Special Guest: Beyond the $10M Ceiling: Tech Truths from Bill Walker

The AI Brain Dump Dilemma

Bert shares his battle with AI context windows - that frustrating moment when Claude says "start a new conversation" just as you're making progress. This sparks a deep dive into how different AI tools handle long conversations, when they drift, and practical strategies for staying organized. From creating "cheat sheets" for your AI to organizing projects, backing up your work, and knowing when to start fresh - this episode is packed with actionable advice for anyone using AI regularly. Plus: why AI's memory limitations might actually be a point where humans still win. Bert and Julianna kick off with a Friday recording session. Bert's wearing something other than his signature black polo. Bert introduces the challenge: choosing which AI to use based on context window limitations. Claude cuts you off, ChatGPT slows down, Grok stays focused longer. Where Bert hits the limit: deep architecture and coding work. Going back and forth on "why" decisions, not just "what" to do. "It's like I'm calling into tech support... I've spent minutes explaining what's going on and then I have to talk to someone new." The frustration of losing context. Julianna asks: If you're using GPT to organize ideas for a book over three months, does it drift? Bert: "Totally. Drift is a more accurate term." Claude can now check previous conversations. "Let me look" - it searches your chat history to maintain continuity across sessions. Bert connects this to a timeless challenge: big projects are overwhelming. Where do you start? How do you organize context? Bert's tool for huge documents: Google's Notebook LM. Drop in congressional bills, documentation, ask questions, or convert to podcasts. Bert's strategy: Create multiple small conversations about specific aspects. Then make a "cheat sheet" - ask the AI to summarize what you've discussed so you can start fresh. Julianna's observation: Gen Z asks ChatGPT, Millennials Google it. Different approaches to finding information, both creating conversation clutter. Both tools have "Projects" features. Bert's example: Family cartoons for his boys, separate from work. Keeps context siloed with specific instructions per project. Bert's coding workflow: Python script pulls README, file tree, architectural decision records into a single file. Drop it in Claude when starting fresh. Julianna's scenario: Using AI for social media ideas over three months. Setting up projects, giving feedback, going on tangents. How do you stay organized? Bert's recommendation: Save AI summaries to Notion, OneNote, or Google Docs. Ask the AI to create a cheat sheet for itself, then document it. Long conversations slow down progressively. ChatGPT and Grok get slower with more history. Claude cuts you off to maintain speed. Julianna: This is where humans win. A developer or marketer who's been working on something remembers the context. AI is like a new intern every time. If you train AI on the hooks you like, all your hooks sound the same after a year. Humans bring fresh perspectives and challenge themselves to evolve. Bert shares a story of pushing Grok too far. It started forgetting things and led him into a coding corner. Had to go back to manual debugging. Julianna wraps with actionable steps: 1) Clean up miscellaneous chats, 2) Make backups on "digital paper," 3) Attach information to specific projects, 4) Keep living documentation that evolves.

How to Script Change Before It Derails

In this episode of Accelerating Humans, Julianna and Bert break down the concept of a "change script"—a practical tool for guiding people through transitions, especially when tech like AI is involved. Drawing inspiration from an MIT case study, they explore why even the smartest strategies can flop without a clear narrative. They share real-life lessons from AI rollouts and corporate transformations, and offer a simple framework leaders can use to get buy-in, ease confusion, and avoid resistance. From the "could vs. should" framework to understanding when to use AI versus automation, this episode cuts through the hype with practical guidance. Whether you're leading change, reacting to it, or just trying to make sense of what's next, this episode offers sharp insights—and a few hard truths—about what it really takes to move people forward.

AI On Your Org Chart

What happens when a chatbot has a name and introduces itself as a team member? Bert and Julianna tackle the provocative question: Should AI agents appear on your organizational chart? From phone answering assistants named Jennifer to the "agentic era" where AI has access to company tools, this conversation explores the practical and philosophical implications of AI as a colleague. They discuss how to position AI agents on teams, what happens to entry-level positions, interviewing for AI collaboration skills, and the critical importance of human judgment. Plus: why treating AI politely might actually get you better results, and the edge cases where human empathy can't be replaced. Join the Presale - Automate to Accelerate - Accelerating Humans [https://acceleratinghumans.com/presale/] Episode Highlights: Julianna encounters a chatbot that introduces itself by name, as if it's a team member. This sparks the central question: Should AI be on your org chart? Bert reveals he's already deployed named AI agents: Jennifer answers phones, and the CEO's digital assistant handles rejected calls. AI is already on the team. Bert introduces the concept of the "agentic era" - where AI agents have access to company tools and can take actions independently, not just respond to queries. "The org chart probably should include the AI... but we're not gonna do it because that's not the way that people think." Bert on why this matters for organizational transparency. Will candidates be evaluated on how well they work with AI? Discussion of AI archetypes and whether employees can leverage AI to add value to the company. Not every company needs AI. Bert notes 7-10% of Americans don't have smartphones and are fine. Some businesses don't need "all this crap" - it's about strategic fit. Julianna asks: What does the relationship look like when AI is your coworker? Who's teaching whom, and how do workplace dynamics change? Being polite to AI costs more (more tokens) but gets better results. Bert explains why humanizing AI with "please" and "thank you" improves prompt quality. Bert's recommendation: Frame AI as a junior team member here to assist. Set clear expectations about what it can do and emphasize that humans still own the output. "I'd actually get the intern in still and pair it with the AI and say, you guys knock yourselves out and see what I get." Human-AI collaboration at the entry level. The future: One human managing five AI agents answering customer calls. How do you track performance and attribution when AI is doing the work? Bert's warning: Companies chasing efficiency now might harm productivity five years out. "They're eating their young" by replacing entry-level positions with AI. AI agents specialized in different capabilities - like second-tier support. But they lack human sympathy and context for edge cases. Julianna's airline story: A customer service rep who stayed on hold and "thought outside the box" to solve a unique problem. Why human empathy and creative problem-solving can't be replaced.

Build or Buy: The Framework for Smart Tech Decisions

Should you build a custom solution or buy something off-the-shelf? It's one of the most common decisions facing businesses today, yet most teams approach it without a clear framework. Bert and Julianna tackle real-world scenarios from luxury hotels to trucking companies, sharing a research-backed decision tree. From the $10/month hotel checkout app to the $500K logistics platform, they break down the core factors: differentiation value, technical complexity, compliance risk, and total cost of ownership. Plus the stories behind homegrown systems that became technical debt nightmares. Julianna opens with the classic dilemma: "Are you a DIY or are you more of a 'I'm gonna call someone'?" The philosophy behind when to do it yourself vs. hiring experts applies to business tech decisions too. Bert's key insight: "How core and how critical is it to what differentiates me in the market?" If you're doing something no one has done before, you build. If it's well-defined, someone's already solved it. First case study: Luxury hotel chain needs late checkout coordination with housekeeping. $10/user/month app vs. tweaking existing scheduling tools. 220 employees, $40M revenue. Julianna argues for building using existing scheduling systems. Bert counters with the "borrow" approach - $26K isn't much for a $40M company, and you can learn what works before committing. Artisanal coffee roaster case: $2,500/year Shopify plugin vs. Excel spreadsheet management. Both hosts immediately agree: "That's a no-brainer. I'd buy that." PCI compliance makes the decision easy. Urgent care self-check-in kiosk: $250K system vs. repurposing iPads. HIPAA compliance and mixed medical records create massive complexity. "It's not worth building it for 250K." The big one: $500K/year fleet management platform vs. patching homegrown Access database. 2,500 employees, 12 states, core business competency. Vendor lock-in vs. technical debt trade-offs. Julianna's CFO perspective: "Are operations going to expand where we can recoup 500K?" If you can add one extra stop per driver per day, that's 300,000 additional stops annually. Marriott's homegrown payroll system that couldn't handle changing overtime laws. "Green screens" from 30-40 years ago. Why technical debt builds up and becomes unmaintainable. How AI accelerates proof-of-concept development. "You're able to develop a proof of concept using AI much faster, show that the thing works and de-risk the entire operation." The future of build vs. buy decisions. 03:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=180s] Core Differentiation Framework 04:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=240s]Hotel Checkout Scenario 08:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=480s]Build vs. Buy Debate 11:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=660s]Coffee Subscription System 13:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=780s]Healthcare Kiosk Complexity 20:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=1200s]Trucking Fleet Management 24:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=1440s]ROI and Expansion Plans 31:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=1860s]Technical Debt Horror Stories 34:00 [https://www.youtube.com/watch?v=BUILD_OR_BUY_VIDEO_ID&t=2040s]AI Changes Everything

Special Guest: Beyond the $10M Ceiling: Tech Truths from Bill Walker

Episode Summary Bill Walker—aka the Purple Squirrel—is the guy CEOs call when they’re stuck at the $10M ceiling and spreadsheets are running the show. With roots in both marketing and IT, Bill doesn’t just build systems—he diagnoses workflow dysfunction at the core. In this conversation, Bert and Julianna dig into: * The myth of “just needing a better system” * How to know when your tech stack is the problem vs. the symptom * Bill’s turning point—when a nurse told him his new system was “the worst thing I’ve ever seen” * What happens when you build cool crap no one actually uses If you've ever felt like your company is buried under 32 different tools (yes, Bill’s seen it), or if you're trying to scale but your ops are held together with duct tape and Smartsheets—this one's for you. * What “Purple Squirrel” really means (and why Bill owns it) * Workflow vs. System thinking * The $10M revenue ceiling (and why so many orgs stall there) * Why listening beats coding, every time * How to spot where growth is breaking your ops * Engaging the people doing the work in system design * Real-world stories from healthcare, manufacturing, and beyond * Tech doesn’t fix chaos. Process does. * The $10M ceiling is real. Growth reveals the cracks you’ve been ignoring. * Listening is a technical skill. Start there, not with a shiny new app. * People won’t use what they didn’t help build. Get the nurse’s input before launching anything. * Your ERP is not a cash drawer. (Yes, that actually happened.) * Workflow Innovators – Bill’s company * “The Worst Thing I’ve Ever Seen” story (Shelton, WA) * ERP horror stories and “The Expense Spreadsheet” that wasn’t Bill Walker is the founder of Workflow Innovators and a true “Purple Squirrel”—part technologist, part business strategist, part therapist. With 25+ years of experience across healthcare, manufacturing, and payments, Bill specializes in helping mid-size companies break past operational bottlenecks—often by not buying a new tool.