Hello everyone, this is programmer Wan Feng actively working on various AI projects.
Recently AI Agents have been particularly hot, with related projects dominating GitHub trending daily.
Many people ask me: What exactly is an Agent? Can ordinary people use it?
Today I spent 1 hour building one—now it handles 80% of my repetitive work every day.
After reading this article, you can build one too.
What Is an AI Agent? Explained in One Sentence
Traditional AI: You ask a question, it answers.
Agent is: You give it a goal, it figures out how to complete it on its own.
For example:
- Traditional AI: "What's the weather in Beijing today?" → "Sunny, 25 degrees"
- Agent: "Help me plan my trip to Shanghai tomorrow" → Check weather→Check flights→Check hotels→Generate complete plan
Agent = AI brain + Tool usage ability + Autonomous decision-making
What Does My Agent Do?
The Agent I built handles daily affairs specifically:
Scenario 1: Auto-reply WeChat messages
- Identify common questions ("Are you there?" "How much?")
- Auto-reply based on knowledge base
- Complex issues transfer to human
Scenario 2: Daily morning news generation
- Auto-grab news at 8 AM
- Filter areas I care about (AI, Python)
- Generate summary sent to Feishu
Scenario 3: Automatic file organization
- Monitor download folder
- Classify by type (documents, images, installers)
- Rename and move to corresponding directory
These originally took me 1-2 hours daily, now fully automated.
How to Build? Super Simple
Using OpenClaw framework, 30 lines of configuration:
1 | # agent.yaml |
Then start:
1 | openclaw run agent.yaml |
That's it—Agent starts running.
Core: How to Make Agent Smarter?
The key is two things:
1. Tools
Tell the Agent what it can use:
- Send WeChat messages
- Read Excel files
- Search web information
- Call API interfaces
More tools = stronger Agent capabilities.
2. Memory
Let the Agent remember:
- Who you are (identity, preferences)
- What you've talked about (context)
- What methods work (experience)
An Agent with memory understands you better over time.
Advanced Play: Multi-Agent Collaboration
For more complex scenarios, use multiple Agents with division of labor:
Content Creation Team Example:
- Topic Agent: Monitor trending topics, find topics
- Writing Agent: Write articles based on topics
- Review Agent: Check content quality
- Publishing Agent: Distribute to various platforms
They collaborate with each other, like a small team.
Who Is Suitable for Agents?
✅ Office workers —— Automate repetitive work, leave on time
✅ Self-media creators —— Auto collection, writing, distribution
✅ Small business owners —— Low-cost customer service, operations automation
✅ Developers —— Quickly build prototypes, validate ideas
❌ Complete beginners —— Should learn basic programming first
❌ Those with overly high expectations —— Agents aren't all-powerful, need debugging and optimization
Recommended: AI Python Zero Foundation Practical Camp
If you want:
- ✅ Master Agent development basics
- ✅ Learn to use OpenClaw to build intelligent agents
- ✅ Build your own automation systems
- ✅ Seize the opportunity in the AI era
I recommend "AI Python Zero Foundation Practical Camp":
Course includes:
- 📚 Python basics (2 weeks to get started)
- 🤖 OpenClaw framework usage
- 🛠️ Agent development practice (build intelligent agent from 0 to 1)
- 💡 Multi-Agent system design concepts
🎁 Limited-time benefit: First 100 to sign up get "Python Programming: From Beginner to Practice" physical book
Related Reading
- 3 Days Testing Claude Code: This AI Programmer Made Me Both Happy and Scared
- I Built an Excel Robot - Now I Sleep 1 More Hour Every Day
- 3 Methods I Used to Earn 10,000+ Yuan Monthly with AI
PS: AI Agent is the future trend—early learners benefit most. Get in now and you're a pioneer.
