If I had to bet my career on 5 skills for the next decade of AI, here's where I'd put my chips.

1. System Design for AI — Not just ML. The entire system. Data pipelines, model serving, monitoring, human-in-the-loop workflows, cost optimization. This skill transcends any specific model or framework.

2. Evaluation & Testing — As AI gets more powerful, knowing whether it's working correctly becomes more valuable, not less. Evaluation engineering is the quality assurance of the AI era.

3. Multi-Agent Orchestration — The shift from single models to agent systems is the biggest architectural change since mobile. Understanding how to design, coordinate, and monitor autonomous AI workflows is a decade-long career.

4. Human-AI Interaction Design — Making AI systems that people trust, understand, and use effectively. This combines UX, psychology, and engineering in a way that's uniquely hard to automate.

5. Domain Expertise + ML — The generalist AI engineer era is ending. The future belongs to engineers who deeply understand a specific industry AND have strong ML skills. Healthcare + AI. Finance + AI. Manufacturing + AI.

What's NOT on this list: specific frameworks (they change). Specific model architectures (they change). Specific programming languages (Python is probably safe, but even that isn't guaranteed).

Invest in skills that survive paradigm shifts. The tools are the details. The thinking is the career.

These five skills will be valuable whether the next big thing is transformers, world models, neuromorphic computing, or something we haven't imagined yet.

That's the whole point. Build a career that doesn't depend on any single wave lasting forever.