You can't sue an AI model provider like Anthropic when an agent makes a costly mistake. Enterprises require a human-led organization, like a consulting firm, to take accountability and liability. This fundamental need for a "throat to choke" ensures the relevance of services firms in the AI era.

A crucial function for humans in an AI-driven economy is to serve as a target for lawsuits. Because you can't easily sue a data center, regulated professions will require a 'human in the loop' to take legal responsibility. This creates a valuable economic role for humans: being a legally accountable entity.

Career security in the age of AI isn't about outperforming machines at repetitive tasks. Instead, it requires moving 'up the stack' to focus on human-centric oversight that AI cannot replicate. These indispensable roles include validation, governance, ethics, data integrity, and regulatory AI strategy, which will hold the most influence and longevity.

Worrying about AI replacing jobs is wasted energy. Like past technological shifts (internet, tractors), new roles will emerge. The onus is on the individual to hold themselves accountable and adapt rather than blame the inevitable progress of technology.

The core question isn't whether AI is capable of a task, but whether an AI-only solution meets the market's demand for trust, accountability, and relationship. This reframes the debate from a technical capability issue to a service design problem, highlighting where human involvement remains essential and valuable.

As AI agents take over execution, the primary human role will evolve to setting constraints and shouldering the responsibility for agent decisions. Every employee will effectively become a manager of an AI team, with their main function being risk mitigation and accountability, turning everyone into a leader responsible for agent outcomes.

AGI won't eliminate all jobs because many roles contain a "Human Premium"—value tied to human involvement that AI cannot replicate. This includes inherent demands for relationship, embodied presence, trust, legal accountability, translation of complex needs, and encouragement for behavior change, ensuring durable roles for people.

Slow AI adoption in fields like law isn't about capability, but reliability. O-Ring Theory, where one failure destroys the whole product, applies here. For a lawyer, a 99.9% accurate AI is unacceptable because the 0.1% error could be catastrophic, preventing automation of the full, high-stakes workflow.

Even as AI masters creative and technical skills like design and coding, the essential human role will be to make the final decision and be accountable for the outcome. Someone must ultimately be responsible for what gets built and shipped.