Why Years of Experience Evaluation Fails
Are you really identifying top engineering talent by asking "3 years Ruby, 3 years JS"? After 5 years in HR and transitioning to engineering, I discovered the fundamental flaw: years of experience with a language correlates poorly with actual execution ability. As CTO hiring 200+ engineers annually, I have proven that GitHub portfolio evaluation (AI-powered analysis) reveals true capability far better than resume years.
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Three Truths Language Experience Does Not Show
1. Repeating same year 3 times: Engineers stuck at same skill level without learning new patterns. 30%+ of "Ruby 5 years" candidates still write Rails 4.2 style code.
2. Maintenance only, zero design experience: "3 years experience" may mean only fixing existing code, never designing from scratch.
3. Outdated tech stack: Stopped at Ruby 2.2 (2015), completely unaware of Ruby 3.x features.
Contrast: 6-month self-taught became top performer
Best engineer I hired: zero professional experience, but 50+ personal projects on GitHub showing exceptional learning velocity, problem-solving, 90%+ test coverage, detailed README, continuous refactoring.
5 Key GitHub Portfolio Evaluation Points
Framework used for 200+ annual hires (100 points total):
| Criterion | Points | Time |
|---|---|---|
| 1. Commit History Quality | 20 | 5min |
| 2. Code Quality & Design | 25 | 10min |
| 3. Git Operations | 20 | 3min |
| 4. Documentation | 15 | 3min |
| 5. Learning Velocity | 20 | 5min |
1. Commit History Quality (20pts)
Commit history visualizes thought process. Evaluate message clarity, granularity, workflow. Excellent: "feat: Add category filter to product search - PostgreSQL FTS index - Search speed 50ms→15ms". Poor: "fix", "update". Red flags: all commits same timestamp (copy-paste suspect), 3+ month gaps, all files in 1 commit.
2. Code Quality & Design (25pts)
Most critical. 15min reveals 80% of capability. ①Directory structure (5pts): controllers/services/repositories separation. ②Error handling (5pts): custom error classes, proper logging, error type classification. ③Maintainability (10pts): magic numbers as constants, DRY functions, Why comments, type safety. ④Test code (5pts): normal/edge/error cases covered, 80%+ coverage.
3. Git Operations (20pts)
Beginner (5pts): all commits to main directly. Intermediate (12pts): feature/fix branches, basic PRs. Advanced (20pts): Git Flow, detailed PR descriptions, self-review evidence, conflict resolution history. Excellent PR includes: change summary, test results, technical decisions, breaking changes, review points.
4. Documentation (15pts)
README.md indicates communication ability. Required (2pts each): project overview (why built), tech stack, setup, execution. Bonus (1.5pts each): problem statement, lessons learned, demo URL/screenshots, future improvements (tech debt awareness).
5. Learning Velocity & Problem Solving (20pts)
①Tech breadth (7pts): Full-stack+infra=7pts, specialized=4pts, single tech=2pts. ②New tech adoption (7pts): latest tech adoption=7pts, stable versions=4pts, legacy only=2pts. ③Problem-solving evidence (6pts): Issue/PR technical discussions, troubleshooting records, quantitative problem measurement→cause identification→solution→result evaluation.
Interview Deep-Dive Questions
About Projects
- "Why did you build this?"→problem definition ability
- "Most challenging part and how solved?"→problem-solving process
- "What would you change if rebuilding?"→tech debt awareness, growth mindset
- "(pointing at commit) Why split this way?"→thought granularity, design judgment
About Technology
- "Performance/security considerations?"→non-functional requirements awareness
Practical Evaluation Sheet
| Item | Points | Score | Notes |
|---|---|---|---|
| Commit History | 20 | 18 | Clear messages, good granularity |
| Code Quality | 25 | 20 | Good design, tests slightly lacking |
| Git Operations | 20 | 15 | Has PRs but brief descriptions |
| Documentation | 15 | 12 | Basic info present |
| Problem Solving | 20 | 17 | High learning motivation |
| Total | 100 | 82 | Interview Pass |
Hiring criteria: 70+ for interview, 80+ for high rating
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Why Engineer Hiring Evaluation AI Assistant is Effective
Moving beyond the "language × years" evaluation framework requires a multifaceted assessment approach. Our AI Assistant evaluates candidates from three perspectives: GitHub portfolio analysis, technical interview assessment, and practical capability judgment to visualize their true competence.
Specific Support Features
- GitHub Portfolio Analysis: Comprehensive evaluation of commit history, code quality, and project structure to assess practical abilities
- Interview Question Design: Provides essential skill-focused questions beyond "language × years" metrics
- Standardized Evaluation Criteria: Establishes unified assessment standards within teams to prevent hiring bias
- 24/7 Consultation: Access professional advice at any stage of the recruitment process
How It Works
- Input Candidate Information: Enter GitHub account, background, and target position
- Run AI Analysis: Generate comprehensive evaluation report in minutes
- Develop Interview Strategy: Review AI-recommended interview questions and evaluation points
- Final Decision Support: Make informed decisions with overall scores and hiring risk analysis
"I couldn't assess GitHub profiles effectively, but the AI analysis clarified candidates' strengths and weaknesses. Interview questions were spot-on, eliminating post-hire mismatches."
(Startup CTO, 30s)SME Focus Points
1. Broad skillset: Frontend/backend/infra coverage. 2. Autonomy: Issue creation, self-directed refactoring. 3. Client communication: README understandable to non-engineers.
Success & Failure Cases
✅Success: 0 years→Team lead in 6 months
800 commits/year, React/TypeScript/Node.js/Docker/AWS, TDD/CI-CD, self-solves unknown problems→promoted in 6 months, 3x performance improvement.
❌Failure: 5 years→quit in 3 months
50 commits/year, Ruby 2.x/Rails 4.x, no tests, no interest in new tech→misled by years of experience, mismatch.
10 Red Flags
- All commits same timestamp
- No README/template unchanged
- No .gitignore
- All files in 1 commit
- Dependencies 3+ years old
- Zero test code
- Commit messages "update" only
- 3+ month gaps
- All projects incomplete
- Copy-paste code everywhere
FAQ
Q1. No GitHub portfolio?
A. Give coding challenge: "Build Todo app in 2 days, publish to GitHub" evaluates all points.
Q2. Evaluation takes too long?
A. Initial review 15-20min sufficient. Checklist mechanical scoring for efficiency.
Q3. Ignoring years dangerous?
A. Use as supplementary info. Focus on "what learned and how grew during those years".
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Summary
"3 years Ruby, 3 years JS" is resume-era relic. GitHub thought-process treasure enables essential ability evaluation. Framework practice yields: ①see through years to true capability②discover high-potential unexperienced③improve interview accuracy reduce mismatch. Hiring determines company future. Escape outdated evaluation, gain power to identify truly excellent engineers.