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Building My First AI Agent: Lessons from 30 Days of OpenClaw

Introduction

30 days ago, I started building my first AI Agent using OpenClaw. Here's what I learned.

What is OpenClaw?

OpenClaw is an open-source framework for building autonomous AI agents. It runs on your own hardware (I'm using a Mac mini) and gives you full control over your AI's capabilities.

My Setup

  • Hardware: Mac mini (M1)
  • Models: Qwen3.5-plus (free), GPT-5.4, Claude Opus 4.6
  • Channels: Telegram
  • Skills: Custom-built for web search, browser automation, file management

Key Lessons

1. Start Simple

Don't try to build AGI on day one. Start with simple tasks:

  • Answer questions
  • Search the web
  • Save files

2. Model Selection Matters

I learned to use different models for different tasks:

  • Free models for chat and simple tasks
  • Premium models for complex reasoning
  • This saved me 80% on API costs

3. Persistence is Key

Agents need memory. I implemented:

  • Daily logs (memory/YYYY-MM-DD.md)
  • Long-term memory (MEMORY.md)
  • Project-specific knowledge (projects/)

4. Safety First

I established rules before giving my agent more power:

  • No destructive commands without approval
  • No external communications without review
  • Budget limits for API spending

The Result

After 30 days, my agent "Ruta" can:

  • ✅ Manage my calendar and reminders
  • ✅ Search and summarize information
  • ✅ Write and publish content
  • ✅ Monitor prices and alert me
  • ✅ Run scheduled tasks (heartbeats)

What's Next?

  • Building an Agent Team (multiple specialized agents)
  • Adding browser automation for complex workflows
  • Exploring monetization opportunities

Resources


Have you built your own AI agent? Share your experience in the comments!

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