I Spent 3 Days Building an AI Employee That Works for Me

Hello everyone, this is programmer Wan Feng.

Recently the term "AI Agent" has been particularly hot.

But honestly, after reading many articles, I was still confused: What exactly is an Agent? What does it have to do with me?

Until I built one myself—that's when I understood—This thing can actually help you get work done.

Today sharing my hands-on experience, teaching you step by step from zero.

What Exactly Is an AI Agent?

Don't be intimidated by the jargon, keep it simple:

Agent = Large Model + Tools + Memory + Autonomous Decision-Making

Regular ChatGPT: You ask a question, it answers, done.

AI Agent: You give it a goal, it autonomously breaks down steps, calls tools, executes, provides feedback, adjusts, until completion.

Like an intern—explain the task clearly, and they figure out how to get it done.

What Agent Did I Build?

Requirement was simple: Every morning at 8 AM, automatically organize my messages and to-dos, send me a daily report.

Sounds simple, but involves:

Reading WeChat unread messages
Checking Feishu calendar
Checking GitHub Issues
Aggregating into structured report
Sending to my email

Before: Manually open 4 apps, copy-paste, at least 20 minutes.

Now: Fully automatic, I just look at the result.

Building Process (Super Detailed)

Step 1: Choose Framework

There are many Agent frameworks:

LangChain (most popular, but a bit heavy)
AutoGPT (fully automatic, but easy to go off track)
OpenClaw (lightweight, easy to get started)

I chose OpenClaw because of clear documentation and active community.

Step 2: Define Agent Capabilities

What I needed this Agent to do:

Read WeChat messages (using itchat library)
Query Feishu calendar (Feishu API)
Get GitHub Issues (GitHub API)
Generate daily report (GPT-4)
Send email (SMTP)

In OpenClaw, these are called "Skills."

Step 3: Write Prompt

This is the most critical step. Tell the Agent:

Who you are (a daily report assistant)
Your task (collect information and generate daily report every morning)
Your workflow (A first, then B, then C)
Output format (Markdown, including which sections)

You are a daily report assistant. Every morning at 8 AM, you need to:

1. Read my WeChat unread messages, filter important contacts
2. Check today's Feishu meeting schedule
3. Check Issues assigned to me on GitHub
4. Summarize into a daily report in concise language
5. Send to my email

Daily report format:
- Today's pending items (by priority)
- Meeting reminders
- Messages needing reply
- GitHub tasks

Step 4: Debug and Optimize

First run, Agent missed a few WeChat group messages.

Checking found: Group whitelist not configured.

Added configuration, ran again, perfect.

This is the core of Agent development: iterative optimization.

Running Results

Every morning at 8:05, I receive the email on time:

【Daily Report】2026-02-28

🔴 High Priority
- Customer A asking about pricing (WeChat, 2 hours ago)
- Bug #234 needs fixing today (GitHub)

📅 Today's Meetings
- 10:00 Product Review (Feishu)
- 14:30 Tech Sharing (Offline)

💬 Messages Awaiting Reply
- Student Xiao Ming: Course inquiry (WeChat)
- Colleague Xiao Hong: Document confirmation (DingTalk)

⏳ GitHub Tasks
- Issue #234: Order export anomaly (Due today)
- PR #56: Awaiting Review

Clear at a glance, no longer need to scroll through 4 apps.

Advanced Play

After basic version was working, I added several features:

Auto-Reply Common Questions

Students often ask "how to install Python"—I let Agent identify keywords and auto-send tutorial links.

Monitor Competitor Updates

Scheduled scraping of competitor websites, notify me of any updates.

Data Report Generation

Every Monday auto-generate last week's data report, send directly to group.

Each new feature is just 1-2 hours of development time.

Pitfalls I've Encountered

❌ Prompt not clear enough → Agent misunderstood task, needed repeated debugging
❌ Permissions not configured → Couldn't read some data, troubleshooting took half the day
❌ No error handling → If one API crashed, entire process stalled

✅ Solution: Add logging, add retries, add fallback plans

Who Is Suitable for Agent Development?

✅ Programmers —— Next big thing, get ahead early
✅ Product Managers —— Understand technical boundaries, design better products
✅ Operations/Sales —— Automate repetitive work, 10x efficiency
✅ Entrepreneurs —— Achieve AI capabilities at low cost

No need to be an algorithm expert, but basic programming ability is required.