From Zero to Your First Agentic AI Workflow in 26 Minutes (Claude Code)

Aentic workflows are changing how we build AI automations, but not only that, they're also changing the entire industry with more businesses investing in Aentic AI to improve their workflows.

So, if you're looking to start building AI automations to make your life easier, or you want to make money building these for businesses, then this is the best place to start. I've been building AI automations for a little over a year now, and I've already helped thousands of people build their first AI

automation. So, I do know how

automation. So, I do know how intimidating everything can look at first. So, that's why in this video,

first. So, that's why in this video, I'll be telling you everything you need to know, and then I'm going to show you how to build your first agentic workflow from absolutely zero. My job is to make this as easy to understand as possible for you. So, let's get into it. All

for you. So, let's get into it. All

right. So, before we actually build anything, let's make sure that we're on the same page about what agentic workflows actually are. If you've been building traditional automations, you know the drill. You use a tool like make or n. You drag a node onto the canvas.

or n. You drag a node onto the canvas.

You configure it. You connect it to the next one. You make sure the right

next one. You make sure the right variables are passing through. You test

it. You add another node. And you keep going. And when you hit an error, which

going. And when you hit an error, which you will, you read the error message.

You figure out what went wrong. You fix

it. You test again. And you repeat until it works. You're basically building the

it works. You're basically building the whole thing manually. and if it breaks again later, you're the one who has to go back in there and fix it yourself.

Now, this was a huge leap in the AI automation space because it significantly lowered the barrier to entry and it allowed anyone from any background to learn these tools and build some really powerful automations in a matter of days. But Agentic

Workflows completely flipped that whole process because instead of telling the system how to do something step by step, you're just telling it what you want and then the agent figures out the rest. So,

think about it like hiring a really talented developer. You don't sit there

talented developer. You don't sit there explaining the code or walking them through the logic line by line. You walk

in and you explain the problem. You

describe the outcome you want and then you ask, okay, what else do you need from me? So that's what makes it

from me? So that's what makes it agentic. The system reasons, it adapts,

agentic. The system reasons, it adapts, it asks clarifying questions when it needs to, it makes decisions, it fixes itself when something breaks and it does research all to make your job as easy as possible. Now I do believe that

possible. Now I do believe that traditional automation with a tool like NN isn't going anywhere. It's still

perfect for repetitive, predictable tasks. And there are two terms that we

tasks. And there are two terms that we use in the AI automation space, deterministic and non-deterministic.

Deterministic means predictable. And in

automation, predictable is beautiful.

Boring is beautiful because you know exactly what's going to happen every single time the automation runs.

Non-deterministic means that given an input and you don't know exactly what the output will be. There's variability,

there's judgment, there's AI, and AI is non-deterministic. So our job as AI

non-deterministic. So our job as AI automation builders is to make a non-deterministic process as deterministic as possible because typically business processes are pretty deterministic or at least as

deterministic as they can be. So that's

exactly where agentic workflows shine.

They unlock tasks that are too variable for traditional automation stuff that needs judgment calls at every step just to be a little bit more dynamic. Maybe

research, maybe content creation, customers support, lead genen. These are

messy processes that can involve a lot of moving pieces. So with aic workflows, we can handle that variability and the system actually gets better over time instead of just setting it and forgetting it or having to go manually in and make improvements by yourself.

There's a reason why so many builders right now are shifting to tools that are a little bit more genetic like cloud code or anti-gravity because they fix a lot of the common struggles with traditional automation. There's no more

traditional automation. There's no more finding and fixing errors manually. No

more setting up API calls yourself. No

more manually connecting to MCP servers.

No more getting stuck on the logic. So,

here's a really simple way to think about that evolution. Let's say you wanted to get to a carnival across town and you know roughly where it is, but you still need directions. Traditional

automation is like using a paper map and a compass and you're looking at the street names and you're trying to figure out your own routes. You're choosing the streets to walk down and you can get there and you will get there. It just

takes a little bit more effort and if you make the wrong turn, you'd have to figure that out and course correct. But

with Agentic workflows, that's just like pulling out your phone, googling for the carnival, and then it basically gives you this blue line, and all you have to do is follow it. And if you go off the path, it will like recalculate and it will make sure that you go back to the actual outcome that you're looking for.

So in both scenarios, you can get to the same destination, but it's just a completely different experience getting there. So let's talk about what's

there. So let's talk about what's actually happening under the hood and what you need to know in order to build an agentic workflow. So we're using a framework called WAT. You could just hop into Cloud Code right now and start talking to the agent and honestly it

would do just fine. But without

structure, things get messy fast. Think

about it like a school locker. If you

just threw every piece of paper, every homework assignment, every note from every subject into a locker with no organization, you could get straight A's, but it would be tough because you'd be digging through piles of paper. You'd

probably forget things or lose things.

And that's why you would have finders, shelves, folders, notebooks. Structure

makes everything easier. So, it's the exact same thing here. We need to tell cloud code how to stay organized. And

that's why we do that using our framework called WAT. W stands for workflows, A stands for agent, and T stands for tools. Each piece of that framework has its own job. So let me break that down. All right. So first we have the workflows which are the

instructions. These are instruction

instructions. These are instruction files that are written in markdown which is basically just natural language but it uses things like pound signs and asterisks so that the agent knows what are the headers, what are the subheaders, what's bold, what's important, stuff like that. So I'll put

a quick example right up here on the screen if you've never heard of markdown, but just know it's super simple and you could go read that and you would not be confused at all. So

think of a workflow like a job description or an SOP, just a process.

It tells the agent what to do. For

example, we might have a workflow called competitor analysis. The workflow tells

competitor analysis. The workflow tells the agent to research businesses, then gather data from five competitor sources, then analyze those findings, and then analyze our business, and then create a PDF report. So, it's just basically a process, a sequence of

steps. They're guidelines. The agent

steps. They're guidelines. The agent

then uses these guidelines to figure out how to achieve that end goal. And here's

the cool part. As the agent works and it gives you outputs, you can say, I liked this, but I didn't like that, or go ahead and change this. And it'll

actually update its workflow file so that next time it calls on the workflow, it will do better. Now, the A stands for agent, which is the coordinator. This is

the actual AI. This is claude code itself. This is the brain. It reads your

itself. This is the brain. It reads your workflows and it reads those instructions and it looks at what tools it has available and then it makes decisions about which tool to use and when. And if something breaks, it will

when. And if something breaks, it will handle the error. It will research it.

It will figure it out and it will adapt for you. So really just think of this as

for you. So really just think of this as like a project manager. You hand them the instructions and they will delegate tasks to the right people except for not people. It's more so they delegate tasks

people. It's more so they delegate tasks to the right tools and workflows. So you

don't have to figure out the sequencing or the logic. Cloud code does it. And

then the T are the tools which are kind of the workers or the actions. Tools are

Python scripts that actually do the work. And this is where the ugly code

work. And this is where the ugly code lives. But don't worry, you don't have

lives. But don't worry, you don't have to touch it. Each tool will have a one specific job. The workflow is a big

specific job. The workflow is a big process. A tool is just one specific

process. A tool is just one specific action like scraping a website or generating a PDF. The agent then calls these tools when it needs to based on what it says in the workflow instructions. So for a research

instructions. So for a research workflow, your tools might be one to scrape a website, one to analyze findings, and one to generate a PDF. And

here's the best part. These tools also get automatically built by cloud code, and if they fail, they get automatically updated and fixed by cloud code. They're

super modular, so you can call a tool with a different workflow if you want to later. So, how do these three layers

later. So, how do these three layers work together? Let me just show you how

work together? Let me just show you how this connects. Let's say that we give an

this connects. Let's say that we give an agent a task like research company X's pricing and then create a PDF report for me. The agent reads the workflow, the

me. The agent reads the workflow, the instructions, looks at the available tools and decides the sequence. So,

first it would call something like a web search tool to find the relevant info.

Then it would call something like a scrape website tool to pull content from those URLs. Then it calls the analyze

those URLs. Then it calls the analyze finding tool to synthesize everything.

And finally, it could call the generate PDF tool to create that branded report.

Now, the whole time it's reasoning and it's making decisions based on what you told it to do in the workflow and you're not mapping it out step by step. The

agent handles the logic and updates it.

All right, so that's what I wanted you guys to understand about agentic workflows. All right, but before we

workflows. All right, but before we continue, if you want to follow along with the video, you can download this resource I'll be using in my community.

Once you're there, you just need to look for the post with this video and you'll find it attached as a markdown file.

Now, let's get back to building your first agentic workflow. Okay, so we got all of that stuff out of the way. The

first thing I need you to do is go to Google or a browser and type in VS Code or Visual Studio Code and go ahead and download this. This is where we are

download this. This is where we are going to be using Cloud Code. So once

you install that, it's going to look like this when you open it up. It's just

kind of like a welcome onboarding screen. What I'm going to do is just

screen. What I'm going to do is just break everything down as far as what you actually need to click on, what you need to know because there's a lot of buttons in here and it's probably a new interface which makes it overwhelming, but it's going to be simple. You'll see.

So before we do anything else, we have to actually install the Claude Code extension. You can see up here I've got

extension. You can see up here I've got this little button where if I click on it, it opens up Cloud Code and we get the little crab and we can now talk to Claude Code. So, you're not going to

Claude Code. So, you're not going to have that by default. The way you get that is you go over to the lefth hand side to the menu bar and you're going to click on extensions. You are then going to search for claude code. So, if you just type in claude, it should pop up over here and you'll click on it and

then you just have to install this extension. Now, once you install this,

extension. Now, once you install this, it will prompt you to sign in with your Anthropic or your Claude subscription.

And so, you do have to be on a paid cloud subscription in order to use cloud code. You can see here on the free

code. You can see here on the free version you don't have it but pro or max or the higher max you will have cloud code with opus 4.5. So once you're on a pro or max plan then you will come back into VS Code. You'll sign in with that

and you should be all set to start using cloud code right here. So we've got that configured. Now what I want you to do is

configured. Now what I want you to do is click on the button up in the top right and close out of this window and you should be able to see that you have cloud code right here. So now in order to really use cloud code we have to be in some sort of project. So, if I go

over to the lefth hand side, and I go all the way up to the explorer, you can see that it says no folder open, which means basically we're not in a project.

So, you're going to go ahead and click on open folder, and you can see what I did is I created a folder right here called first aentic workflow, and it's completely blank. So, open up a blank

completely blank. So, open up a blank folder or go create a new one, and then select it. So, this is what your screen

select it. So, this is what your screen should now look like. You've got your folder on the lefth hand side with no files in there. You've got these other panels on the right, and what we're going to do is close out of the VS Code agent, and then we're going to open up Cloud Code. And then, we're just going

Cloud Code. And then, we're just going to get rid of the welcome VS Code screen. So what we have here is files on

screen. So what we have here is files on the lefth hand side and this is where we're going to see any folders that we create, any of the files that Claude actually makes for us. And then right here is where we can actually talk to Claude code. And just think of this as

Claude code. And just think of this as your typical chat GBT interface, your Gemini interface or of course your Claude interface. This is where the

Claude interface. This is where the agent lives and then this is where the files live. So this is where we'll see

files live. So this is where we'll see the workflows and tools as we mentioned.

So you remember earlier I talked about how we had to make sure that our agent understands our structure just like it wouldn't want to throw notes and random stuff in a locker. We have to give it structure. So, what we're going to do is

structure. So, what we're going to do is we're going to give it this file that's called a claw.md file. And if you want to get this, I will have it available for download in my free school community. So, this is basically the

community. So, this is basically the onboarding document. We're catching the

onboarding document. We're catching the agent up to speed as far as how do we want to work. So, you can see what we're doing is we're explaining you're working inside the WAT frameworks, agents, tools. So, then we go ahead and explain.

tools. So, then we go ahead and explain.

Layer 1 is the instructions. Layer two

is you. Layer three are the tools. I'm

not going to read out this whole markdown file line by line. You guys can access it like I said, but I'll hit on a few of the important things. So, we go over how to operate. So we tell it first look in your existing tools then you learn and adapt when things fail. So

when you hit an error you read it you fix the script and you reset. So for

example if you get rate limited on an API you would dig into the docs you would see if you could discover a batch endpoint you would refactor the tool to use it verify it works and then update the workflow so that error never happens again. And then of course you want to

again. And then of course you want to keep the workflows current. We explain

the self-improvement loop. We explain

the file structure which is going to look like this. These are the different folders we're going to have. We'll have

one for temporary files. We'll have one for tools. We'll have one for workflows.

for tools. We'll have one for workflows.

And then we'll of course have some other different files in here as well. So

anyways, that is our cloud.MD file. So

what I'm going to do is I'm going to drag it over here into the lefth hand side because this is where we have our project files and folders. So I drop it in there. You can see it opens up over

in there. You can see it opens up over here. We could also read it right there.

here. We could also read it right there.

But I'm just going to go ahead and close out of that. And now we have claw.md set

up right here. So what you can do now that we have claw.md is you could do a slash command which is /init. And that

basically just initializes the environment. But we could also just do

environment. But we could also just do this in natural language. So, I'm going to go ahead and say, "Hey, Claude, I just dropped in a claw.md file that explains how I want you to work in this project. Go ahead and initialize the

project. Go ahead and initialize the project and get everything set up and ask me any questions if you have any."

So, when I shoot that off, what you're going to notice is that we can see everything the claw's doing. We're going

to see its thinking. We're going to see its thoughts. We're going to see what

its thoughts. We're going to see what it's doing. So, in this case, it

it's doing. So, in this case, it literally says, "Okay, I'll read the claw.md file to understand your project

claw.md file to understand your project requirements, and then I'm going to get everything set up." And then what's cool is we can actually see what it's doing.

So, we can see that it read the file. We

can see now that it understands, and now it's going to create a to-do list and start to make us those folders. So,

temporary tools, workflows, and you can see on the lefth hand side, it actually just built those. Now, one thing you may have noticed right here is that when we're talking to Claude, yours might look a little bit different because you may be looking for this bypass permissions mode. When we talk to Claude

permissions mode. When we talk to Claude Code, we can either use bypass permissions, we can use ask before edits, we can use edit automatically, or we can use just plan mode. So, if you want to be able to get bypass permissions mode, you have to go to your settings and then you're going to type

in clawed code and then you just have to allow dangerously bypassed permissions.

Now, yes, I know it sounds dangerous because the word dangerous is explicitly in there, but it's not too bad. It's

really just more so if you give it a huge task and you don't do any planning and you don't know what it could do, it's just going to go execute everything without asking. So typically the flow

without asking. So typically the flow that we like to follow is use plan mode, have it build out a really nice plan, ask you questions, and then once you're confident in it, say, "Yep, go ahead."

And you turn on bypass permissions, which you guys will see me do that exact thing when we start building this workflow. So it did ask some questions.

workflow. So it did ask some questions.

Do you want me to continue with a straightforward initialization? Do you

straightforward initialization? Do you want any Python packages? Do you want to do a git repository? Are there any specific tools or workflows? Right now,

we're not going to worry about that. All

I wanted to do was just get this folder structure set up. As you can see, we've got workflows, nothing in there. We've

got tools with nothing in there. And

we've got a temporary folder with nothing in there. So, I'm just going to go ahead and do /clear, which is just going to reset our conversation. All

right. So, let's talk about the actual workflow that we want to build today.

What I want to build is a competitor research workflow. And I want the

research workflow. And I want the deliverable to be branded PDFs, meaning I want to give Cloud Code my logo, my brand guidelines, and information about my business. And then it has to go

my business. And then it has to go research competitors. It's going to

research competitors. It's going to create, you know, like maybe a SWAT analysis or opportunities for us or tracking what they're doing really well.

And then it's going to report all back with a PDF that once again is branded.

So that's basically what I'm going to start with because I know what I want, but I don't know maybe the tools we're going to use or the exact structure. So

I'm going to switch over here to plan mode and I'm just going to say exactly that. Hey Claude, so I've got an idea

that. Hey Claude, so I've got an idea for a workflow that I want you to build.

I basically at the end of it want a PDF and I want it to be branded. So I want to be able to give you my company logo and my company brand guidelines and the whole PDF output should have my logo on there and have our colors and our

typography and stuff like that. But what

I want you to do is it's basically a competitor analysis and research workflow. So I want to also give you

workflow. So I want to also give you information about my business that you need to save. And based on that information, you need to go find competitors and you need to find me areas to improve my business. Maybe see

what's working well for them and just build me out a good way for me to keep tabs on the market and what's going on with my competitors. Yeah, that's kind of what I'm looking for. So help me build a plan for this workflow. And once

again, of course, you can ask me any questions that you have if you're confused. All right, so that was my

confused. All right, so that was my request. You can see it was all natural

request. You can see it was all natural language. It's very simple. It's

language. It's very simple. It's

probably the way I would just speak to like a human. And what it's going to do now that it's on plan mode is it's going to think. It's going to look at some

to think. It's going to look at some stuff. It might even do some initial

stuff. It might even do some initial research in order to help build a plan.

And then what it's going to do is it is going to actually ask us questions. Now,

I know that this might seem a little intimidating, but really when I was learning Claude code, the way that I did it was I would ask it a question and then I would just read every single line of what it's doing. If any of these tasks or glob pattern like what is that?

If anything confused me, I would just say what is this? What did you do here?

Why did you do that? So, it's really about if you're genuinely curious and you just read and pay attention, you will pick this up really, really fast.

So, you can see it first of all explored existing workflows and tools and then it's looking at branding and PDF capabilities. This was basically just

capabilities. This was basically just seeing if it could find any tools in the folder for Python. It's reading other files in our environment to see what's going on. And now you can see that we

going on. And now you can see that we are in the question phase. So, it's got four questions to start. First one is discovery. How should competitors be

discovery. How should competitors be identified for analysis? I can either provide a list. It can autodiscocover based on my business info or hybrid. You

know what? So, let's just go ahead and try autodiscocover based on my business info. Then it asks us what business

info. Then it asks us what business information should the workflow collect and save about your company. Company

description and value prop, product, service, and pricing, target market, and customer segments, key features. Let's

just do all of that. We wanted to get as much information about us as possible.

For analysis, it asks what aspects of competitors should be analyzed. We've

got products, services, features, pricing and business model, marketing, messaging. I want to analyze all of

messaging. I want to analyze all of this. Why would we not? So, I'm going to

this. Why would we not? So, I'm going to choose all of it. For branding, it says can I use the existing branding assets I found in your YouTube analysis project?

And this is basically because I've got a big project that this first agentic workflow project sits in and it can search through those as well. But I'm

going to assume that this is like you guys setting up a first workflow. So I'm

going to say no, which is I will provide different branding. So I'm going to go

different branding. So I'm going to go ahead and submit those answers. It's

going to take those adjust the plan a little bit and it may come back with more questions. It may not. So we'll

more questions. It may not. So we'll

see. And this is pretty cool because it said I have all the information I need.

Let me launch a plan agent to actually design the implementation approach. It's

asking us how often do we want to run this. I'm just going to go with monthly

this. I'm just going to go with monthly for now. For the output, it asks if we

for now. For the output, it asks if we want anything else besides a PDF. That's

pretty cool. But I'm just going to go PDF. And then for the budget, what's

PDF. And then for the budget, what's your comfort level with API cost for this workflow? I like how it's showing

this workflow? I like how it's showing us different approaches here. And I'm

just going to continue to go with the recommended approach. And we're going to

recommended approach. And we're going to go ahead and do this middle one. All

right. So, at this point, it actually finished the plan. So, if I scroll all the way back up to when it started telling us, you can see this is super comprehensive. So, I'm still scrolling.

comprehensive. So, I'm still scrolling.

Okay. Competitor analysis workflow implementation plan. Build a monthly

implementation plan. Build a monthly recurring competitor analysis system that automatically discovers competitors, researches their offerings, generates a fully branded PDF report with actionable insights. So user

requirements would be discovery, business info, analysis, output, frequency, budget. We've got the

frequency, budget. We've got the architecture. We've got the text stack.

architecture. We've got the text stack.

So it's going to be using cloud sonnet.

It's going to use firecraw and perplexity. It's going to use sonnet.

perplexity. It's going to use sonnet.

And it's going to use report lab for pdf generation. So it'll probably prompt us

generation. So it'll probably prompt us to go grab an API key there. And it's

also going to generate charts using mattplot lib, which I believe is a python extension or plugin. And it's

going to help with charts. It's also

going to add some things in our folders over here. So you can see it's going to

over here. So you can see it's going to add a new folder called brand assets, and that's where we will upload our logo and our brand guidelines. And it's

basically planning to create a few different things. It's going to create

different things. It's going to create some files in the temporary folder. As

you can see, it's going to create a workflow called competitor analysis. And

it's going to create these five tools.

So, collect business info, discover competitors, research competitors, analyze competitors, and generate competitor PDF. So, exactly like I said,

competitor PDF. So, exactly like I said, it's going to create this workflow. It's

going to create these tools, and then we should be good to run it. Now, one thing I noticed is it has a brand configuration file, and this basically made up our brand information, and it would probably want us to come in here and choose, you know, a name and maybe a

logo path. But what we're going to do is

logo path. But what we're going to do is we want to actually just drop in those files for it. So that's something that we will have to change, but we'll just keep going for now. We can see that it decided how to handle edge cases like competitor websites block scraping or

insufficient competitors found, rate limiting, invalid brand assets, and data completeness issues. It's also giving us

completeness issues. It's also giving us a cost breakdown, which is pretty cool.

So the first run will be about a dollar and a half. It's also going to be doing subsequent runs on a 30-day cycle, which will be a huge cost savings because it's going to cache some of the data. And

then if you're adding some new competitors, it'll be maybe another 50ents. So anyways, that is the end of

50ents. So anyways, that is the end of the plan. We could basically go ahead

the plan. We could basically go ahead now and auto accept or we could keep planning. And I do want to say no keep

planning. And I do want to say no keep planning because there's one thing I want to change, which was our brand assets. So what I'm going to do is I'm

assets. So what I'm going to do is I'm going to take a logo, drag it into the lefth hand side. Take the brand guidelines and drag that into the lefth hand side. And you can see that we have

hand side. And you can see that we have these things up here that pop in and we can actually see them. That plan looks good. The only change I want to make is

good. The only change I want to make is about the brand guidelines and the assets. So I just dropped you in two

assets. So I just dropped you in two files AISpng.png and AIS brand guidelines.png.

Those are the ones that I want you to use to create the branded PDF. So, look

at those, extract the information out of them, and make sure that the logo and the colors and everything appear on the final output PDF. And if you need to, you can throw those into a folder in this project to keep things organized.

So, this is awesome. It said, "I found your logos and I'm creating a brand asset guide." So, we've got the logo and

asset guide." So, we've got the logo and then it also extracted our colors and typography and now it's going to update the plan to use those assets. And now,

since that has been changed, we're going to go ahead and auto accept the plan.

Hopefully, it will get working for us.

Of course, it's going to create a to-do list, and then it's just going to start building all these different scripts, whether that's a workflow or a tool. And

then it's going to test the workflow.

And like I said, it'll probably have to come back and ask us for an API key or something like that. All right, so the workflow is ready. We can see that we have our branded assets set up. We've

got the workflow completed. We've got

the Python tools completed. We've got

some setup files. So, we also have a readme that we could open up, which should basically just tell us pretty much how this actual workflow works. So,

that's pretty cool. Now, we do have to go get two API keys to start. We need an enthropic key, and we need a fire crawl key. So it does actually tell us that

key. So it does actually tell us that here again we have to install dependencies. We have to set up those

dependencies. We have to set up those API keys and then we have to run the workflow. So first of all to install the

workflow. So first of all to install the dependencies I'm just going to say can you do this and then paste in exactly what it gave me. And so it's interesting it asks us to do that when it could have just done it itself. As you can see it's able to just run that command for us. So

once it did that now it says okay you have to go create two API keys. So we

need to create av file which is just going to be a copy fromv.ample.

So I'm actually just going to run this command and it's going to copy that file for us. And now we have an actualv file

for us. And now we have an actualv file right here. And so you can see it says,

right here. And so you can see it says, "Okay, cool. Now we need your enthropic

"Okay, cool. Now we need your enthropic key, your firecall key." And if I open up the it gives us those placeholders.

So basically all we have to do is go grab those keys and then put them in here instead of these placeholders that you can see right there. So first let's go to Enthropic. I'm going to go to my cloud developer platform. I'm going to create a new key. This one's going to be

called competitor analysis demo. We're

going to have this key right here. Copy

that and go into VS Code. Paste it in there. And then the next one we need to

there. And then the next one we need to get is the firewall key. So you can use the link in the description to go to firecraw. You can actually get 10% off

firecraw. You can actually get 10% off and 1,000 free credits if you use codeenate and use the link in the description. But I'm going to go to my

description. But I'm going to go to my dashboard here. And then all I have to

dashboard here. And then all I have to do is grab my API key from right here.

Paste it into this section. And then

what you have to do is make sure you save this file. So you could do crl s or you could just go file save. But now

that that file has been saved, we actually should be good to go ahead and run the workflow to see if it works. So

before I do that, you can see that we have this little thing down here which is context. So 23% of your context

is context. So 23% of your context remaining until autocompact. So, usually

when this goes over 60%, I usually just like to clear because there's this thing called context rot, which basically means the more and more you use one conversation, the worse the model kind of gets. So, we're going to clear the

of gets. So, we're going to clear the conversation. We're going to go ahead

conversation. We're going to go ahead and ask it to run competitor analysis and then we're going to go ahead and see what happens. Now, the one thing I did

what happens. Now, the one thing I did notice is that we still haven't given it a ton of information about our business.

So, I am a little confused why it hasn't asked about that, but we will see what happens. I'm going to keep it on bypass

happens. I'm going to keep it on bypass permissions mode to just see what it does. And I'm going to ask it to

does. And I'm going to ask it to generate a competitive analysis. and I'm

going to give it a really small amount of information about our business. Hey

Claude, I need you to help me run a competitor analysis. My business is

competitor analysis. My business is called Get Leads with AI and we basically help you scrape leads, build lead lists, and do personalized outreach at scale using AI. And we're starting to

see a lot of competitors pop up. So, I

want to understand our opportunities and what we need to be doing better. All

right. So, what happened there is I just shot off a prompt and I didn't explicitly say like, "Hey, go use your competitor analysis workflow." But what it's going to do is it's going to think about what we have. So you can see that it just searched through our workflows.

It searched through our tools. It said

we already have a competitor analysis workflow set up. Let me read how this works and let me just go do it. So let's

just see what it comes up with. I'll let

you guys know if we have any questions.

Otherwise I'll check in with you guys when we get that output. Okay. So here

we are getting some questions. So this

is the part where it realized it didn't actually have enough information about us yet. So what's your primary target

us yet. So what's your primary target for get leads with AI? We're just going to go with um we'll just say marketing agencies. For pricing I'm going to go

agencies. For pricing I'm going to go with credit based usage. What's your key differentiator? I'm actually going to go

differentiator? I'm actually going to go ahead and say other and I'm just going to say our key differentiator is an all-in-one platform. But make sure

all-in-one platform. But make sure you're saving all of this information that I'm telling you about my business somewhere in this project so I don't have to tell you it again. And so I'm pretty sure it would have done that either way because that's kind of the whole point here. But just to make sure that it does it for the sake of the

example, I wanted to show you guys that you have the ability to just tell it to do things. So got it. I'll save the

do things. So got it. I'll save the information. So that's all you have to

information. So that's all you have to do. And now it's going to continue on

do. And now it's going to continue on with its to-do list. And actually it does come up with some more questions.

So we're a single all-in-one product and our price range, let's just say 200 to 500 a month. Now this is good. I know

what you guys may be thinking is that's a lot of questions. Well, the thing is as you use it more and more, it gets smarter and smarter because each time you use it, you know, it has more information and you you give it feedback. So, yes, the initial setup may

feedback. So, yes, the initial setup may seem like a lot, but think about the questions it's asking and think about how good it's going to get now that it has all this info. So, you can see what it did is it created this file right here called business profile JSON. And

this is where it decided to store all of the information about our business. And

now, if we ever tell it something else and it needs to add like a new memory or fact about us, it will just go ahead and update this JSON file. Here's a great example of it fixing itself. So, it

basically went ahead and started looking up for competitors and it found an error. So, I see there's a uni-ode

error. So, I see there's a uni-ode encoding issue with the script on Windows. Let me fix that. It reads how

Windows. Let me fix that. It reads how to fix it and then it goes ahead and fixes it because there were some emoji characters or something like that. And

then it said, "Let me update it." And

what it's doing now is it's actually changing the script and changing the tool to make sure that that error doesn't happen again. It's also now created a new file called competitor list. So, it was able to do research and

list. So, it was able to do research and find different competitors like Apollo, Outreach, Clay, Instantly, Lemlist. And

now if it ever needs to save more information about different competitors, it will just put it here. All right,

looks like it's finishing up right now.

So it found some key insights. You're

positioned as a mid-market blah blah blah. Your eight main competitors, what

blah. Your eight main competitors, what you're doing right, critical gaps you need to address, top three recommendations. Let's see what those

recommendations. Let's see what those are. Add white labeling. Introduce $99

are. Add white labeling. Introduce $99

to $149 starter tier and double down on built for agency's positioning. So it

created three different files or sorry, four different files. It created the business profile, which we looked at. It

created the analysis, competitor data, and the PDF report. Wow. So, it created a new folder called competitors and it made an individual file for every single one of our competitors. So, that's

really cool. We can actually see a lot of data about them now. It created a folder called analysis history. So, this

is where we can see pretty much all of the data that it ran and got for this specific run. And now, of course, it has

specific run. And now, of course, it has the PDF. So, let's check out the final

the PDF. So, let's check out the final output. All right. So, here it is. Now,

output. All right. So, here it is. Now,

I can definitely say that these are my colors and the typography. So, that's

good. But, I don't see the logo. And I

really I think it's just because it is a white PNG logo. So, I bet that it's up here. I just think that we probably

here. I just think that we probably can't see it. But anyways, we'll see if we can fix that. For now, we've got executive summary, we've got business profile, we've got competitive landscape with feature analysis. We've got

competitor profiles, so high threat, medium threat. We've got all these

medium threat. We've got all these different companies with strengths and our advantages. And then we also have

our advantages. And then we also have our strategic recommendations at the end that we saw earlier. So, really, the problem with this report is that our logo isn't visible because it's white.

You can also see that it said that that run costed $143. So, not too bad. But

what I'm saying now is that's great, but we can't see the charts or logos. I'm

assuming because they're the same color as the background. Investigate and fix these issues. Now, typically I would put

these issues. Now, typically I would put this in plan mode and go back and forth a little bit again, but for the sake of the demo, I want to see how good it's able to do when we just let it run with a super super vague request, as you can see. All right, so here's the thing. It

see. All right, so here's the thing. It

said the PDF generator has several problems and listed those out. And now

it's going to go ahead and fix those issues. So once again, this is just me

issues. So once again, this is just me telling you guys about you have to run the workflow a few times to discover those holes. And once you discover those

those holes. And once you discover those holes, it'll fix them. And then you'll get to a place where you have more of a battle tested workflow. Okay, so it regenerated the PDF and once again we talked earlier about the caching. It's

saving all the data it had already. So

it doesn't have to do a new search, which is really good. And in the future, it will still do current research, but it already has the business profile about all of our competitors and it's already researched them. So now it just has to see if there's anything new. But

anyways, let's open up the new report and see how it looks. All right, so here's the new report. Okay, so we've got competitive intelligence report, get leads with AI, today's date, and now we do see the logo. So executive summary, we can see this business profile once

again, competitive landscape, competitor profiles. However, there we go. We can

profiles. However, there we go. We can

finally see a pricing analysis chart which looks pretty solid. Cool. So, at

this point, it would just be a matter of making tweaks cuz obviously this isn't perfect. There's some things we might

perfect. There's some things we might want. We might want more details cuz

want. We might want more details cuz like up here, you know, it's pretty it's not super super wordy and super detailed. So, maybe you like that, maybe

detailed. So, maybe you like that, maybe you don't. At this point, you've got

you don't. At this point, you've got enough info and you've got every tool you kind of need and you just go back and forth and ask for feature enhancements. And once again, you can do

enhancements. And once again, you can do that all with completely natural language. But you can see I didn't have

language. But you can see I didn't have to go look at any API documentation. I

didn't have to figure out how to prompt something to run a competitive analysis.

I didn't have to go figure out how to generate these PDF reports or charts. It

handled all of that for me. So, I hope you guys were able to follow along and I hope you're excited to go build your first agentic workflow. So, as you can see, building your first agentic workflow is actually so simple. But if

you still have doubts about what you need to do or where to start, you can always join my community. In here, you can get every single resource that I've ever used in my YouTube videos. All the

templates, the workflows, the prompts, the files, all completely free. Also, if

you ever have a problem making something work, you've got tutorials in there on different topics, and the support of over a quarter million people willing to help you. The link for this is down in

help you. The link for this is down in the description. And if you want to turn

the description. And if you want to turn these skills into a business, I have tutorials and tips to help you make your first dollar building AI automations.

But anyways, that's going to do it for today. If you guys enjoyed the video or

today. If you guys enjoyed the video or you learned something new, please give it a like. It definitely helps me out a ton. And as always, I appreciate you

ton. And as always, I appreciate you guys making it to the end of the video.

I'll see you on the next one. Thanks

everyone.