Shreyas Doshi Unveils ‘AI-in-the-Loop Coaching’ for Leaders Navigating the AI Era

In a recent LinkedIn post, Shreyas Doshi explores a novel coaching method designed to equip founders and senior leaders with essential skills for the age of artificial intelligence. Doshi introduces his approach, termed ‘AI-in-the-loop coaching,’ which integrates AI tools directly into the problem-solving and decision-making process.

The methodology, as detailed by Doshi, involves a collaborative process where leaders engage with an AI by pasting their discussion points into a chosen Large Language Model (LLM). The AI then generates recommended actions, which are then meticulously reviewed by Doshi and the leader.

“we discuss a problem you’re facing or a decision you want to make – you paste our verbatim discussion into an LLM of your choice (thanks Granola) – ask it for recommended action(s) – we *carefully* review the LLM’s response”

Doshi emphasizes that this careful review is crucial. He highlights his role in dissecting the AI’s output, identifying compelling or useful elements, and explaining why other parts might be less effective. The process also involves refining the AI’s answers through further prompting, with Doshi guiding this refinement, often facilitated by screen-sharing capabilities during virtual sessions.

Cultivating Critical Thinking in the Face of AI Output

A core benefit of Doshi’s ‘AI-in-the-loop coaching,’ as he explains, is its ability to foster critical thinking skills. He observes a trend where individuals are becoming overly impressed by the sophisticated language and format of AI-generated content, potentially overlooking the need for rigorous evaluation.

“Creates the habit of critical thinking for AI responses – too many people these days are getting impressed by the format and language of AI output and are not evaluating the output critically enough”

According to Shreyas Doshi, this method directly combats that tendency by making critical assessment a built-in part of the workflow. The process encourages leaders not just to accept AI suggestions but to actively question, analyze, and validate them, thereby building a crucial defense against uncritical reliance on AI.

Leveraging AI for Novel Insights and Optimal Solutions

Beyond critical evaluation, Doshi points out that AI can serve as a catalyst for generating novel ideas that might not surface through conventional human-to-human discussions. The LLM can offer perspectives or solutions that differ from typical human brainstorming, thereby broadening the scope of possibilities.

Enhancing Question Framing and Prompt Engineering

Furthermore, Doshi highlights how this coaching method illuminates the art of effective AI interaction. By observing and participating in the process of refining prompts and reviewing AI responses, leaders learn how to ask better questions to elicit higher-quality, more relevant answers from AI models.

“Shows how to frame better questions to get higher quality answers from AI – Shows how you can reach more optimal ideas, answers, recommendations by layering strong human judgment on top of an already-great AI response”

As Shreyas Doshi argues, the ultimate goal is not to be replaced by AI, but to augment human capabilities. The ‘AI-in-the-loop’ approach demonstrates how to combine the powerful processing capabilities of AI with the nuanced judgment and contextual understanding of experienced leaders to arrive at superior outcomes.

Building Confidence in Human-AI Collaboration

In his post, Doshi concludes by noting the confidence-building aspect of this methodology. By successfully navigating and refining AI outputs, leaders develop a stronger belief in their own ability to leverage increasingly sophisticated AI tools effectively. This growing confidence is vital as AI models continue to evolve and become more capable.

“Builds confidence in one’s own ability to do this as models continue to get smarter 🙌”

Shreyas Doshi’s ‘AI-in-the-loop coaching’ offers a practical framework for leaders aiming to harness the power of AI responsibly and effectively, ensuring that human intelligence remains at the forefront of decision-making in an AI-driven future.