github star gitee star atomgit star PyPI Downloads AI Programming AI Community

Hello everyone, this is programmer Wan Feng actively working on various AI projects.

Over the past month, I researched 100+ AI projects on GitHub, Product Hunt, and major domestic platforms.

With one goal: Find the AI directions that truly make money in 2026.

Today I'm sharing my findings—these 3 directions have the biggest opportunities.


Direction 1: AI Agent Services (Monthly Income 1-100k)

What are Agent services?

Help businesses or individuals build AI agents to automate specific tasks.

Real cases:

I know a developer who specializes in building customer service agents for e-commerce sellers:

  • Auto-reply common questions
  • Handle return/exchange requests
  • Aggregate customer feedback

Pricing model:

  • Setup fee: 5000-20000/set
  • Monthly maintenance: 500-2000/month

He currently has 20 clients, monthly income 40k+.

Why can it make money?

  • Real demand: Every business has repetitive work
  • Moderate barrier: Requires programming + AI knowledge, but not too difficult
  • Scalable: One system can be sold to multiple clients

What skills do you need?

  • Python basics
  • OpenClaw or similar frameworks
  • Basic business understanding

Direction 2: AI Content Industrialization (Monthly Income 5k-50k)

What is content industrialization?

Use AI to batch-produce high-quality content instead of manually writing articles one by one.

Real cases:

A friend who does self-media, operating 10 accounts:

  • AI generates topics
  • AI writes first drafts
  • Manual polish and publish
  • Multi-platform distribution

Before, he managed 1 account alone. Now he manages 10 accounts.
Total income increased 5x.

Specific approach:

  1. Find popular niches (emotional, career, parenting)
  2. Build content template library
  3. Use AI for batch generation
  4. Manual review and optimization
  5. Matrix-style publishing

Key success factors:

  • Prompt Engineering
  • Quality control process
  • Multi-platform operations experience

Direction 3: AI Training and Consulting (Monthly Income 200-200k)

Why is this direction hot?

AI is developing too fast—there's always someone wanting to learn new things.

Market status:

  • Enterprise training: 5000-50000/session
  • Personal courses: 199-2999/person
  • Consulting: 500-2000/hour

Real cases:

I'm an example myself. Started doing AI programming training last year:

  • Online courses: 3000+ cumulative students
  • Enterprise training: 2-3 sessions monthly
  • Paid community: Annual membership 500+

Not getting rich overnight, but stable income and getting easier over time.

Why can training continuously make money?

Because AI is evolving—there's always new things to learn:

  • GPT-4 → GPT-5
  • Claude 3 → Claude 4
  • New tools emerging constantly

As long as you keep learning, there's always content to teach.


Comparison of 3 Directions

DirectionStartup DifficultyIncome CeilingSustainability
Agent Services⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐
Content Industrialization⭐⭐⭐⭐⭐⭐⭐⭐
Training Consulting⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐

My suggestions:

  • With technical background → Do Agent services
  • With content experience → Do content industrialization
  • With desire to teach → Do training consulting

Can also combine: First do services to gain experience, then turn into courses to sell.


Pitfall Guide

A few common pitfalls:

Don't chase hot topics too closely
Sora is hot today so you do video, MusicLM is hot tomorrow so you do music.
Chasing around, never accumulate anything.

Find one direction and go deep
Being excellent in one niche is more valuable than being mediocre in everything.

Don't ignore basic skills
Many people want to skip learning and go straight to making money, but end up unable to produce good work.

Invest in yourself first, then consider monetization
Skills are principal, ability is leverage.


How to Start?

No matter which direction you choose, you need basic skills:

Required Skills Checklist

  • ✅ Python programming (basic syntax + common libraries)
  • ✅ AI tool usage (ChatGPT, Claude, etc.)
  • ✅ Prompt Engineering (efficient communication with AI)
  • ✅ Data analysis (understand data, make decisions)

Learning Path

  1. 2 weeks: Python basics
  2. 1 week: AI tool practice
  3. 1 week: Go deep in one direction
  4. Continuous: Learn by doing, grow through practice

If you want to quickly master these basic skills, I recommend my course:

"AI Python Zero Foundation Practical Camp"

🎓 AI 编程实战课程

想系统学习 AI 编程?程序员晚枫的 AI 编程实战课 帮你从零上手!