"AI will take your job." But These opportunities will rise: - Inference Engineering for LLMs/VLMs - Demand Forecasting with RL Agents - Data Engineering at scale (evergreen) - GTM Engineering & Strategist - AI Product Managers - DevRel for B2B AI - Mathematician for AI Research - Federated/Distributed Engineering - Networking and Security for AI - AGI R&D Engineering - CUDA GPU kernels - Technical Content Creation with human taste - Sales & Marketing (evergreen) - Teaching AI by Humans - Observability in AI - Solo founder with AI team - Quant Finance with ML - Multi-agent system engineering - Cloud Deployment for AI services - LLMs/SLMs in IoT All technical skills require architecture design, business alignment, and distribution. Coding will never be that tough, but understanding the basics is important. Why? So things won’t be a black box for you. Basics mean concepts, not syntax. Learning these is mandatory to stay relevant: 1. Neural Networks 2. Transformers & LLMs 3. RL 4. Inference for LLMs 5. Linear Algebra 6. Distributed Systems 7. Ops 8. Content Creation (text or video) 9. Marketing and Sales 10. Public Speaking Keep basics clean to stay relevant in next tech wave.

@kmeanskaran the list is real but the framing is off. AI doesn't take jobs, it takes tasks. the people who lose are the ones whose whole job was a single task. the ones who survive own a problem, not a task.

@TFisPython ok