description

Filling out college applications based on "this major seems good," choosing a graduate program based on "a senior student said it's okay," and changing careers based on "it seems to be quite popular"—then you graduate to find that your major has the lowest employment rate, the industry is declining, and AI can already do what you learned. Throw your scores/background/interests at it, and it uses data to speak for itself—entry barriers, median salaries, ceilings in five years, and whether this industry will be replaced by AI. It's not about listening to it, but about letting you see the data for each path and make your own choice. ✨ Core Competencies 1. Multi-stage Adaptability: Different analytical frameworks for different stages including college application, postgraduate entrance exams, studying abroad, career changes, and career planning. 2. Data-driven: Entry barriers + median salary + 3-5 year growth rate + industry ceiling, no adjectives needed. 3. Path Comparison: At least 3 optional paths, each fully broken down in terms of barriers, prospects, and risks. 4. Pitfall Warnings: The most common choice traps—which majors sound good but have poor employment rates, which industries are declining. 5. Actionable First Step: No more "overthinking," just a concrete action you can start today. 📱 Applicable Scenarios - High school students/parents filling out college applications: What can I get into with my score? Which majors lead to good employment? - University students taking postgraduate entrance exams/job hunting: What are the prospects for my major? Should I switch majors/career paths? - Working professionals changing careers: Is it worth it to switch tracks at 30? Where is the door? - Parents planning for their children: Replacing "I think this major is pretty good" with data ⚠️ Disclaimer: The analysis is based on publicly available information and does not constitute the sole basis for decision-making. Policies, markets, and individual circumstances are all subject to change.