Most AI agent content is hype. This isn’t.

I’m Mike, host of Lone Wolf Unleashed.

This week I walk you through how I implemented my first AI agent team using Paperclip — an open-source multi-agent platform — and more importantly, the methodical approach that made the result controllable rather than chaotic.

The short version: I started with a target operating model in Obsidian, not with the tool.

People, process, technology, on a page.

I handed the architecture to Claude, spun up a “CEO agent” in Paperclip, and let it form a team — CTO, business analyst, content writer, marketing manager, clips publisher — that now runs my content pipeline from Asana through Descript, SharePoint and into Metricool.

Architecture before automation.

Human-in-the-loop, non-negotiable.

You’re still the master of your business.

Listen to hear me walk you through it.

Chapters

00:00 First AI agent team, implemented

00:30 Why Paperclip (and going from local to cloud)

01:18 Starting with a target operating model in Obsidian

02:03 Handing the architecture to Claude

02:22 The CEO agent spawns the team

03:40 The content workflow: Asana → Descript → SharePoint → Paperclip → Metricool

05:04 Matching agents to models: Opus, Sonnet, Haiku

05:56 Routines instead of manual triggers

06:40 What took the time (spoiler: it wasn’t the agents)

07:34 Human-in-the-loop and run history

09:10 You are the master of your business

10:54 The 80/20 rule for phase-one builds

Resources: lonewolfunleashed.com/resources

Mentioned in this episode:

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This podcast is part of the Podknows Podcasting ICN Network

G'. Day. My name's Mike and you're listening to Lone Wolf Unleashed, the podcast that

helps you take time back from your business so you can live it on your

terms. This week I have implemented my first

agent team to start doing stuff in my business. I'm

super excited to walk you through how I've done that and how you can do

that for yourself as well. So the system I've used to do this

is in Paperclip. It is an open source piece of software.

You can go to paperclip clip.ing, i believe it is,

to go and check that out. I have initially installed

it on some local servers just on my machine to

play around with. And then once I was happy with the fact that I was

going to be using this more often, I have deployed it onto my own cloud

server, which is pretty cool. And I've basically

gone and created an agent team to help with some of my content management

things. Things like generating of

titles and descriptions for clips and drafting of

newsletter articles based on the transcripts of these

podcasts.

And I've connected them up to my different tools such as SharePoint and

Metricool to be able to do that automatically. So how do we

start? Well, I have a target

operating model and I modeled this out in Obsidian. It's

similar to if you go check out my 5PS framework,

the second P IS profile. I've done previous episodes on that.

You can check out the 5PS framework on my website. The

profile basically paints a high level picture of your business,

lists out a lot of the high level processes, the different platforms and things that

you're using. This time around, I've done a little bit more of a technical diagram

that actually connects up all the processes and systems to each other so, so we

can get a sense of how things flow. And at the bottom of all those

things is Paperclip. So things will feed into there so

the processes can run with the agent teams. I basically

took that, gave that to Claude to say, hey, this

is my target operating model. Here's what Paperclip is and what it does.

Give me an initial architecture about how this will

work, what each agent will do, et cetera. So that's what we

did. We took that architecture, I said,

great, let's do up a prompt for the CEO.

So the CEO is an agent. It's the first agent that exists in your

Paperclip instance and the CEO is going to now

take that prompt and it's going to start to form up the

different teams with the different capabilities that

can exist in there. So the prompt is basically all

the work stream items to have that as a project. So in Paperclip, I

went in, I created a new project which is the target operating model. I

gave the issue to the CEO to say, hey, this is what we have

in mind. What happened? Well, it spun up a

CTO role, so a chief Technology Officer to help with

the understanding of the technical side of things. There's a business

analyst agent in there to help with some of the requirements work. And

then from there it went, okay, based on the requirements that we're seeing

here, we're going to need a content writer agent, we're going to need a

marketing manager agent. We're going to. We're going to need a clips publisher agent.

When you look at the org chart, because there is an org chart now

of the agents and how they are linked to each other, you can see now

the hierarchy in the org chart that that structure has come into, which

is really cool. So then each agent can now be configured to do

different things based on the ecosystem that we're trying to set up.

In this case, content management. So it all begins with the

content plan. I need to get better at content planning, but that is

all done in my Asana. And so there's a

connection to the Asana, right? So we can draw down whatever the

content pipeline is that we have planned. And then there's the

podcast that we record, just as I'm doing now, that's done in

descript. Now, Descript has a bit of a limited API

in terms of, like, what we can do there. But once I've finished with the

recording of the podcast, I can then go and put the

recording and the transcript in a specific SharePoint

folder, and the agent will pick up that transcript and it will start to do

stuff with it, such as understand what the SEO profile

of the transcript will be. It will start to form up

various different titles and descriptions of

clips and that sort of stuff. So basically, it has helped us understand

the types of clips that we can start to produce, where in

the transcript, where in the original video we can go to start to take that

content out, to be able to snip it up and to get it out. On

social platforms, after the clip video is uploaded to a certain

folder, another agent will come, it'll pick it up and it will push it

into Metricool by the API and it will schedule a draft

post, which is amazing because scheduling some of these

posts can be very time consuming and to be able to see how it's

working and Sitting there in the background working is very,

very cool. What we can do is we can then refine the different

configurations. Now, you've heard me talk before about

how to do Claude skills. This is very, very much

the same. So each agent can be connected to a different large

language model or an AI tool. In this case, I'm in the

Anthropic suite already, so I've connected it to the various different

Claude models. The CEO has Opus, for

example. My content writer has Sonnet. One of my agents is even able to

operate off Haiku, which is great. Why is that important?

It's important because, as I've discussed in a previous episode, is

being able to manage our token costs, the cheaper models.

If we're able to execute the task on a cheaper model, then we

should absolutely be doing that. We don't want to drive a Ferrari to get the

groceries. We want to use the right tool for the right job.

So that's all set up now so we have the different skills and then we

can set this up on a routine. So a routine is

every so often. So at a time interval that we've set

in, you can go and get the agent

to then check the folder to see if there's a new transcript, and if there

is, then do something with it. If not, then it will stop and then it

will start again at the next interval. You don't have to initiate a

particular workflow run. You can just let it pull away

in the background and then to do the stuff when

the particular signal appears, which is amazing. So

now we've got the process, the overarching process down, the main

activities that need to happen, what tools need to be connected.

The thing that I learned about this is because AI

is moving at such a speed now in terms of how it

operates, what happened was it then had a list of things, a

list of issues that came back to me. And issues in Paperclip are just tasks

to review, to check, to update different pieces of information.

What I found was it came back with a whole bunch of information that I

needed, and it took me a long time, time to go through. And I had

to engage with Claude about where to get certain pieces of information from for my

systems and how to get the API credentials and where

to put them securely and all that sort of stuff that took me

quite a long time. So it didn't take the agent teams a whole lot of

time to set themselves up and to have the initial stuff there. What

took the time was me then going away and doing the task,

doing the Review, making sure that things were right, making some adjustments, that sort of

stuff. Now, the cool thing though, about this is

it allowed me and gave me confidence that I was in control. And

I think there's a lot of people out there at the moment who are scared

about what AI can do. We've heard the stories about OpenClaw and things about

AI that is uncontrolled and it can go out and do stuff. It

will just delete file directories. It will do that automatically

of its own volition. We don't want that. What my

Paperclip instance is allowing me to do is it's allowing me to be in the

loop with what the agents are doing. It has

a full run history of what every

agent has done at every single point. It gives the thought processes,

it gives what it's doing, what it's executing, what it's accessing. All

of that information is in there. So it really does give

me a higher confidence in using this moving forward

because I am being held and retained within

the loop. So that is something to think about as you're using these AI

tools. How much do you know is actually happening in the background? How

much control and influence can you have over the AI as you go about doing

things? And I have talked before about how you go about prompting.

Definitely want to be prompting well, but when it comes to doing things that are

more routine workflow, this is really important as

well, that you're targeting a very specific folder. Don't go outside that

folder. You don't need to access anything else. It's just that folder.

And to be able to see in the order history that that is what has

happened is that it's gone. And check that very specific folder.

Okay, found nothing. I'm gonna go to sleep again. An hour later, I'm gonna

wake up, I'm gonna check the folder. Oh, I found something in that folder. Now

I know what to do with it. I'm gonna initiate these particular skills and I'm

going to go and do that. I hope this has painted a little bit of

a picture for you, because being able to document out what our

processes are, the types of knowledge that go into executing each one of

these tasks, and being able to go in with a solid architecture

in terms of how the system will look and how it will behave is super

important. You can't just go from, I have an idea

and I'm just going to get AI to set it up. You can't just do

that. You've got to apply your intelligence of your business

to the page first. Take the time

to sit down and think through what it is that I'm doing, how do

I do it, what systems am I using, and then

go from there. I can absolutely help you brainstorm, it can

absolutely help you plan, it, can absolutely do all those things. I've got

a video that I'm going to be putting on my website that sort of takes

you through like a little bit of how I've set this particular instance up. I

initiate a new build in there of a new agent team

that I'm setting up around business analysis. It's not

as straightforward as going, oh well, I'd really love it to just do

this and then it go away. You are the master of your business.

It's likely that if you're listening to this podcast, you are the

sole operator of your business, the sole person in it. You are the master.

You know what is going on in your business. So you need to be able

to articulate what is happening so that it then can be

replicated by an agent team. Don't worry about going straight

automation end to end right now. Let's just focus on the little information

transfer things that can be done and automated now in

phase one, and then we can look at refining later. If you try to go

for perfection first, it will take a whole lot longer.

So much more effort. Think of the 8020 rule here. Okay, we want to

get 80% of the results with 20% of the effort. What's the 20% of

effort that I can put in now? They can get me almost there. And then

we can make refinements later on in terms of how you automate that.

So what have we learned? We've learned document out a target operating

model. That includes who is doing what in what process

and what tech you're using. A target operating model has those three components.

It has the people, the process and the technology. And then

we can give it to AI to do the architecture for

you. Give it some of the paperclip docs so it knows how to behave

and what the system does. And then we can feed an initial prompt

into the CEO so it can start to set up your different other sub agents

that will need to operate that particular process.

You can go and check out my website, lonewolfunleashed.com

forward/resources. There's a whole bunch of stuff there. There's a whole

library there of things that you can go and check out that might be useful

for you in building out your business systems. Learn how you can set up

your first AI agent suite. It's a very exciting time in

terms of the individual productivity that we are able to achieve

now. Thank you so much, and I'll see you next week.