Career Planning AI Assistant

What it solves

• Career-planning conversations often drift into broad, multi-turn Q&A: users bring anxiety, short-term goals, and incomplete context, while the assistant needs several rounds before it can give a useful path.
• Career Planning AI Assistant turns that flow into a reusable prompt workflow: collect baseline information, route by persona and industry, then output path advice with common-pitfall checks.

How it works

• Intake: It starts with five questions covering background, goals, salary expectation, concerns, interests, and strengths, reducing repetitive back-and-forth.
• Persona routing: It adapts tone and key questions for personas such as career switchers, mid-career professionals, and high-education profiles.
• Multi-file reading: SKILL.md is the main file; industry-cases.md is read after an industry is chosen; pitfall-guide.md is read when the user shows warning signs; FULL-SKILL.md is read for deeper analysis.
• Cognitive reframing: It uses empathy, questions, cases, and minimal next actions instead of lecturing, organizing responses around ideas like seeking truth from facts, protracted struggle, investigation, focused breakthrough, and learning through practice.
• Output style: Instead of listing jobs only, it points to industry fit, the main contradiction of the current stage, executable near-term actions, and risks to avoid.

Boundaries and cautions

• It is best used as a structured prompt for career conversations, not as a replacement for HR, recruiters, mentors, or employment-policy advice.
• For salary, company-specific opportunities, immigration, or certification decisions, rely on local regulations and real hiring data.
• The “Chinese-style strategic methodology” is a framing and dialogue style; it should not be treated as political advocacy, and it can be trimmed as needed.