Future of general LLM work (interp/inference/alignment) vs agentic/physical AI (VLA, multimodal) for career

Editorial analysis

The advancement in future of general llm work (interp/inference/alignment) vs agentic/physical ai (vla, multimodal) for career demonstrates the accelerating maturity of agent-tool integration protocols. I'm at a crossroads with two grad school options that would take me in somewhat different research directions, and I wanted some general advice on these fields, their growth, and industry... The Model Context Protocol (MCP) is emerging as the de facto standard for connecting language models to external tools and data sources, analogous to how LSP standardized editor-language server communication. For engineering teams, this means tool integrations can now be written once and reused across multiple agent frameworks and hosts. The security model—capability-based permissions with explicit user approval—addresses the primary enterprise concern around agent autonomy. Teams should evaluate their existing tool surfaces for MCP compatibility and plan migration from framework-specific tool registries. The ecosystem momentum suggests MCP will become a baseline requirement for enterprise AI deployments within the next twelve months.