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