Here's the deal. Most "AI agent" tutorials are written by developers for developers. They assume you know Python, APIs & terminal commands. That's not you. You're a founder. You need results, not a programming course.
I'm Johann. I'm 21. I sold my first company at 20 & now I run a SaaS called DMpro. About half my business operations are handled by an AI agent named Jars. Morning briefings, CRM, lead outreach, overnight code builds, SEO, research. All handled by AI.
I didn't write a single line of code to make that happen. And you won't need to either.
This guide breaks down exactly how to build your first AI agent from scratch. The same approach I teach inside the AI Operators community.
What is an AI agent (and why it's not ChatGPT)
First, let's kill the confusion. An AI agent is NOT a chatbot. It's not ChatGPT. It's not "a better prompt."
An AI agent is a persistent system that can:
- Run in the background without you sitting there
- Access your tools, APIs & databases
- Complete multi-step workflows automatically
- Remember context across sessions
- Take real actions (send emails, update CRM, ship code)
ChatGPT is like texting a smart friend. You ask, they answer, done. An AI agent is like hiring an employee. You give them a role, responsibilities & tools. They do the work without you hovering over them.
Read the full AI Agents vs ChatGPT comparison if you want the detailed breakdown.
Before (ChatGPT)
- You type a prompt every time
- No memory between sessions
- Can't access your tools
- Just generates text
- You're always in the loop
After (AI Agent)
- Runs on autopilot 24/7
- Remembers everything
- Connected to your stack
- Takes real actions
- Works while you sleep
The tools you need (all of them)
You only need two tools to build an AI agent. Not 47 SaaS subscriptions. Two.
1. Claude Code
Claude Code is Anthropic's coding agent. It's basically a developer that works for you in the terminal. You tell it what to build in plain English & it writes, debugs & ships the code.
Why Claude Code? Because it's the best AI coding tool available right now. It understands context better than anything else. And it can handle complex, multi-file projects without losing track of what it's doing.
Cost: ~$100/month for the API. Worth every penny when you see what it builds overnight.
Full setup guide: Claude Code Setup Guide
2. OpenClaw
OpenClaw is the open-source framework that turns Claude Code into a persistent agent. Think of it as the operating system for your AI employee. It handles:
- Memory: Your agent remembers past conversations & decisions
- Tool access: Connect to your CRM, email, calendar, whatever
- Scheduling: Run tasks on autopilot (morning briefings, overnight builds)
- Multi-step workflows: Complex tasks that take multiple actions to complete
Full tutorial: OpenClaw Tutorial for Beginners
Step 1: Define what your agent should do
Don't start with the tools. Start with the problem.
Grab a piece of paper (or a notes app, whatever). Write down every repetitive task you do in your business. Things like:
- Checking email every morning
- Updating your CRM with new leads
- Scoring leads based on engagement
- Writing outreach messages
- Following up on deals
- Scheduling meetings
- Summarizing reports
- Doing competitor research
Now pick ONE. Not five. One. The one that eats the most time or annoys you the most. That's your first agent's job.
For most people, I recommend starting with a morning briefing agent. It's simple, immediately useful & shows you how the whole system works.
Step 2: Set up Claude Code
The setup takes about 15 minutes. Here's what to do:
That's basically it. You've got Claude Code running. Now you can talk to it in plain English & it will build whatever you describe.
Detailed walkthrough: Claude Code Setup Guide
Step 3: Set up OpenClaw
OpenClaw gives your agent persistence. Without it, Claude Code is just a one-off tool. With it, you've got a full AI employee.
Full step-by-step: OpenClaw Tutorial for Beginners
Step 4: Build your first agent (morning briefing)
Here's where it gets fun. You're going to build an agent that scans your inbox, CRM & calendar every morning and gives you a summary.
Inside OpenClaw, you create an agent config. This is basically a job description for your AI employee. In plain English.
# agent-config.yaml
name: "morning-briefing"
schedule: "0 7 * * *" # 7am daily
description: |
You are my morning briefing agent.
Every morning, do the following:
1. Check my inbox for important emails
2. Scan my CRM for new leads & deal updates
3. Review my calendar for today's meetings
4. Summarize everything in a Slack message
Keep it brief. Bullet points. No fluff.
tools:
- gmail
- hubspot
- google-calendar
- slack
That's it. That's your agent config. You're telling the AI what to do, what tools it has access to & when to run. No code. Just a description of the job.
Step 5: Connect your tools
Your agent needs access to the tools it's going to use. OpenClaw handles this through integrations. You basically:
- Add your Gmail API credentials
- Connect your CRM (HubSpot, Pipedrive, whatever)
- Link your calendar
- Set up Slack webhook for delivery
Each integration takes about 5 minutes. OpenClaw has guides for all the popular tools.
Step 6: Test & iterate
Run your agent manually first. See what it produces. Is the briefing useful? Too long? Missing stuff?
Tweak the config. Add more specific instructions. "Focus on emails from @clients.com" or "Only flag leads with engagement score above 50."
This is the beautiful thing about AI agents. You iterate by changing the English description, not by debugging code. It's like giving feedback to an employee.
Step 7: Scale to more agents
Once your morning briefing is running smoothly, you'll want more. That's natural. Here's what to build next:
- Lead outreach agent: Scores leads, writes personalized DMs, queues them for sending
- Customer follow-up agent: Tracks deals & sends timely follow-ups
- Overnight build agent: Ships code features while you sleep
- Research agent: Monitors competitors, finds opportunities, summarizes findings
Each agent follows the same pattern. Define the job. Connect the tools. Test. Iterate. Done.
My agent Jars now handles all of these. It started as a morning briefing. Six months later it runs half my business.
Real results from real people
These aren't projections. This is what happened when I built Jars for DMpro. The $48k pipeline was generated overnight through automated lead outreach. The 4 hours saved is every single day. And I closed a $1,500 consulting deal helping someone else set up the same system.
Common mistakes to avoid
I've seen a lot of people try to build AI agents & fail. Here's why:
Trying to automate everything at once
Start with one task. Get it working perfectly. Then expand. Don't try to build a super-agent on day one.
Not being specific enough
Vague instructions produce vague results. "Handle my emails" is bad. "Check my inbox every morning, flag emails from @clients.com, summarize anything with 'urgent' in the subject" is good.
Skipping the test phase
Always run your agent manually before putting it on autopilot. Check the output. Make sure it's actually useful. Then automate.
Using the wrong tools
There are dozens of AI agent frameworks. Most of them are overengineered or half-baked. Claude Code + OpenClaw is the combo I've tested & trust. Stick with what works.
What's next?
You've got the blueprint. Now here's how to actually make it happen:
- Set up Claude Code (15 minutes)
- Install & configure OpenClaw (30 minutes)
- Build your morning briefing agent (1-2 hours)
- Join AI Operators to get templates, help & feedback
The community is free. You'll get Johann's exact agent configs, production-tested templates & direct access to ask questions.
If you're a SaaS founder, agency owner, freelancer or content creator, there are specific guides for your situation too.
Stop prompting. Start operating.