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 Vow
01:42 AI Labs Enter Services
03:29 Your Offer Is Not The Moat
05:00 Seven Model Ingredients
06:47 How AI Changes Each Part
15:25 The Evolved Model Blueprint
25:26 Three Breakthrough Signals
29:49 Four Steps To Redesign
36:53 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/entrepreneurship
• jeff-meade.com
• jmeade@pqc.edu
• https://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