1/ There aren't many jobs in this space. There are still far more companies (and roles) that need 'full-stack development' than those focused on 'AI/LLM internals.' With low demand for AI internals and a high supply of talent—many people have earned data science certificates in AI hoping to land lucrative jobs at OpenAI, Anthropic, etc.—the bar for accessing these few roles is very high.
2/ The risk here is AI makes everyone good at full-stack. This means more competition for roles, less demand for roles (now 1 in-experienced engineer with AI, can output 1.5x the code an experience Senior engineer could do in 2020).
In the short/medium term, 2/ has the best risk/reward function. But 1/ is more future proof.
Another important question is where are you in your career? If you're 45 years old, I'd encourage you to switch into leadership roles for 2/. This wont be replaced by AI. If you're early in your career, it could make more sense to switch.
1/ There aren't many jobs in this space. There are still far more companies (and roles) that need 'full-stack development' than those focused on 'AI/LLM internals.' With low demand for AI internals and a high supply of talent—many people have earned data science certificates in AI hoping to land lucrative jobs at OpenAI, Anthropic, etc.—the bar for accessing these few roles is very high.
2/ The risk here is AI makes everyone good at full-stack. This means more competition for roles, less demand for roles (now 1 in-experienced engineer with AI, can output 1.5x the code an experience Senior engineer could do in 2020).
In the short/medium term, 2/ has the best risk/reward function. But 1/ is more future proof.
Another important question is where are you in your career? If you're 45 years old, I'd encourage you to switch into leadership roles for 2/. This wont be replaced by AI. If you're early in your career, it could make more sense to switch.