Hello everyone, I'm Programmer Wanfeng.

Recently helped a student review a resume and discovered a very common problem:

Resume writes "Proficient in Python" "Familiar with machine learning" "Master data analysis"...

But when asked "Have you made any projects yourself?"

8 out of 10 people say: No.

Why Do Interviewers Value Project Experience Most?

I've interviewed quite a few people and helped many fans revise resumes.

One pattern is particularly obvious:

People with project experience find jobs easier; people without project experience, resumes sink without trace.

The reason is simple:

  1. Project = Proof of ability: Grammar can be memorized, but if you can't make a project, you can't
  2. Project = Precipitation of experience: Interviewers want to know if you can solve actual problems
  3. Project = Talking points in interviews: With projects, you're not afraid when asked "What technical difficulties have you encountered"

So, everyone who wants a tech job needs at least one presentable project.

In 2026, What Kind of Projects Add the Most Points?

After observing many award-winning projects in AI programming competitions this year, I discovered a trend:

Projects made with AI tools, with actual application value, that solve real problems are most favored.

Specifically, these types of projects are currently popular in the job market:

1. AI Automation Office Tools

Direction: Use Python + AI to automatically handle daily office tasks

Examples:

  • Scripts that automatically generate Excel reports
  • Tools for batch processing Word documents
  • Assistants that automatically send emails
  • Crawl competitor data and generate analysis reports

Extra points: Strong practicality, can directly improve work efficiency, interviewers understand at a glance

2. AI Data Analysis Assistant

Direction: Use Python + AI to quickly analyze data and generate conclusions

Examples:

  • Tools that automatically clean and organize data
  • Automatically generate charts and reports based on data
  • Trend analysis models predicting certain indicators

Extra points: Data ability is a hard skill, financial institutions, e-commerce, operations companies all compete for these

3. AI Content Creation Tools

Direction: Use AI to batch generate content, auto-publish

Examples:

  • Tools that automatically generate Xiaohongshu/WeChat public account copy
  • Scripts for batch generating product descriptions
  • Multi-platform content distribution assistant

Extra points: Content operations ability + technical ability combination, high scarcity

4. AI Agent Intelligence

Direction: Use AI toolchain to build automated workflows

Examples:

  • Robots that automatically answer customer service questions
  • Assistants that regularly crawl news and organize summaries
  • Butler that automatically organizes files and to-dos

Extra points: Represents the most cutting-edge technical direction, interviewers will think you're very forward-looking

How to Make a Small Tool from 0 to 1?

I'll explain using an actual case: How to use AI tools, start from scratch to make a "Auto-generate Weekly Report" small tool.

Step 1: Clarify Requirements (5 minutes)

The problem I want to solve is:

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