Summary of the Core Content
This news article discusses a platform called “Miaozhao Square,” which features various “smart tools” created by workers to solve common problems in their daily tasks using AI. These seemingly simple tools are giving rise to three new professions: Miaozhao Engineers (who break down work challenges into steps that AI can execute), Miaozhao Hunters (who adapt general tools for specific industries), and Miaozhao Assessors (who test and recommend effective tools). These professions do not require programming skills; they rely on a deep understanding of the business process to create useful tools. In the future, these roles could generate income through platform fees or subscription models, representing new opportunities for ordinary people in the AI era.
I. “Miaozhao Square”: A Platform for Workers to Share and Solve Problems
Miaozhao Square functions like an “AI tool marketplace,” where users share lightweight tools designed to address specific work challenges. For example:
- Construction Engineer CQ: Instead of spending days filtering bid data from five provinces, he broke down the process into steps that AI could handle (automatically opening web pages, extracting data, and organizing it in Excel), completing the task in just 20 minutes.
- Financial Writer Chen Lin: Previously, it took her half a day to extract video captions from videos; now, with the “Bilibili Video Caption Extraction” tool from Miaozhao Square, she can do it in minutes and has saved several similar tools for future use.
These tools address niche needs that large companies tend to overlook, such as HR staff filtering resumes, administrative staff preparing reimbursement forms, or writers searching for materials. Although these tasks are trivial, they are time-consuming for individual workers.
II. Three New Professions: Becoming an “AI Toolmaker” Without Coding
None of these three professions require programming skills; the key is a combination of business understanding and problem-solving abilities:
1. Miaozhao Engineers: They identify their own work challenges and share solutions with others. For instance, CQ and art student Xiaozeng used AI to solve complex quantitative analysis problems for their graduation thesis, turning the most time-consuming steps into easily reusable tools.
2. Miaozhao Hunters: They modify general tools to fit specific industries. Users like Chen Lin adapt existing tools (e.g., resume filters) to meet the needs of internet operations roles by adjusting prompts and optimizing output formats.
3. Miaozhao Assessors: They evaluate tools to determine their reliability and suitability for different environments, providing users with recommended lists (e.g., “Top 5 Excel Tools of the Week”) to save time on trial and error.
III. Why These New Professions Are Successful
There are three main reasons for their success:
1. Real, Unmet Needs: There are many small, yet critical work challenges that large companies neglect, but workers urgently need solutions.
2. Lower Barriers to Entry: AI tools like Tabbit enable non-programmers to create tools using natural language.
3. Reliability of Verified Tools: While AI can generate many ideas, only those that have been tested and adapted for specific use cases are truly valuable.
IV. Can These Professions Be Profitable in the Future?
There are already precedents for generating income from these professions:
- GitHub: Initially a place for programmers to share code, it later became a platform where high-profile authors were recruited by recruiters, with some earning thousands of dollars per month from sponsorships.
- Notion Templates: Users shared their work templates, and the company later launched a marketplace, allowing some users to earn millions of dollars annually from selling them.
For Miaozhao Square, potential revenue models include:
- Platform Fees: The platform could charge fees for customized tools created by users, with a share going to the platform and the creator.
- Creator Incentives: Assessors could earn money through traffic or subscription fees.
- Crowdsourcing: Companies could post challenges, and engineers could develop custom tools in exchange for payment.
The core competitiveness lies no longer in programming skills but in the ability to identify problems, break them down clearly, and build trust with users—skills that remain in high demand in the AI era.
Conclusion: Opportunities for Ordinary People
In the past, creating tools required programming knowledge. Now, as long as you understand your industry’s challenges, you can use AI to develop useful tools. These new professions are still emerging, but those who dare to try out new ideas may reap early benefits. For example, CQ’s tool has been adopted within his department, and Chen Lin’s tools are being used by colleagues, demonstrating their value. As the platform matures, these roles could become stable sources of income.