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In this episode, I talked with Keith Jacobs, CEO of geniant, and Grant Baldwin, Partner at geniant, about why most AI investments never show up on the P&L, and what the small group of companies making real money on AI actually does differently. Grant walks through a McKinsey study of 1,700 companies where only 6% are making real money on AI, and Keith and Grant make the case that what sets that 6% apart is redesigning how the work gets done instead of automating a broken process, what Keith calls paving the cow path. We get into why geniant puts anthropologists and psychologists to work before its designers start building with AI, the Olympic level of performance employees will need once the busy work disappears, and why leadership has to clear the path from the top or AI initiatives slow down considerably. We also run a thought experiment on the future of software, closing the context gap until every piece of software is custom to the person using it, and talk about who should own your data and why an opt-in model matters. Chapters: 00:00 The Olympian Worker 02:35 Performing at a Higher Level 06:46 Building the Right Thing 09:51 The 6% Making Real Money 11:53 Paving the Cow Path 15:52 Scared to Admit Using AI 17:54 Air Cover From the Top 20:49 A Behavior First Operating Model 22:46 Staying Optimistic About the Risk 24:45 100 Times More Capable 27:23 Closing the Context Gap 30:48 Who Should Own Your Data 33:19 Every Employee Owns Equity 36:38 Thinking Like a CEO Connect with Keith & Grant: geniant geniant on LinkedIn Keith Jacobs on LinkedIn Connect with Raul: Work with Raul Free Growth Resources Connect with Raul on LinkedIn (DMs open)

In this episode, I talked with Garrick Van Buren about pricing as value creation and why every price is really set against the status quo of “doing nothing,” meaning you must outcompete the comfort of not fixing a problem. We break down value as transformation from current to future state and how to quantify it through revenue gains, cost savings, time savings, and especially retention/churn, with examples like a real estate brokerage commission tool where agent retention drove the true value. Garrick shares his “value stack,” customer rediscovery interviews to uncover unpriced value and unmet needs, and a “How’s My Driving” approach to re-segment customers and refine positioning. We also discuss AI, speed-to-value premiums, services vs product tradeoffs, incremental pricing rollouts, and why founders must remove their own money emotions from pricing using metrics like percentage of annual revenue and risk mitigation. 00:00 Pricing Against Status Quo 04:34 Quantifying Value Shifts 06:24 Revenue Retention and Churn 08:35 The Value Stack Framework 09:59 Real Estate CFO Case Study 14:17 Net New Value With AI 17:52 Customer Rediscovery Calls 19:56 Unpriced Value and Missing Offers 21:31 Services Strategy and Time to Value 23:21 AI as New KPI 24:41 Niching and Positioning 25:01 Customer Rediscovery Buckets 27:03 Pricing Power Signals 29:18 Incremental Price Rollouts 33:02 AI Discounts Debate 34:26 Speed to Value Premium 39:23 Jobs to Be Done Lens 42:28 Detach Emotions from Pricing 45:40 Risk Transfer and Credibility Connect with Garrick:  • https://forstarters.substack.com • https://linkedin.com/in/garrickvanburen • https://pricingfromthestart.com Connect with Raul:  • Work with Raul: https://dogoodwork.io/apply  • Free Growth Resources: https://dogoodwork.io/free-growth-resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

In this episode, I sat down with Phil Berry, founder and CEO of Northwind Health, who has bootstrapped the company for nearly 18 years to over 100 people and close to $100M in revenue while taking on massive healthcare incumbents. We compare his early survival-mode years—keeping headcount lean, fearing payroll, and carrying the business himself—with his shift toward intentional growth, leadership hiring, and asking what the business is “called to do” beyond his personal identity. Phil shares how meaning emerged through employee wins and patient outcomes, shaped by his Catholic faith and a focus on human dignity, which he frames as serving “souls,” not “lives” or “belly buttons.” We also unpack why the healthcare system functions as “sick care,” why big players can’t structurally reduce costs, and how Northwind aims to scale high-touch, waste-removing, outcomes-driven care. 01:13 Founder Mindset Shifts 02:18 Early Hiring and Survival 06:24 Finding Meaning in Work 10:25 Planning Beyond Survival 13:10 Belief and Big Bets 14:42 Stewardship and Scaling 20:04 Separating Identity from Business 22:08 Is Growth Always Right 26:46 Leading in the Tension 30:06 Human Flourishing Thesis 34:01 Fixing Sick Care at Scale 39:14 Human Dignity in Healthcare 42:49 Defining a Human Soul Connect with Phillip:  • Northwind https://www.northwindhealth.com Personal website: https://www.phillipberry.com [email protected] Connect with Raul:  • Work with Raul: https://dogoodwork.io  • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

I sat down with Bill Benjamin to break down his research on the “last 8%”—the small but crucial part of a difficult conversation or decision we often hold back because it feels risky. Bill shares how the idea started with two executives, then expanded through studies of 34,000+ people, showing we leave an average of 7.56% unsaid, and why our brains treat conflict like a threat. We talk about recognizing last 8% moments through body cues and behaviors, the two pillars of high-performing teams (connection and courage), and common defaults like avoiding or “making a mess.” We also cover why psychological safety alone isn’t enough, how leaders can model curiosity and set team norms, and why these human skills matter even more as AI adoption struggles due to fear and disengagement. 00:07 Why We Hold Back 01:33 What the Research Shows 02:36 Brain Science of Fear 03:06 Last Eight Percent Moments 03:42 Individual vs Environment 05:03 Body Awareness Framework 07:58 Beyond Psychological Safety 09:53 Avoiders and Make a Mess 11:10 Skillful Hard Conversations 12:32 Founder Modeling and Norms 14:50 AI Makes Humans Matter 18:51 Disengagement and Connection 20:09 Who Does It Best 22:20 Bill Personal Turning Point 24:06 Toughest Partner Moment Connect with Bill:  • www.ihhp.com • https://www.linkedin.com/in/bill-benjamin-12b671/ Connect with Raul:  • Work with Raul: https://dogoodwork.io  • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

AI As Strategy Workshop: Work and Grow at the Speed of Your Thoughts Most conversations about AI begin with the model. This workshop begins with the business. In this episode explores AI as a strategy question across ownership, ethics, operating design, pricing, and net new value. Raul breaks down the AI COO harness he built for Do Good Work, explains the 5 ingredients inside it, and shares practical examples of how agents support his work without taking control of the relationships or decisions that matter. Use the episode as a workshop with your team. By the end, you will have 2 questions to work through: what you wish your business could do today, and where your business model will need to evolve next. What You'll Learn Why a good model is just a brilliant stranger, and what makes AI useful inside a real businessThe 3 parts of AI sovereignty: your data, the model, and the harness around bothHow the restaurant analogy explains orchestrators, agents, skills, hooks, memory, and rulesThe 5 ingredients every owned AI system needsWhy every product carries a belief about people, and how Raul's 9 operating values protect human flourishingWhy memory, security, compliance, and human approval have to be designed togetherThe difference between automation, augmentation, and net new value5 examples from Raul's AI COO, including daily briefings, content production, searchable business memory, relationship research, and quality controlHow AI moves value up the Service Stack toward judgment, transformation, accountability, and beliefThe 4 pricing choices in the New Value QuadrantWhy speed to value is becoming a critical measure for product and fulfillment teams2 reflection questions to help you decide where AI belongs in your businessChapters [00:00] Why I'm sharing this workshop [01:14] Work and grow at the speed of your thoughts [01:24] The goal: own your AI instead of only renting access [01:45] What the workshop will help you decide [02:10] Why I built my own AI COO [03:14] The experience that shaped what I built [03:48] AI sovereignty: data, model, and harness [04:33] Why a good model is just a brilliant stranger [05:17] The restaurant analogy for an AI harness [06:43] The 5 ingredients: agents, skills, hooks, memory, and rules [08:29] Human flourishing and the values inside the system [10:43] Why memory improves the system over time [11:08] Security, compliance, and human approval [12:04] One orchestrator with a team of specialists [14:06] What AI actually makes possible [14:38] Automation, augmentation, and net new value [19:54] Examples from inside my own AI COO [24:28] Quality loops and the chain [26:10] How AI moves value up the Service Stack [28:08] The AI pricing trap [29:40] How service business pricing is already changing [30:21] The 4 choices in the New Value Quadrant [34:46] Speed to value as a new KPI [35:31] Why the advantage window will not stay open forever [36:34] The written workshop and reflection questions [36:49] Question 1: what do you wish you could do but are not doing [38:34] Question 2: where will your business model evolve [39:37] The build manual and additional resources Reflection Questions 1. What do you wish you could do, but are not doing today? Name the bottleneck, opportunity, client outcome, product, or operating improvement you already know deserves attention. Then decide whether it is actually solvable with AI, which data and model it requires, what should live in the harness, and which decisions must stay human. 2. Where will your business model evolve, or be forced to change? Review your value proposition, customer segments, channels, customer relationships, revenue structure, costs, and key partners. Look for where AI compresses an input and where that new capacity can create greater value for the people you serve. Resources Free Build Manual The AI Growth Harness Manual: the open sourced architecture to build an owned AI system with your own agentMore on Strategy How AI Will Evolve the 7 Parts of Your Consulting Business ModelOn Creating Net New ValueThe New Value Quadrant: How to Price in the Agentic EraThe Service Stack: What Remains When AI Eats Client Services

In this episode, I sit down with Taylor Black, who leads AI and venture ecosystem work in Microsoft’s Office of the CTO and brings a deep “better-formed humans” conviction to the AI conversation. We draw a hard line between intelligence (statistical knowing) and insight—where a human knower makes the categorical leap to “this is true,” what Taylor calls grasping the “virtually unconditioned.” We talk about how LLMs can pattern experience to help us reach insight but can’t replace judgment, and why venture building should be anthropology-first: every product ships an implicit view of the human person. We cover the risk of using AI as an oracle that shortcuts productive struggle (especially in education), the importance of humility and sustaining the tension of inquiry for product-market fit, and Taylor’s “cold storage” idea—using AI as a context engine to shelve, monitor, and revive ventures when conditions change. We close on the key builder question: not what can we build, but what ought we build? 02:08 Intelligence vs Insight 02:58 Statistical Knowing 05:02 Virtually Unconditioned 09:02 Using AI Without Outsourcing Judgment 11:39 Formation in Venture Building 14:19 Anthropology First Product Design 17:56 Hard Rules for Human Flourishing 18:53 What Ought We Build 21:20 Humility and Idea Flow Playbooks 24:19 Probabilistic Products and Implicit Anthropology 28:48 AI as Oracle in Education 34:29 Cold Storage for Venture Ideas Connect with Taylor:  • https://substack.com/@pourbrew • https://www.linkedin.com/in/blacktaylor/  • https://leonum.catholic.edu/ • https://innovate.pourbrew.me/ Connect with Raul:  • Work with Raul: https://dogoodwork.io • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

In this episode, I sit down with Michael Lopez, a Fortune 500 transformation consultant and author of “Change,” to break down why stress and resistance can be biological signs that change is working and why leaders often abandon transformation too early. We unpack Michael’s national workforce study, Rethinking Change Management, which surveyed 1,000 U.S. employees and found “zero overlap” between the top five change supports companies provide (like emails, newsletters, and training) and the top five things employees say they actually need (time and space to experiment, coaching, permission to fail, and leaders modeling change). We also discuss the AI readiness gap—65% of executives feeling ready versus about 29% of employees—and how “licenses without direction” leads to passive resistance and stalled pilots. Michael shares what real change requires: honest expectations, redesigned incentives, and an 18–24 month adaptation journey. 01:12 Stress Means Progress 03:29 Diagnosing Change Problems 05:22 Nuclear Plant Case Study 07:32 Why Playbooks Fail 09:58 The Easy Button Trap 12:23 Pricing Change Work 16:42 Zero Overlap Finding 19:37 AI Readiness Gap 22:40 Redesigning Change Strategy Connect with Michael:  • www.michaeljlopez.coach, IG - @michaeljlopez9, LinkedIn - https://www.linkedin.com/in/michael-j-lopez9/ , X - @MichaelJLopez9 Connect with Raul:  • Work with Raul: https://dogoodwork.io/apply  • Free Growth Resources: https://dogoodwork.io/free-growth-resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

In this episode, I’m joined by Jim Schleckser, founder and CEO of The CEO Project, to break down how CEOs identify and fix the real constraint in their business. We cover practical signals for finding the “kink in the hose,” including where inventory accumulates, cycle time slows, congestion builds, or customer complaints spike—and why top-performing CEOs consistently spend meaningful time at the constraint. Jim explains when the CEO becomes the bottleneck (as the constant decider or by staying stuck in a functional role) and shares his Five Hats framework: learner/analyst and player to find constraints, and architect, coach, and engineer to solve them through business design, talent, and systems. We also dig into why values and mission are part of the operating system, Jim’s grounded view of AI as mostly augmentation amid hype, and what business types may be more resilient long term. 01:25 Why Constraints Matter 03:27 Finding the Business Kink 04:51 When the CEO Is Bottleneck 07:27 Five Hats Framework 09:14 Design Talent Systems Fixes 12:27 Big Model Shifts and Pivots 13:24 Balancing CEO Hats Over Time 13:59 Client Story Clairvoyant Service 14:38 Firing Unprofitable Clients 15:39 Small Shifts That Matter 16:13 AI as Human Amplifier 17:06 Hype Cycles and ROI 18:39 Is AI Creating New Value 21:18 Professional Services Pricing Shock 22:29 Best Businesses in an AI Future 24:46 Constraints Versus Opportunities 25:19 CEO Surprises and AI Doomsday Connect with Jim:  • IG: @the_ceoproject • Twitter: @the_CEO_Project  • YouTube: https://www.youtube.com/@CEOProject  • LinkedIn: https://www.linkedin.com/in/jimschleckser/  • Links: Podcast: https://theceoproject.com/the-podcast/  • Website: https://theceoproject.com/ and https://jimschleckser.com/great-ceos-are-lazy/ Connect with Raul:  • Work with Raul: https://dogoodwork.io • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

I sat down with John Johnson, founding CEO of Patmos Hosting, to unpack how he bootstrapped a data center company with no outside capital after a big tech host threatened to cancel a client, leading him to pursue independence by “controlling the dirt.” We talk about his rule “he who pays, rules,” why he believes VC money erodes a founder’s mission, and how owning infrastructure and going upstream helps you control your destiny and protect your data. John also explores AI’s risks—counterfeit human personhood and reducing humans to artifacts—while arguing for a renaissance where authentic humanity becomes a premium. He shares how Patmos is redeveloping the old Kansas City Star printing press into a C-PACE financed, assessed clean-energy data center plus a downtown tech hub to create jobs and urban renewal. We also discuss his Albertus Magnus Institute and his North Star: human freedom. 03:25 Counterfeit Humanity & the Organic Human Market 08:07 AI and the Technocratic Paradigm 11:21 The Human Renaissance: Practical Counter-Revolution 14:08 Owning the Dirt: Freedom Through Education & Independence 14:20 John's Journey: From Ministry to Data Centers 22:55 Patmos: Free Speech Hosting & AI Infrastructure 27:23 Data Centers, Sustainability & The Kansas City Story 32:20 Owning Your Own Data & Patmos Phase Two Connect with John:  • https://patmos.tech/ • https://magnusinstitute.org/ Connect with Raul:  • Work with Raul: https://dogoodwork.io • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

In this podcast, I sat down with Ronan Leonard, founder of Intelligent Resourcing, to break down how he helps sales teams eliminate the 40% of their day spent manually researching companies and instead deliver real buying signals directly into the CRM so reps can take action. We talked about how fast AI is reshaping business models—Ronan compared it to waking up and finding the snow gone overnight—and why he refuses to build SaaS right now. He explained “dark data” hidden in sales call transcripts, how he enriches CRMs into “evergreen” systems, and how those insights feed content and GEO/answer optimization. We also covered tool-stack volatility, internal tooling vs productizing, structuring teams around learning speed, value-based pricing and price elasticity, and we had an honest disagreement on co-risking and revenue-share deals. 01:36 AI Overwhelm and Pace 03:19 Snowstorm Business Models 04:13 No SaaS Moat Strategy 05:09 Signals Into the CRM 06:45 Dark Data and Transcripts 08:55 Scaling Clients and LTV 15:49 Team Structure and Learning 19:41 Agents vs SOP Iteration 24:39 Standardize Custom Work 24:59 Value Based Pricing Framework 27:48 Cost Savings Case Study 30:16 Pricing as Perception 31:49 Why Upside Deals Fail 35:36 Confidence and Client Execution 36:34 Staying Ahead of AI Curve 39:37 Creativity and Feedback Loops Connect with Ronan:  • https://www.linkedin.com/in/ronan-leonard/ https://intelligentresourcing.co/ Connect with Raul:  • Work with Raul: https://dogoodwork.io • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/

How AI Will Evolve the 7 Parts of Your Business Model: Leverage AI to enable you to solely focus on client relationships, belief and the nuances of your work 00:00 The Bold Pricing Vow01:42 AI Labs Enter Services03:29 Your Offer Is Not The Moat05:00 Seven Model Ingredients06:47 How AI Changes Each Part15:25 The Evolved Model Blueprint25:26 Three Breakthrough Signals29:49 Four Steps To Redesign36:53 Closing Call To Evolve Substack Version of this podcast: https://dogoodwork.substack.com/p/how-ai-will-evolve-the-7-parts-of

In this episode, I talk with Jeffrey Meade, founding director of entrepreneurship at Paul Quinn College, about the school’s “Every Quinnite is an Entrepreneur” program, where by 2028 every student must launch a real business that generates revenue before graduating. Jeff explains why traditional schools optimize for employment but the job market is changing, making entrepreneurial thinking—creativity, adaptability, and problem-solving—more essential. We dig into what qualifies as a “real business” (no fixed revenue threshold, but real customers, pivots, and an MVP mindset), why they focus on solving a core problem before layering in AI, and the mindset shift first-generation and Pell Grant students must make from “don’t fail” to “fail fast” in a safe learning environment. Jeff also shares how he’s open sourcing the model through case studies and a podcast, plus where to learn more. 00:45 Why Entrepreneurship Now 03:38 Mandatory Student Ventures 04:35 MVPs And First Sales 06:52 AI Tools Problem First 10:31 From Scarcity To Confidence 13:06 Safe Space To Fail 15:18 Open Sourcing The Model 17:29 Where To Learn More Connect with Jeffrey:  https://paulquinn.edu/[email protected]://www.linkedin.com/in/jeffmeade Connect with Raul:  • Work with Raul: https://dogoodwork.io  • Free Growth Resources: https://dogoodwork.io/resources

In this episode, I interviewed Patrick Rooney, a cognitive science–trained AI practitioner and founder of Leonis Strategy, about how founders mischaracterize AI by collapsing “scripted autonomy” (agents doing tasks while you step away) into personhood autonomy (will, rights, interiority). Patrick argues this isn’t just sloppy language but a leadership issue that shapes how teams relate to technology. They discuss why LLMs are plausibility engines rather than truth-seekers, how humans can pursue truth, beauty, and goodness for their own sake, and why leaders must own inputs, outputs, and responsibility instead of outsourcing judgment. We explored why LLM training is text-bound and disconnected from lived experience, the appearance-versus-reality problem behind Turing-test thinking, practical cautions around anthropomorphizing AI, and why doubling down on in-person human connection is a strategic response to AI at scale. 01:53 LLMs Are Plausibility Engines 05:10 Leadership And Culture Values 07:34 Why LLMs Aren't Intelligent 08:54 Turing Test And Training Limits 12:42 Language Detached From Reality 14:48 Personhood Rights And Ethics 19:01 Anthropomorphism Risks 19:34 Human Ownership Mindset 20:25 Outsourcing Your Thinking 22:24 IP Training Fears 24:34 Responsibility Still Human 28:41 Leading In AGI Hype 29:38 Grounding In Real Life Connect with Patrick:  • https://leonisstrategy.com/ • https://www.linkedin.com/in/prooney1/ Connect with Raul:  • Work with Raul: https://dogoodwork.io/apply  • Free Growth Resources: https://dogoodwork.io/free-growth-resources

In this episode, I’m joined by Jim Ristuccia, a former US Naval officer, founder/CEO, and Vistage Chair in San Diego who leads peer groups for CEOs of $5M+ companies and small business owners in the $1–10M range. We break down what actually happens inside a Vistage meeting—especially the “issue processing” that surfaces blind spots through uncomfortable but growth-producing questions. Jim shares how AI started showing up consistently after a 2024 speaker session, including a case where an IP law firm put its team through AI bootcamps, tripled personal productivity, and grew revenue 50–60% in a year. We discuss the adoption gap (CEOs vs. leadership teams vs. employees), why employees often feel threatened, and how leaders can create psychological safety. We also dig into practical implementation via AI champions, committees, process mapping, low-hanging-fruit use cases, and measuring ROI through time savings, productivity, and revenue. 01:56 What Vistage Really Is 02:45 Issue Processing Secret Sauce 04:46 When AI Hit the Groups 06:43 Why Some CEOs Lag on AI 08:44 Use Cases vs Business Model Shifts 09:45 AI Readiness and Industry Friction 11:20 Leading Change and Finding Use Cases 13:25 Prompts Training and Psychological Safety 15:01 AI Champion and Process Mapping 16:04 Why People Quit 16:32 Build AI Champions 17:58 Pick Use Cases Fast 18:33 Measuring AI Impact 20:00 Beyond Time Savings 21:02 Culture and Safety 23:48 Compliance and Knowledge 24:32 Jobs and Business Models 27:38 Adoption Takes Time Connect with Jim:  • https://jimristuccia.com/ Connect with Raul:  • Work with Raul: https://dogoodwork.io • Free Growth Resources: https://dogoodwork.io/resources

In this episode, I’m joined by Thaddius Ruszkowski, CTO at Fuzati, who’s built software platforms for over a decade, from 25-person internal workflow systems to consumer platforms with millions of users. Thadd isn’t just theorizing about AI agents; he’s running a fleet of them in parallel every day across multiple projects. We dig into what happens to value, intellectual property, and labor as production costs collapse, and why efficiency is only the opening round, not the real competitive advantage of AI. We also talk about managing parallel agents without losing your mind, the comeback of hardware, why on-prem/local will matter more than most people think, and why IP is actually more valuable now in a world flooded with slop. Plus, how he built an early chatbot trained on the writings of St. Thomas Aquinas. 03:12 Working With Agents 04:44 Aquinas Chat Origins 10:28 Beyond Efficiency 20:49 Net New Value 24:28 Create Net New Value 25:02 Decouple Labor From Value 27:58 Outcome Value Shift 30:26 Future Digital Assets 34:35 Three AI Futures 37:58 IP And Distribution 40:56 Local Hardware Shift 42:42 Client AI Disclosure Connect with Thadd: https://www.linkedin.com/in/thad-ruszkowski/ Connect with Raul:  • Work with Raul: https://dogoodwork.io  • Free Growth Resources: https://dogoodwork.io/resources • Connect with Raul on LinkedIn (DMs open): https://www.linkedin.com/in/dogoodwork/