The Counterintuitive Path to AI Efficiency, According to Stephanie Hills, Ph.D.

In a recent LinkedIn post, Stephanie Hills, Ph.D. offers a timely perspective on optimizing Artificial Intelligence (AI) usage, particularly for leaders who find themselves in a hurry. She highlights a common pitfall: the temptation to bypass essential setup steps when needing a quick AI-generated output, which often leads to more frustration and wasted time in the long run.

Stephanie Hills, Ph.D. points out that the desire for immediate results can lead users to skip crucial preparatory actions. She details this common approach:

“You need something from AI quickly. So you skip the setup. No real context. No workflow definition. No skill creation. No MCP. No thinking through what “good” actually looks like. You just start prompting.”

This initial haste, as Stephanie Hills, Ph.D. explains, often results in a cycle of prompting, reviewing, and correcting that negates any time saved. She admits to falling into this pattern herself, especially when feeling pressured by urgency. “Usually when I am in a hurry,” she writes, “I know I should slow down for a few minutes and set the work up properly. But when something feels urgent, the temptation is to jump straight into execution.”

The Hidden Cost of Rushed AI Implementation

Stephanie Hills, Ph.D. argues that this ‘fast’ approach with AI often becomes the slowest. The core issue, according to her, is not AI’s inherent inefficiency, but rather the user’s setup process. When context is lacking, workflows are undefined, and desired outcomes are not clearly articulated, AI is forced to guess, leading to suboptimal results that require extensive revision.

Relearning the Lesson of Upfront Investment

The central lesson Stephanie Hills, Ph.D. emphasizes is a counterintuitive one for those under pressure: the most efficient way to use AI involves investing more time *before* the AI begins its work. She outlines specific steps that constitute this essential preparation:

• Give it the context.
• Define the workflow.
• Create the skill when the task will repeat.
• Connect the right tools through MCP when access matters.
• Be explicit about the output you want.

Stephanie Hills, Ph.D. states, “That upfront work feels slower. But it dramatically reduces the guessing, correcting, and re-prompting later.” By dedicating time to these preparatory steps, users enable AI to perform more effectively from the outset, thereby minimizing the need for iterative corrections.

Rethinking AI Setup for Leadership Effectiveness

According to Stephanie Hills, Ph.D., the responsibility lies with leaders to harness AI correctly. She posits that AI itself is not the bottleneck; rather, it is the initial setup and lack of clear direction that lead to inefficiency. “AI is not inefficient. Our setup often is,” she asserts. The better the context and workflow are defined, the less time individuals will spend correcting the AI’s output. This approach not only improves the quality of AI-generated results but also fosters a more productive and less frustrating user experience.

Stephanie Hills, Ph.D. concludes by encouraging leaders to adopt this more deliberate approach to AI implementation, framing it as essential for true efficiency and effective leadership in the age of artificial intelligence. She also offers resources, including a “Before You Prompt Guide” and an “AI vault,” to assist users in adopting these best practices.