure.
What was the third one?

775
00:48:32,034 –> 00:48:32,867
Format. And.

776
00:48:33,600 –> 00:48:37,014
Polish it. And then the third
idea here is the tool of the week.

777
00:48:37,074 –> 00:48:40,334
So if I find something that’s like,
okay, that’s a bad, nice tool there,

778
00:48:41,894 –> 00:48:45,574
I’ve played with it, I want to bring
it up. So I’ve got a structure on that.

779
00:48:45,634 –> 00:48:49,154
So it’s the same set of research,
three different outputs.

780
00:48:50,714 –> 00:48:55,154
And the difference is
that this set of rules is

781
00:48:55,294 –> 00:48:57,374
different for each of those structures.

782
00:48:58,134 –> 00:49:02,794
And if you think about
this from a standpoint of
building any content or copy,

783
00:49:05,834 –> 00:49:07,814
what is the story? It doesn’t have
to be deep research. Of course,

784
00:49:07,874 –> 00:49:11,415
it could be a rant, it could be a
transcript, it could be a YouTube video,

785
00:49:11,474 –> 00:49:15,915
it could be any place that we generate

786
00:49:16,055 –> 00:49:20,155
ideas, then take that,
get it into some format.

787
00:49:21,155 –> 00:49:25,195
And again, I almost always recommend
bullets or tables because from there,

788
00:49:25,775 –> 00:49:28,935
once you get that stuff into a
table, you can then say, “Okay,

789
00:49:28,995 –> 00:49:31,735
apply these rules and
apply these rules.” Now,

790
00:49:31,795 –> 00:49:36,095
if I take this one step further and
go into cowork and how cowork works,

791
00:49:36,815 –> 00:49:38,995
how cowork works, the way ChatGPT,

792
00:49:39,055 –> 00:49:42,335
let’s first start with
how ChatGPT still works,

793
00:49:42,855 –> 00:49:47,755
would be if I want to format it
this way and this way and this way,

794
00:49:47,855 –> 00:49:50,055
I would need three different GPTs,

795
00:49:50,115 –> 00:49:55,115
I would have to stop and I would have
to call that GPT or copy and paste a

796
00:49:55,195 –> 00:49:58,795
prompt. Instead, what I do is I say,

797
00:49:59,715 –> 00:50:04,195
take story one, turn it into a
news story format, take story four,

798
00:50:04,315 –> 00:50:07,675
turn it inot of the week, take story
six and turn it into tool a week,

799
00:50:08,735 –> 00:50:13,355
and it’s got all those skills saved in
there and it just goes and runs and it’s

800
00:50:13,375 –> 00:50:16,320
just like … And

801
00:50:19,095 –> 00:50:20,455
if I get to the end and I’m like,

802
00:50:20,575 –> 00:50:25,335
“I really don’t like how you’re
writing those headlines for the news

803
00:50:25,355 –> 00:50:26,188
story,

804
00:50:26,695 –> 00:50:30,756
I want you to change it so that it works
this way.” And then it’ll just say,

805
00:50:30,836 –> 00:50:34,616
“Cool, I changed that and do you want
me to update the skill?” And it’s like,

806
00:50:34,676 –> 00:50:38,096
yeah, so that next time
I run it, it’s done.

807
00:50:38,176 –> 00:50:41,036
So it’s sort of that self-healing
idea that we talked about.

808
00:50:41,616 –> 00:50:45,936
Earlier. I love it. I love
it. This is fantastic.

809
00:50:46,356 –> 00:50:49,610
I could spend another hour going
through this stuff. Actually,

810
00:50:49,920 –> 00:50:54,196
I would like to because I’ve got
like a million questions for you now.

811
00:50:54,996 –> 00:50:56,376
I guess we are running out of time.

812
00:50:56,436 –> 00:50:59,516
So I guess the next thing is I got
to have you back for the 10th time or

813
00:50:59,556 –> 00:51:01,676
whatever it is. So we’ll for sure do that.

814
00:51:01,756 –> 00:51:06,256
But where can people find more? So you’ve
got a community called the Click.ai.

815
00:51:07,316 –> 00:51:08,616
Talk to us a little bit about that.

816
00:51:09,816 –> 00:51:12,776
And then also your great follow
on LinkedIn and other places.

817
00:51:13,056 –> 00:51:13,896
So talk about that as well.

818
00:51:14,616 –> 00:51:17,916
Yeah. You can always find me on
LinkedIn and even message me over there.

819
00:51:18,036 –> 00:51:20,136
I’m almost on LinkedIn all day long.

820
00:51:21,316 –> 00:51:24,656
The Click.ai has two components to it.

821
00:51:24,716 –> 00:51:27,376
It has a membership for individuals.

822
00:51:27,596 –> 00:51:31,976
And then I do team
training and implementation

823
00:51:32,776 –> 00:51:37,056
for teams. So both of those things
you can find on the Click.ai,

824
00:51:38,176 –> 00:51:43,016
the membership is really about using

825
00:51:43,156 –> 00:51:45,836
AI to do business work. These tools,

826
00:51:46,696 –> 00:51:50,456
they’re general purpose technologies.
They’re like electricity or something.

827
00:51:50,517 –> 00:51:55,017
We have the electricities everywhere
and it’s used for dang near everything.

828
00:51:55,577 –> 00:51:57,277
So AI is the same, right?

829
00:51:57,337 –> 00:52:01,097
It wasn’t built for business and it wasn’t
built for science and it wasn’t built

830
00:52:01,137 –> 00:52:03,957
for education. It was
built for all those things.

831
00:52:04,017 –> 00:52:08,497
And there’s no instruction manuals out
there for each one of these massive

832
00:52:08,537 –> 00:52:11,277
things that we can do.
And this is a big time

833
00:52:13,417 –> 00:52:14,617
tech transformation.

834
00:52:15,177 –> 00:52:18,817
And so the membership is there for
people that are trying to figure out,

835
00:52:18,877 –> 00:52:21,757
how do I use these tools
to do real business work?

836
00:52:22,557 –> 00:52:24,537
And I do think that we are entering in,

837
00:52:24,597 –> 00:52:26,917
you mentioned that the 2026
is going to be a big year.

838
00:52:27,097 –> 00:52:30,657
I do think this Cloud
cowork jump is a big one.

839
00:52:32,037 –> 00:52:36,557
And we are going to start
seeing a gap between both

840
00:52:36,617 –> 00:52:41,317
individuals and companies
that adopt this stuff and

841
00:52:42,277 –> 00:52:45,337
start to get more out of the same team.

842
00:52:46,037 –> 00:52:47,317
Totally, totally.

843
00:52:47,537 –> 00:52:48,370
It’s just crazy.

844
00:52:48,597 –> 00:52:50,157
And that’s what I’ve
heard recently. It’s like,

845
00:52:51,117 –> 00:52:53,857
we shouldn’t be fearful that AI is
coming for our jobs. Most people,

846
00:52:54,157 –> 00:52:56,217
there are going to be some exceptions,
so don’t want to downplay that.

847
00:52:56,280 –> 00:53:01,137
But hearing people talk on
podcasts, the team members you have,

848
00:53:01,237 –> 00:53:02,798
the team members that
really understand AI,

849
00:53:02,857 –> 00:53:06,757
and maybe they can both vibe code
and use cloud coworker or whatever,

850
00:53:07,438 –> 00:53:11,618
they become worth two or three
or four employees to you.

851
00:53:12,078 –> 00:53:16,598
And so that improves someone’s
marketability and someone’s earning

852
00:53:16,998 –> 00:53:20,058
potential. It doesn’t
diminish it. And so yes,

853
00:53:20,598 –> 00:53:24,458
the gap is going to be widening between
those that embrace this and Excel at it

854
00:53:24,578 –> 00:53:27,458
and the companies that embrace it
and Excel and those that don’t,

855
00:53:27,718 –> 00:53:28,898
the gap is going to widen for sure.

856
00:53:29,438 –> 00:53:34,238
Yeah. An interesting number right now
to look at is revenue per employee,

857
00:53:34,338 –> 00:53:34,518
right?

858
00:53:34,518 –> 00:53:35,498
Yeah. I love that number.

859
00:53:37,078 –> 00:53:37,911
How big can your …

860
00:53:39,118 –> 00:53:43,018
You mentioned I was with digital marketer
and I was texting with Richard Linder

861
00:53:43,078 –> 00:53:43,798
the other day,

862
00:53:43,798 –> 00:53:48,598
and we were talking about how many people
would have taken for us to get DM to

863
00:53:48,718 –> 00:53:50,938
wherever we got it was like
25 million or something.

864
00:53:51,698 –> 00:53:53,118
And by the time we did that,

865
00:53:53,178 –> 00:53:56,258
we had like 80 people and we’re
sitting there thinking, man,

866
00:53:56,318 –> 00:53:59,378
we could have done that with
four or five people maybe

867
00:54:01,338 –> 00:54:01,738
with these.

868
00:54:01,738 –> 00:54:03,778
Tools. It’s crazy what’s
possible now. Crazy.

869
00:54:04,078 –> 00:54:04,398
Yeah.

870
00:54:04,398 –> 00:54:07,918
Yeah, for sure. It’s awesome,
man. Really appreciate it.

871
00:54:08,618 –> 00:54:11,118
I do want to even jam with you one on
one because I’ve got some stuff we got to

872
00:54:11,138 –> 00:54:13,958
talk about, maybe get you in for some
training. And so for those listening,

873
00:54:14,118 –> 00:54:17,658
do that as well. Check out
the click.ai, hire Russ,

874
00:54:17,918 –> 00:54:22,738
put these tools to work for your
business. With that, Russ, thanks,

875
00:54:22,799 –> 00:54:26,099
man. Ton of fun. Looking forward to
the next time. Good to see you, buddy.

876
00:54:26,179 –> 00:54:30,759
Absolutely. And as always, thank you for
tuning in. We’d love to hear from you,

877
00:54:30,899 –> 00:54:33,659
leave us a review on iTunes or
wherever if you haven’t done it. Also,

878
00:54:33,719 –> 00:54:35,579
if you found this episode helpful,

879
00:54:35,999 –> 00:54:38,759
share with somebody else you think
will benefit from it. And with that,

880
00:54:38,839 –> 00:54:41,259
until next time, thank
you for listening. Hey,

881
00:54:41,319 –> 00:54:45,359
as we wrap up this week’s episode, I
want to mention, if you’re a great brand,

882
00:54:45,459 –> 00:54:47,759
if you’re scaling high seven, eight,

883
00:54:47,879 –> 00:54:52,399
nine figures in D2C or Omnichannel,
we should potentially talk.

884
00:54:52,939 –> 00:54:57,059
We’ve worked with some of your favorite
brands and we’d love to consider working

885
00:54:57,199 –> 00:55:01,999
with you as well. We are masters at
unlocking new channels like YouTube,

886
00:55:02,359 –> 00:55:06,159
unlocking new scale on platforms like
Amazon where we can add up to eight

887
00:55:06,259 –> 00:55:08,879
figures in new growth, and we’ve got
multiple ways we can work with you.

888
00:55:09,019 –> 00:55:13,979
So we can do the full service thing and
work like a partner with your team and

889
00:55:14,019 –> 00:55:16,839
really run everything, or
we can offer consulting.

890
00:55:16,919 –> 00:55:19,779
So maybe you’ve got an internal
team that really knows their stuff,

891
00:55:19,879 –> 00:55:22,819
but there’s an area they don’t know
really well and they’d like to get some

892
00:55:22,839 –> 00:55:26,299
consulting. We can do that. We also have
tons of free guides, free resources,

893
00:55:26,379 –> 00:55:27,459
free materials you can check out.

894
00:55:28,159 –> 00:55:32,099
All of that gets started
at omgcommerce.com,

895
00:55:32,619 –> 00:55:34,819
and we can’t wait to help
you scale profitably.