Former Tesla AI Director and OpenAI co-founder Andrej Karpathy released the US Job Market Visualizer on March 16, 2026, a tool that maps AI exposure across 342 occupations covering 143 million jobs. Built in a two-hour Saturday morning coding session, the project visualizes Bureau of Labor Statistics data and estimates which professions face the highest risk from current AI capabilities.
Dataset Covers Full US Labor Market
The visualization displays 342 occupations representing 143 million jobs across the US economy. Each rectangle's area is proportional to total employment in that occupation, with color indicating the selected metric. Users can explore multiple dimensions:
- BLS projected growth outlook
- Median pay levels
- Education requirements
- AI exposure scores (the key innovation)
Karpathy described the project as "a saturday morning 2 hour vibe coded project" that demonstrates rapid prototyping with AI assistance, creating a nationally-discussed economic analysis tool in hours rather than weeks.
AI Exposure Inverts Traditional Automation Concerns
The "Digital AI Exposure" metric estimates how much current AI—which is primarily digital—will reshape each occupation. Karpathy used large language models (Gemini Flash via OpenRouter) to generate rough exposure scores, acknowledging they are "not rigorous predictions."
The analysis reveals 42% of jobs score 7+ on AI exposure, representing 59.9 million workers and $3.7 trillion in wages. Critically, the data shows an inverted relationship compared to traditional automation fears:
- Professions earning more than $100,000/year: worst average score (6.7)
- Jobs earning less than $35,000: lowest exposure (3.4)
This pattern suggests AI primarily threatens white-collar knowledge work rather than blue-collar manufacturing jobs, reversing historical automation trends.
Elon Musk Amplifies Viral Discussion
Elon Musk commented on the project, stating "All jobs will be optional," driving additional viral attention. The Hacker News post gained 400 points and 313 comments, with discussions focusing on the economic implications of high AI exposure in high-wage professions.
The tool remains live at karpathy.ai/jobs, though Karpathy later deleted the GitHub repository. He emphasized important caveats: "This is not a report, a paper, or a serious economic publication — it is a development tool for exploring BLS data visually."
Technical Implementation Demonstrates Vibe Coding
The project's technical approach included:
- Occupational data from BLS Occupational Outlook Handbook
- Large language models (Gemini Flash) for automation risk assessment
- Interactive visualization with multiple metric views
- Open-source release (initially, before repo deletion)
The "vibe coding" approach—rapid prototyping with AI assistance—allowed a former AI leader at Tesla and OpenAI to build and ship a nationally-discussed economic visualization tool in one morning. This demonstrates how AI tools are compressing software development timelines from weeks to hours for experienced developers.
Key Takeaways
- Karpathy's US Job Market Visualizer maps AI exposure across 342 occupations covering 143 million US jobs
- 42% of jobs score 7+ on AI exposure, representing 59.9 million workers and $3.7 trillion in wages
- High-wage professions (over $100K) show the worst average AI exposure score at 6.7, inverting traditional automation concerns
- Built in a two-hour Saturday morning coding session using AI assistance, demonstrating rapid "vibe coding" approach
- Low-wage jobs (under $35K) show lowest AI exposure at 3.4, suggesting current AI primarily threatens knowledge work