Working in AI, no theater.
Eight guides on AI work — what the roles are, what they pay, what the interviews look like, what the resume needs to say, what to negotiate. Public data, current pay bands, no influencer hype.
Career pathways
Research engineer · ML engineer · MLOps · AI product · prompt engineer · applied AI · the actual job ladders and how they branch.
Skill tree
The dependency graph of skills. What to learn first, what's optional, what hiring managers actually test for.
Real salary ranges
Frontier labs (Anthropic / OpenAI / DeepMind / Meta / xAI) · public-company AI roles · startup ranges · government roles. Bands by level + total comp breakdown.
AI resume
How to show competence on paper for AI roles in 2026. The specific projects that get interviews. The fluff that gets discarded.
Interview prep
What ML/AI interviews actually test. System design for ML systems. ML-specific behavioral questions. The frontier-lab loop.
Non-technical AI roles
Product management, policy, communications, legal, operations, sales, design — the AI jobs that aren't writing code.
Offer negotiation
What's negotiable in 2026 AI offers. Equity vs cash. The specific data points that move the number.
Independent path
Open-source contributions, paid research, consulting, building a company. The non-W2 routes that actually work in AI.