265 Buying AI vs Building AI - A Leader’s Decision Guide
Release Date: 12/19/2025
EP281 Your Team's Nervous System Is Infrastructure - Sira Laurel on Load-Bearing Trust
AI Literacy for Entrepreneurs
Most of the leaders Sira Laurel works with look like they're winning. Inside, they're exhausted. Sira is an executive coach and facilitator who works on leadership, organizational design, cognitive load, trust and nervous system capacity. She has watched organizations get very good at making work faster while getting worse at deciding what the speed is for. AI raises the stakes on that question. Her starting point is that capacity covers far more than time. It includes attention, decision-making, emotional bandwidth and creative energy. A tool can hand back hours on the calendar while draining...
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EP280 Faster Than a Generation - Ian Alden Russell on Change That Outruns Us
AI Literacy for Entrepreneurs
This episode skips the tools, the prompts, and the latest model release. It goes somewhere more philosophical. started out as an archaeologist and anthropologist. He was the kid who loved museums and Indiana Jones. Since then he has worked across history, contemporary art and culture in Dublin, Istanbul, Beijing, Hong Kong, Pittsburgh and Doha. Now he works as a strategist helping organizations make sense of complexity and line up around change. His starting point is that change itself is old news. Humanity has absorbed huge technological shifts again and again. The new part is the speed....
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EP279 How higher ed moves from AI interest to governed use with James Hutson
AI Literacy for Entrepreneurs
A previous president from Lindenwood University (a former IBM executive) stands up in town halls and tells people he uses Claude - that it helped him organize the financial report. HR follows and says they used Gemini for an employee questionnaire. Then James Hutson PhD. goes and asks employees whether they understood that as permission. The answer? 'No. The policy says I'll get fired if I use it.' That gap is the subject of this episode. James is Senior Professor and Director of AI-Enabled Academic Transformation at Lindenwood University, with two PhDs - the first in art history, the second...
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EP278 AI Governance in Higher Ed with Dr. Eugene Chan
AI Literacy for Entrepreneurs
Most organizations govern AI the same way cities govern speeding. They set a rule, then punish people who break it. Dr. Eugene Chan thinks that's the least interesting tool available. He's a behavioural scientist - founder of the consultancy Behavieural and Professor of Business at Tyndale University - and his argument is that punishment is a lagging response to a problem you could have designed out. His analogy is a speed camera versus a speed bump. Both reduce speeding. The camera does it by fining you after the fact, and it needs maintenance forever. The speed bump does it by making the...
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EP277 Is AI Going to Take the Gift of Failure Away? asks Julie Cole
AI Literacy for Entrepreneurs
Episode description Julie Cole and her co-founders started Mabel's Labels in a Hamilton basement 23 years ago, back when customers were still nervous about typing a credit card number into a computer. They figured out early that they weren't really running a label company - they were running a tech company that happened to make labels. Nothing off the shelf did what they needed, so they built it themselves. Which is why her read on this moment carries some weight. She's watched every technology wave since. She's not a skeptic and she's not a cheerleader. She uses AI, has a clear personal rule...
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EP276 Your AI Strategy Is a Hammer. Where's the Nail? - with David Cohen
AI Literacy for Entrepreneurs
"We need AI" is the most common brief in business right now. David Cohen's read on what it means: usually nothing in particular. David is the founder of Superposition, a consultancy for data and AI consultancies - a meta consultancy, as he calls it. He's spent his career inside both big and boutique consulting shops, which makes him refreshingly blunt about what's actually happening in the services world right now. His diagnosis is that we're still in the solution-in-search-of-a-problem stage. Everybody's curious. Everybody's excited. There's enormous movement, enormous hype, and very few real...
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EP 275 "Do I Trust Myself?" Grace Gravestock on the Real Reason AI Adoption Stalls
AI Literacy for Entrepreneurs
Episode description Everyone's arguing about whether AI can be trusted. Almost nobody's asking the harder question underneath it. Grace Gravestock has spent more than twenty years leading change management on some of the highest-profile technology projects around - including the team that set the stage for the $67B Dell EMC integration. Her verdict on why AI pilots stall is unsentimental: it's the same reason ERP stalled, and CRM before that. People aren't using the technology the way it was intended. You can have the best tools in the world, and if people don't use them, it doesn't matter....
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EP 274 The Human OS - AI Adoption With Curiosity, Safety, and Monday Ease ft. Melissa Penton
AI Literacy for Entrepreneurs
In the final episode of the Podcast-to-Book series, host sits down with change leader and AI education lead (Sun Life) for a human-first conversation about what actually makes AI adoption work. They talk productivity vs room-for-life, why one-prompt culture is snake oil, the shift from prompt engineering to context engineering, and the simplest enterprise question that changes everything: “What would make Monday easier for employees?” Episode summary Susan closes out the Podcast-to-Book sprint with a conversation that feels like the point of the whole series: AI isn’t a tool problem....
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273 - Future-proofing your organization through continuing AI literacy
AI Literacy for Entrepreneurs
Most companies do a few AI trainings, run some pilots, and then stall. In this episode, host argues the only real future-proofing strategy is continuous AI literacy. She breaks down what “continuous literacy” actually includes (skill, judgment, workflow, norms), the predictable failure modes of the AI literacy divide, and a simple flywheel you can run monthly so capability keeps compounding. Episode summary Susan opens with a familiar pattern: a burst of AI excitement, a deck called “AI Strategy 2025” a few clever workflows… and then reality hits. Tools change. Policies shift....
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EP 272 - Mindset, Sales, and AI That Actually Helps with Gazzy Amin
AI Literacy for Entrepreneurs
Host sits down with sales strategist , founder of Sales Beyond Scripts, to talk about the real ways AI is changing revenue, planning, and scale. They cover AI as a thinking partner, how to use it across departments in a small business, why audits matter more than hype, and how mindset quietly determines whether you treat AI as a threat or an advantage. Episode summary This episode is part of Susan’s 30-episodes-in-30-days “podcast to book” sprint for Swan Dive Backwards. Susan and Gazzy zoom in on the selling process first. Then they zoom out to the whole business. They talk about three...
info_outlineMost teams are stuck in tool obsession: “Should we build agents?” “Should we buy this AI platform?” In this solo, workshop-style episode, host Susan Diaz pulls you back to reality with a simple decision guide: buy vs bolt-on vs build, four leadership filters, and a practical workflow exercise to help you choose the right approach - without falling for agentic fantasies.
Episode summary
Susan opens with a pattern she’s seeing everywhere: 75% of AI conversations revolve around tools - agents, platforms, add-ons - and they’re often framed as all-or-nothing decisions. She reframes it: AI is best understood as robotic process automation for the human mind, not a single agent replacing a person or a department.
This episode is structured like a mini workshop. Susan asks you to grab paper and map a real workflow step-by-step - because the decision isn’t “which AI tool is hot” it’s what job are we automating.
Then she defines the three choices leaders actually have:
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Buy: purchase an off-the-shelf solution that works as-is.
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Build: create something custom (apps, integrated experiences, models).
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Bolt-on: the underrated middle path - use tools you already have (enterprise LLMs, suites), then add custom GPTs/projects, prompt templates, and lightweight automations.
She introduces a six-level “ladder” from better prompts → templates → custom GPTs/projects → workflow automation → integrated systems → custom builds, and offers a gut-check on whether your “agentic dreams” match your organizational capacity.
Key takeaways
Start with the job-to-be-done, not the tool. The most common mistake is choosing tech before defining the workflow. A workflow is simply a chain of small tasks with clear verbs and steps.
AI is RPA for your brain. Think “Jarvis” more than “replacement.” It’s about removing repetitive noise while keeping human judgement, discernment, and creativity in the lead.
Buy vs Build vs Bolt-on:
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Buy when you need reliability, guardrails, enterprise support, and the use case is common (summaries, note-taking, analytics).
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Build when the workflow is your differentiation, data is proprietary, outcomes are strategic, and you can support ongoing maintenance and governance.
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Bolt-on for most teams: fast, cheaper, easier to change. Start by layering custom GPTs/projects and lightweight automation on top of existing tools and licences.
Six levels of maturity (a ladder, not a leap):
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Better prompts (one-off help)
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Templates / prompt libraries (repeatable help)
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Custom GPTs / projects (consistent behaviour + knowledge)
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Workflow automation (handoffs between steps)
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Integrated systems (data + permissions + governance)
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Custom builds (strategic + resourced)
Four decision filters for leaders:
A) Repeatable workflow or one-off?
B) Is the value in the tech itself, or in how you apply it?
C) Data sensitivity and risk level? (enterprise controls matter)
D) Do you have operating maturity to run it? (monitoring, owners, governance, feedback loops)
Automation ≠ autopilot. Automation is great. Autopilot is abdication. If you ship first-draft AI output without review, you’ll get “garbage in, garbage out” reputational risk.
A simple friction-mapping exercise:
Map a 10-step workflow (open, check, find, copy, rewrite, compare, ask someone, format, send, follow up).
Circle the friction steps.
Label each friction point:
R = repeatable
J = judgement-heavy
D = data-sensitive
Then choose: buy / bolt-on / build based on what dominates.
Reality check for “agentic dreams”:
Before building:
Do you have a documented workflow?
Do you have a human owner reviewing weekly?
Do you have a feedback loop?
If not, you’re building a liability, not a system.
The real bet isn’t build vs buy. It’s this: “What repeatable work needs a personalised tool right now?”
Episode highlights
[00:02] Why most AI conversations are tool-obsessed (agents, platforms, add-ons).
[01:50] “RPA for the human mind” + the Jarvis analogy.
[04:14] Workshop setup: buy vs bolt-on vs build + decision filters.
[05:15] Step 1: define the job-to-be-done (not the department).
[08:13] The 10-step workflow template (open → follow up).
[10:49] Definitions: buying AI vs building AI vs bolt-on AI.
[14:13] The ladder: prompts → templates → custom GPTs → automation → integrated systems → builds.
[16:42] Filter A: repeatable vs one-off (and why repeatable is bolt-on territory).
[18:27] Filter C: data sensitivity and enterprise-grade controls.
[19:45] Filter D: operating maturity—where agentic dreams go to die.
[20:08] Automation vs autopilot (autopilot = abdication).
[21:24] Circle friction points + label R/J/D to decide.
[25:42] Reality check: documented workflow, owner, feedback loop.
[26:33] The takeaway: personalised tools for repeatable work beat agent fantasies.
Try the exercise from this episode with your team this week:
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Pick one recurring, annoying-but-important job.
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Map it in 10 simple steps.
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Circle friction points and label R / J / D.
Decide: buy, bolt-on, or build—and write: “For this workflow, we will ___ because the biggest constraint is ___.”
Connect with Susan Diaz on LinkedIn to get a conversation started.
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