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Embodied Intelligence (Moravec's Paradox) This peak represents the challenge of AI operating effectively

AI is reshaping how we work, think, and create — but exceptional results don’t come from guesswork. They come from  how you ask . In a recent live demonstration during one of my AI Whisperer for Business Workshops, I used AI to help a company uncover new opportunities to strengthen its competitive positioning and innovate more effectively. Together, we explored multiple strategic frameworks — from Wiki creation to SWOT analysis, Porter’s Five Forces, and Blue Ocean Strategy. The result? A fully-formed strategic management report and PowerPoint presentation, suitable for a board-level audience. The kind of deliverable you’d expect from a top-tier consultancy produced not over six months, but in just 30 minutes, from ideation to polished printout. But I wanted to go deeper. After generating those outputs, I turned the lens inward. I invited AI to review the prompting journey itself, to suggest refinements — to help me become not just a user, but a better  co-creator . Think of it as AI becoming your own personal prompt tutor. Then I added another layer: using Google Gemini’s Deep Research 2.5 tools, I explored the latest peer-reviewed research on what makes a prompt not just good — but great. The findings were surprising, structured, and powerful. This article was originally published on LinkedIn by Severin Sorensen and has been approved for placement on Arete Coach. Scroll to continue reading or click here  to read the original article. What the research says about prompting well Recent studies analyzing how to extract clear, useful, and factual outputs from LLMs have outlined 10 top prompting strategies — not necessarily in the order of use, but in terms of their potential to elevate outcomes. Chain-of-Thought Prompting Break complex tasks into steps:  “Let’s think through this step by step.”  This improves transparency and logical reasoning — particularly for multi-step challenges. Instruction Clarity & Specificity Define the task, audience, format, and scope. I’ve taught this for years as:  “Stack the intent + output format.” Retrieval-Augmented Generation (RAG) Connect answers to real sources — documents, websites, knowledge bases. This reduces hallucinations and grounds results in verifiable truth. Contextual Anchoring Reference prior analysis or session context. Great prompting is rarely standalone — it’s scaffolded like a consulting engagement. Structured Output Specification Shape the response explicitly:  “Provide a table and a one-line summary.”  This boosts clarity, usability, and speed of application. Self-Refinement & Meta-Prompting Ask AI to critique and improve its own work. But remember: refinement only amplifies what’s already strong — it doesn’t rescue a vague prompt. Self-Consistency Sampling Generate multiple reasoning paths and compare them. Especially helpful in strategic ambiguity or when identifying trade-offs. ReAct Framework (Reason + Action) Use real-time tools (e.g., search, calculator) in tandem with AI logic. Essential for dynamic or data-driven tasks. Few-Shot Prompting with Reasoning Teach by example, then have the AI model the same logic in a new case. Role Prompting (with Caution) Assign a persona —  “You are a 90th percentile, high-performing, top management consultant…”  Powerful for tone and perspective, but don’t expect it to enforce factual precision. Scoring my own prompting journey With these 10 strategies in hand, I asked AI to re-evaluate my full strategy thread through the lens of evidence-based prompt craft. The result? I received clear, actionable insights on how to further sharpen my prompt effectiveness — not just in theory, but in daily use. Areas for growth included: Crafting prompts with greater clarity and specificity Ensuring logical coherence and step-by-step reasoning Using real-time facts via online search (RAG) Providing concrete examples for better generalization Grounding responses in evidence-based structure Increasing comprehensiveness and interpretability of complex outputs These enhancements are now part of my everyday prompting toolkit — expanding both the  precision  and the  creative latitude  of what AI can deliver. But that wasn’t the end of the story. Exploring the frontier: beyond the research While academia is catching up to practice, new prompting styles are emerging at the edge of creative interaction—and I’ve been exploring there. One of my most exciting discoveries emerged from a simple question: If AI performs worse under simulated stress… could it perform better when relaxed? In my workshops and client strategy sessions, I began using what I now call Vibe Prompting—intentionally shaping the emotional tone of the prompt to invite playfulness, boldness, or curiosity. I would guide the AI with phrases like: “Let’s do this with curiosity and wonderment…” “Explore this with creativity and boldness…” “Imagine you’re pitching this to the world’s best thinkers…” The result? When the task required creative synthesis — branding, product naming, story design, or innovation — the outputs were not just better, they were inspired. They felt co-created. But when the task was regulatory, factual, or precision-bound, this approach could reduce reliability. In those cases, I returned to evidence-based prompt craft to ensure accuracy and structure. The insight? Prompting is situational. Different modes for different tasks. Reducing errors with collaborative AI roles Even the best prompts can lead to hallucinations. That’s why I now teach this core principle:   Never let the AI that wrote the content be the only one to check it. Instead, I use a Collaborative Roles Framework that mirrors the structure of editorial, legal, or consulting teams: Researcher – Finds data or sources. Analyst – Interprets what it means. Writer – Drafts the content. Editor – Refines clarity, structure, tone. Evaluator – Scores quality and flags risks. You — the human — become the orchestrator of these roles. This division of labor, especially when combined with RAG and structured outputs, drastically reduces errors and builds confidence in generative results. Where prompt craft is going next We’re entering a new era of AI interaction — one that is: Rooted in evidence-based frameworks; Enriched by creative permission, and; Strengthened through collaborative oversight. It’s no longer about  using  AI. It’s about  partnering  with it. And that partnership begins with the quality of your prompts. Final thought Are you prompting with curiosity, clarity, and strategic intent? I encourage you to revisit your prompts and see them as  journeys, like exploring the 5 Whys, laying in frameworks, etc.  Incredible prompt journeys are not just opening questions but invitations to co-create, ideate, discover, and elevate with AI. Let’s continue to build smarter, more human-centered AI futures—one great prompt at a time. Copyright © 2025 by Arete Coach LLC. All rights reserved.

will evolve from decision-maker to decision-architect, designing the environments where humans and intelligent

, how to interrogate AI outputs, and how to distinguish between interesting insights and actionable intelligence

The future of success lies in the orchestration of collective intelligence, synthesizing diverse human adaptive enterprise: a dynamic exchange between people and machines that creates a new kind of collective intelligence A New Kind of Collective Intelligence: How AI Is Transforming the Living, Learning Organization. https ://www.harvardbusiness.org/insight/a-new-kind-of-collective-intelligence-how-ai-is-transforming-the-living-learning-organization

Two forces above all are rewriting the rules of risk and opportunity: the explosive proliferation of Artificial Intelligence and the pervasive, systemic nature of cybersecurity risk. The Intelligence Analyst:  The strategist who researches the organization from the outside, identifies

Palantir is trusted by: National defense agencies Global intelligence communities Fortune 100s with high-risk

As AI becomes woven into the fabric of everyday work, employees are asking: “Where do I fit in now?” Fear of AI rarely comes from the technology itself. It comes from the belief that someone, or something, will take away a person’s agency, relevance, or dignity. If leaders don’t address that psychological gap directly, no amount of training or tools will ease the anxiety. This is why the stories leaders tell right now matter more than the tools they deploy. Stories shape meaning. And meaning shapes behavior. In this moment of technological acceleration, employees need narratives that restore a sense of control and reinforce that AI is here to support, not replace, the human beings who make an organization extraordinary. Below are powerful, executive-ready stories leaders can use to build trust, reduce fear, and position AI as a force multiplier. “AI Is the Autopilot, Not the Pilot.” Modern aircraft are marvels of automation. Autopilot can handle more than 90% of a flight. Yet, no passenger boards a plane thinking, “Good thing we don’t have a pilot.” We trust the system precisely because a trained human is in the cockpit. AI is no different. It handles routine tasks exceptionally well, but humans remain accountable for judgment, nuance, and decisions. For employees, leaders should reiterate: “You’re not being replaced. You’re becoming the pilot.” “Think of AI Like GPS: You’re Still Driving.” A GPS system offers recommended routes based on traffic, weather, and real-time data. But the human driver stays in full control. You ignore the directions when you know better, and you choose the destination. AI in the workplace mirrors this dynamic. It suggests, accelerates, and guides, all while the employee remains the driver. For employees, leaders should reiterate:   “You stay in control of decisions and direction.” “Doctors Using AI Aren’t Less Valuable, They’re More Capable.” Medical imaging AI can identify anomalies in scans with incredible accuracy. Yet no hospital is replacing radiologists; they’re equipping them.  AI adds a level of precision humans can’t achieve alone. But only humans can interpret results, make diagnoses, and comfort patients. For employees, leaders should reiterate:   “Your expertise becomes more  valuable when paired with AI.” “Power Tools Didn’t Replace Builders. They Empowered Them.” A carpenter with a power drill isn’t less of a carpenter, they’re a more efficient one. Power tools transform what’s possible. AI is the modern equivalent. If a task can be automated, it frees a person to operate at a higher level of skill and creativity. For employees, leaders should reiterate: “You’re not losing tasks. You’re gaining impact.” “Spell-Check Didn’t Replace Editors, It Made Better Writers.” When spell-check first appeared, professional editors were among the most vocal skeptics. Many worried that if software could catch errors automatically, their value would be reduced. Spell-check did not eliminate editing jobs. Instead, it eliminated the mechanical parts of editing—freeing editors to apply deeper value. For employees, leaders should reiterate: “Technology takes away the trivial so humans can focus on the meaningful.” “AI As Anti-Lock Brakes.” Automatic brake systems (ABS) don’t take over your car, they keep you from losing control. AI often works the same way: it catches errors, prevents mistakes, and safeguards decision-making. AI is a safety feature. It prevents more problems than it creates. For employees, leaders should reiterate: “AI helps you avoid errors—it doesn’t override your judgment.” “In an ER, Machines Monitor and Humans Respond.” Hospitals rely on monitors to track patient vitals. But nurses and physicians interpret the signals, decide the interventions, and act with empathy. AI does the monitoring; humans do the meaning-making. For employees, leaders should reiterate: “You remain essential to context and care.” Why These Stories Matter To lead people through technological transformation, leaders must address five core fears AI often triggers: Fear of Loss of Control: Stories like autopilot and GPS restore agency. Fear of Being Replaced: Power tools show human value increases. Fear of Not Being Capable: Medical imaging emphasizes partnership, not competition. Fear of Surveillance: ABS reinforces that AI protects, not polices. Fear of Rapid Change: Spell-check shows that we’ve adapted before, and thrived. If there’s one message employees need from leadership right now, it’s this: “AI will not replace you. A person using AI might. And we’re committed to making that person you .” Leaders who use the right metaphors, the right stories, and the right commitments will transform anxiety into agency, and agency into acceleration. Copyright © 2025 by Arete Coach™ LLC. All rights reserved.

What happens when a prompt isn’t just a request—but a map, a compass, and a vision? Our ability to express intent—clearly, creatively, and semantically—has become the new high-performance language of leadership in AI prompt craft. Recently, I went on what I call a Prompt Safari: a multi-step, iterative journey through high-stakes prompting powered by curiosity, strategy, and the poetic precision of words. The journey and discovery patterns I share here are real. However, in respect of client confidentiality, the use case has been veiled. While the methods, prompts, and models are authentic, the audience and application have been adapted. This article is written not to reveal the work—but to share the structure, mindset, and lessons learned so that others may benefit. Let me tell you the story—and show you how you can do the same. This article was originally published on LinkedIn by Severin Sorensen and has been approved for placement on Arete Coach. Scroll to continue reading or click here to read the original article. What Gets Measured Improves: A Prompt Review Framework Prompting isn’t magic. It’s a skill. And like any craft, the more we assess and refine, the sharper it becomes. At the end of each day, I ask AI for a rating of how I did with my prompts, requesting feedback on what I did well, what could be better, and how I can improve to reach excellence every time. This self-review loop reinforces clarity, deepens my awareness, and sharpens my craft one interaction at a time. To help myself and others grow, working with AI, I developed a simple scoring framework that anyone can apply: Prompt Review Criteria (5.0 Scale) Rate each prompt across the following five dimensions using a 5.0 scale. Use this guide to evaluate and improve your prompt craft—or to teach others how to elevate theirs. Five core dimensions to evaluate and improve your prompt craft. Use this guide as a self-assessment tool—or to coach others toward precision, clarity, and strategic AI interaction. Setting Out on the Journey: From Intent to Precision My original goal was to build a dynamic contact-sourcing system—for elite construction and project managers who oversee complex residential and commercial builds. These were high-value candidates who might be a fit for leadership roles or strategic introductions across multiple markets. But in the world of AI, what starts as a search becomes a symphony. I began by defining the parameters—project scope, location, sector (residential/commercial), experience level, certifications, and even management style. But then came the prompts that refined the strategy: "Can your identify distinquishable markers of excellence in candidate backgrounds?" "Can you rank candidate readiness to be contacted or recruited?" "Are there semantic tells—like 'generational project experience' or 'boutique builder'—that show future potential?" "How can we score readiness to leave or openness to collaboration based on firm language, size, or affiliations?" From this, we built a new score: the Green Shoot Readiness Score (GSR) — a signal model for candidate prospecting readiness. Teaching the Machine, Training the Mind We didn't stop at finding names. We designed a custom GPT template that accepts a location (e.g., city or zip code) and returns 50 curated candidate profiles with signals like: Construction specialization Career journey progression Management history and longevity Collaboration openness Presence in industry groups or elite firms Then it asked: Are we on the right track? — and adjusted based on user feedback before scaling up to complete our candidate pipeline. Prompting became architecture. Each instruction became part of a larger system. The results were magical—worksheets of high-potential candidates from any geography were generated within moments. The paradigm of traditional sourcing was broken. Candidate access was now available at the asking. The task was done, but I was not done. I paused and flipped the mirror: I asked the AI to score my own prompts using the review framework above. What emerged was a feedback loop of excellence—and that loop is available to anyone willing to engage with intent. Examples to Learn From: Prompts Reviewed & Improved Let’s apply the framework. Below are actual prompt styles from this safari, generalized for learning and adapted to the talent-sourcing use case. Use these 5 dimensions to review your prompts or teach others to improve theirs. There were many more prompts in this journey, each one offering new insights, iterations, and learning moments. But you get the picture: Prompt. Iterate. Refine. Reflect. Improve. Use these examples not as a script, but as inspiration—models to shape and sharpen your own prompting journey. Why I Say “Explore With Wonderment” People sometimes ask why I use phrases like: Explore with wonderment — Opens creativity in AI collaboration With deep curiosity — Invites thoughtful, layered exploration Enter with a beginner’s mind — Invites a layered stepwise learning journey approach Framework + Format + Function — Core structure in high-value prompts Here's the answer: These words frame the conversation. They invite AI to operate in a more creative, collaborative space. They set the stage for curiosity—and in turn, better results. Prompting isn’t about commanding a machine. It’s about designing the conditions for insight to emerge. From My Journey to Yours The truth is, this wasn’t a story about me being a great prompter. It’s a story about how you can become one. Use these frameworks. Refine your intent. Let curiosity lead the way. Start with: What am I trying to learn, uncover, or build? How can I express that clearly, with a structured format? What would a strategist—not a technician—ask? What would excellence look like in this profession? What have I not asked, that a subject matter expert might ask? How could AI take this prompt directive and improve it? Because the best prompt engineers are not code experts. They’re semantic architects of thought. Closing Thought If you’re using AI in your business, don’t just give it a task—give it a journey. Craft prompts with purpose. Layer your intent. Ask better questions. Build feedback loops. Reflect. Iterate. Refine. You’re not just automating. You’re designing insight. You’re architecting understanding. And the real magic? It’s not in the model. It’s in the moment when you bring structure, strategy, and language together with clarity. Explore with wonderment. Discover with intent. Words shape thought. Structure shapes behavior. Wonderment unlocks wisdom. And why does this work? Because you're not just whispering to AI — you're orchestrating its impact. Copyright © 2025 by Arete Coach LLC. All rights reserved.

Artificial Intelligence is the culmination of that promise, an efficiency engine capable of summarizing

Manus AI is a recently launched artificial intelligence system developed by a Chinese startup called Claude 3.5 Sonnet acts as the "brain," providing intelligence and decision-making, while the multi-agent potential overhype, early performance issues, and concerns about data privacy given China’s National Intelligence Focus on Human Skills: As AI automates more tasks, the demand for uniquely human skills like emotional intelligence

School of Management on the future of work , is that an executive's value is shifting from computational intelligence