Know exactly which skills to invest in to become irreplaceable in the age of AI.
The open-source career transformation guide for every knowledge worker.
88 roles. 1,028 skills. Each rated for AI impact. Free forever.
Get My Action Plan · Read the Playbook · Top 15 AI Skills · Skills by Function · Self-Assessment · Give Feedback
| Finding | Details |
|---|---|
| Skilled Trades are the most AI-resilient function | Trades average just 21% automation risk -- the lowest of all 17 functions. You can't automate pulling wire through walls or soldering pipes. |
| 8 roles have "low" AI impact | 4 of them are skilled trades (electrician, plumber, HVAC, automotive). Physical dexterity and on-site judgment can't be automated. |
| Marketing is the most exposed function | 54% average automation risk across all marketing skills. Content generation, ad optimization, and analytics are rapidly AI-driven. |
| 7 roles are rated "very-high" AI impact | Including Content Writer, Paralegal, Medical Coder, Technical Writer, and SDR. These roles are transforming fastest. |
| The most resilient skills? | Electrical Installation, Live Performance, Apprentice Mentoring, and Conflict Resolution -- all at 5%. Hands-on craft and human connection can't be delegated to a model. |
No matter your role, these are the skills that matter most in the agentic age:
| Tier | Skills | Why |
|---|---|---|
| AI Fluency | Prompt Design, AI Output Evaluation, Model Behavior Understanding | Direct AI effectively and spot when it's wrong |
| Human Anchors | Cross-Functional Collaboration, Stakeholder Management, Mentoring, Ethical Judgment, Conflict Resolution | What AI can't do -- your career insurance |
| AI-Optimised Skills | Data-Driven Decisions, Strategic Communication, Process Improvement, Statistical Analysis, Change Management | Where AI amplifies you 10x |
| Domain Depth | Your core expertise, Adaptability | What makes AI work for you specifically |
Read the full guide → | Skills by function →
- Type your job title (accountant, PM, backend engineer, electrician -- we cover 88 roles)
- Select your current level
- Get a personalized plan: green skills to invest in, yellow skills to partner with AI on, red skills to let AI handle
60 seconds. No signup. No cost.
For every role across 17 functions -- engineering, product, design, data, marketing, operations, leadership, finance, legal, sales, support, HR, healthcare, AI & agents, creative, research, and skilled trades:
- What AI is automating -- stop doing these manually
- What AI is augmenting -- learn to use AI as your 10x multiplier here
- What remains human -- pour your career investment here
- Proficiency levels -- what "good" looks like from junior through principal
- AI impact scores -- every skill rated 0.0 (fully human) to 1.0 (fully automated)
- Career transitions -- which roles you can move to based on skill overlap
- Self-assessment -- score yourself across 15 AI-era skills and get personalised gap analysis
- Learning resources -- curated courses, books, and free guides for every skill area
Wondering how AI changes your job? Get your action plan. 60 seconds.
Building a team development plan? skillich export --function engineering --format csv gives you a spreadsheet with every skill, rating, and proficiency level.
Designing career frameworks? The taxonomy has 5 proficiency levels per skill with observable behaviors. Use it as your leveling foundation.
Building AI-powered career tools? Machine-readable YAML with Python SDK, MCP server, and OpenAI/Anthropic tool export.
skillich was built from research and industry frameworks. The ratings become trustworthy when real practitioners validate them.
If you're an accountant, recruiter, PM, engineer, or anything in between -- your experience is the most valuable thing missing:
Submit feedback -- 2 minutes, no coding. Tell us what matches your experience and what doesn't.
Propose a rating change -- share evidence from your work:
"I've been a Controller for 8 years. The 'Month-End Close' rating of 0.4 is too high -- AI generates journal entries but someone still investigates every variance. I'd say 0.25."
Share your playbook story -- tried the 6-step playbook? Tell us what happened after 90 days.
Star this repo to get notified when ratings are updated for your function.
| Function | Roles | Avg AI Impact | Most Resilient Skill |
|---|---|---|---|
| AI & Agents | 5 | 31% | AI Ethics & Responsible Deployment |
| Creative & Media | 5 | 32% | Live Performance |
| Research & Academia | 5 | 29% | Mentoring & Supervision |
| Skilled Trades | 5 | 21% | Electrical Installation |
| Engineering | 10 | 46% | Product & Design Collaboration |
| Product | 4 | 42% | Stakeholder Management |
| Design | 4 | 41% | Cross-Functional Collaboration |
| Data & Analytics | 4 | 49% | Stakeholder Communication |
| Marketing & Growth | 5 | 54% | Brand Strategy |
| Operations | 5 | 41% | Servant Leadership |
| Leadership | 6 | 33% | Engineering Culture |
| Finance | 5 | 46% | Team Management |
| Legal | 5 | 47% | Cross-Functional Collaboration |
| Sales | 5 | 52% | Relationship Building |
| Customer Support | 5 | 46% | Empathy & Emotional Intelligence |
| HR & People Ops | 5 | 46% | Conflict Resolution |
| Healthcare | 5 | 42% | Cross-Functional Collaboration |
For Developers (click to expand)
pip install skillich[cli]
skillich explore # Browse all functions
skillich explore --function engineering --role backend # Full role detail
skillich impact --resilient --limit 10 # Most AI-resilient skills
skillich impact --function engineering --compare # Compare AI impact across roles
skillich learn --function engineering --role backend --level senior # Learning path
skillich transitions --function engineering --role backend # Career transitions
skillich export --function engineering --format csv # Export for spreadsheetspip install skillich[mcp]Add to Claude Desktop config:
{
"mcpServers": {
"skillich": {
"command": "skillich-mcp"
}
}
}Then ask Claude: "What skills should a mid-level PM invest in given AI?"
from core.taxonomy import TaxonomyLoader
loader = TaxonomyLoader("taxonomy")
role = loader.get_role("engineering", "backend")
print(role.ai_impact.summary)
# Most AI-resilient skills
resilient = loader.get_skills_by_ai_impact(max_rating=0.3)from core.registry import SkillRegistry
registry = SkillRegistry()
registry.auto_discover("skills")
openai_tools = registry.to_openai_tools() # OpenAI function calling
anthropic_tools = registry.to_anthropic_tools() # Anthropic tool_use
mcp_tools = registry.to_mcp_tools() # Model Context Protocol| Skill | What It Does |
|---|---|
role_explorer |
Browse functions, roles, skills, and proficiency levels |
ai_impact_analyzer |
Compare AI impact across roles, find most/least automatable skills |
skill_assessor |
Assess your skills against a target role, get gap analysis |
learning_path |
Generate a prioritized development plan weighted by AI resilience |
career_advisor |
Cross-role skill transfer analysis, career transition recommendations |
AI impact ratings (0.0-1.0) are expert estimates informed by the Anthropic Economic Index, GitHub Copilot research, ILO automation studies, and industry career frameworks. These ratings have not yet been validated by practitioners -- that's why your feedback matters.
Every role has a confidence level (low/medium/high) and a last_reviewed date. Most are currently medium. The path to high is practitioner validation.
Known limitations: Ratings are ranges, not precise numbers. Context matters (a 0.5 at a legacy enterprise may be 0.7 at an AI-native startup). Ratings decay as AI capabilities improve — which is why we follow a quarterly review cadence. See the full methodology docs.
The most impactful contributions don't require code:
- Validate your role -- do the ratings match your experience?
- Share your story -- followed the playbook? Tell us what happened
- Propose changes -- with evidence from your work
- Add new roles -- see CONTRIBUTING.md
MIT