Effective AI implementation isn't about automating entire human jobs. It's about re-architecting workflows to assign AI the research and analysis tasks it excels at, while preserving relationship-building, empathy, and high-judgment tasks for humans. This division of labor maximizes the strengths of both.

AI can't generate a great strategy in a vacuum. To get a non-obvious result, a human must provide rich constraints beyond market data, including team motivations, regulatory landscape, and brand identity. The process is more like management than simple delegation.

An investment team intentionally prohibits using AI to draft the core thesis of an investment memo. The act of thinking through and articulating the risks, potential pitfalls, and core bets is a crucial part of the human investment process that should not be outsourced to a machine.

The key to creating effective and reliable AI workflows is distinguishing between tasks AI excels at (mechanical, repetitive actions) and those it struggles with (judgment, nuanced decisions). Focus on automating the mechanical parts first to build a valuable and trustworthy product.

The original "Legos" advice involved completely handing off a task and its mental burden. When you give a task to AI, you are merely delegating. You cannot get rid of the oversight, accountability, and the "mental tax" of ensuring the final output is correct.

Even when AI can perform a task better, professionals should consciously reserve activities for themselves. Tasks core to one's professional identity, credibility, and personal fulfillment—like authentic writing for an expert—should remain human-driven. The mantra is "just because it can doesn't mean it should."

AI automates the execution-heavy middle part of tasks. This elevates the human role, allowing professionals to focus their expertise on the critical bookends of a project: the upfront strategy and the final review, where taste and judgment are paramount.

To determine the boundary between human and AI tasks, ask: "Would I feel comfortable telling my CEO or a customer that an AI made this decision?" If the answer is no, the task involves too much context, consequence, or trust to be fully delegated and should remain under human control.

As AI handles more repetitive tasks, skills like critical judgment, communication, and domain expertise become more valuable, not less. The key competitive advantage is knowing how to use AI-generated output while recognizing its limitations and applying human oversight.