Accelerating Humans

Bert Carroll and Julianna Fricchione
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What if tech didn't make life harder—but actually helped us think better, move faster, and stay human in the chaos? Welcome to Accelerating Humans, where we decode the wild intersection of AI, business, and real-life problem solving. Hosts Bert (a no-BS CTO) and Julianna (an HR/ops pro with stories for days) break down what’s real, what’s hype, and how to make smarter moves—at work and beyond. Each episode is: A candid convo, not a keynote. Packed with analogies, insights, and “okay but how?” tactics. Designed to help you say “I can,” even if you’re not a techie. Whether you’re building

الحلقات

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    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.

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    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.

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    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 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.

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    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 Core Differentiation Framework 04:00Hotel Checkout Scenario 08:00Build vs. Buy Debate 11:00Coffee Subscription System 13:00Healthcare Kiosk Complexity 20:00Trucking Fleet Management 24:00ROI and Expansion Plans 31:00Technical Debt Horror Stories 34:00AI Changes Everything

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    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.

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    Empathy is Your AI Superpower

    AI might be great at optimization—but it still can’t look you in the eye and feel what you're going through. In this episode, Bert and Julianna explore why empathy isn’t just a soft skill anymore—it’s a power skill. From recruiting to layoffs, project planning to tech implementations, we break down how real human connection impacts business outcomes. And we ask the big question: If AI can do the technical work, what’s left that only humans can do? We’ll talk about: The recruiter who felt “seen” during onboarding—and why that matters Why ghosting job applicants isn’t just rude, it’s broken When silence speaks louder than chatbots How to build empathy into your tech projects The case for slowing down in an AI-accelerated world This isn’t about resisting technology. It’s about remembering what makes us irreplaceable. Empathy as a workplace differentiator Soft skills vs. AI capabilities HR + AI: where it helps and where it fails Reading body language, silence, and emotional nuance The ethics and limits of “empathy” in machines Julianna Fricchione – HR and project leader who believes your emotional intelligence is your edgeBert Carroll – CTO and system-thinker challenging the limits of what AI can really replicate

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    The Power of “I Can” How Human-AI Collaboration Removes Excuses and Unlocks Action

    Episode Summary You know that little voice that says, “I can’t”? We’re coming for it. In this episode, Bert and Julianna tackle the mental roadblocks that stop us before we even begin — whether it’s building a website, switching careers, or running a marathon. Bert shares how AI has become his favorite way to get unstuck: it gives you a starting point, fast feedback, and the ability to skip perfection and just do the thing. Julianna brings the real-life “people stuff,” showing how AI can meet you wherever you’re at — and shift you from “I can’t” to “I just did.” How AI can help break down “I can’t” moments into action steps Why you don’t need to master something to get results (hello 80/20 rule) Tools and prompts that help you learn by doing Real-world examples: coding, websites, marathons, and even party planning The mindset shift that changes everything: start simple, iterate fast “The perfect is the enemy of good. AI gives me a version to react to — and that’s all I need to start.” — Bert “AI is like a teacher that adapts instantly to you. You give it feedback, and it gets better — fast.” — Julianna GPT / Gemini for planning, coding, coaching Notion, Squarespace, Wix for quick website builds Custom GPTs trained on your own tone and style You don’t need permission. You need a rough draft.Start where you are, use the tools, and move. AI just makes it harder to keep saying “I can’t.” 🧠 What You'll Learn🔥 Favorite Quotes🛠️ Tools & Prompts Mentioned🎯 TL;DR Takeaway

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    Frankenstack Overload: Why Your Tools Aren’t Helping—and What to Do Instead

    Welcome to Accelerating Humans! In this episode, Julianna and Bert tackle the beast lurking in most businesses: the Frankenstack—that overgrown mess of software, systems, and apps duct-taped together over time. They talk candidly about how teams wind up with tech stacks that don’t serve them, why chasing the newest tools (including AI) often creates more problems, and how to start unwinding the chaos with a practical, human-first approach. Whether you’re in HR, IT, or ops—or just trying to survive your calendar—this episode will help you rethink your relationship with tools and take a more strategic (and less exhausting) path forward. In this episode: What is a Frankenstack, really? The hidden cost of layering tools without strategy Why process—not software—is the real solution Practical steps to start cleaning up your tech clutter How to make sure you’re not just automating dysfunction 🎯 Great for business leaders, tech leads, ops folks, and AI-curious humans who are tired of chasing the next shiny platform. Timestamps [00:00] Julianna confesses her AI tool hoarding problem [01:20] Bert explains what a Frankenstack is—“Frankenstein glued together with Zapier” [03:00] How teams end up with too many tools [05:15] The illusion of control: when “custom everything” backfires [07:40] Bert: “You’re just automating your dysfunction” [09:30] Why chasing AI features creates more chaos [12:00] Real example: trying to manage onboarding across 4 platforms [15:30] The red flag checklist: how to know you’ve got a Frankenstack [18:20] Julianna’s 30-day tool test: keep or cut [21:00] How to run a stack audit (without annoying everyone) [25:00] Process first, software second: how to pick what stays [28:30] Cleaning up the stack without disrupting workflow [32:00] Common mistakes: letting each team pick their own tools [35:00] What better looks like: leaner, cleaner systems [38:30] Final thoughts: you probably don’t need another tool—just a plan Free Download: Mentioned tools: Slack, Google Drive, Zoom AI Companion, ChatGPT, Trello, Asana Julianna Fricchione – Ops & HR brain who’s trying to make tech actually work for people Bert Carroll – CTO, lover of clean systems, allergic to pointless software

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    Train Your Bot to Sound Like You (Not Like Everyone Else)

    Tired of AI spitting out polished-but-soulless copy? In this episode of Accelerating Humans, Bert and Julianna break down how to train your AI tools so they sound like you—not like a corporate consultant or a recycled LinkedIn post. You’ll hear: How Bert built his “Bert GPT” with banned phrases, tone settings, and personality quirks. The simple, under-10-minute process to train ChatGPT (or any AI) to match your style. Why “sounding like everyone else” kills engagement—and how to fix it. Real-world examples of “Bad GPT” vs. “Bert GPT” answers. The secret to using AI without losing your human voice. Whether you’re writing emails, drafting LinkedIn posts, or creating client content, this episode shows you how to make AI work with you—not replace you. Keywords for SEO: AI training, ChatGPT customization, business communication, branding with AI, LinkedIn content, voice personalization, productivity tools, marketing automation. [00:00] – Why losing your voice to AI is a real risk.[01:00] – Julianna’s take on copy-paste LinkedIn posts and “robot voice.”[03:00] – What “robot style” really is and how large language models learn.[05:00] – Bert’s banned word list and the “circle back” ultimatum.[07:00] – How to customize ChatGPT in minutes.[09:00] – What data to feed your bot to match your tone.[11:00] – Why untrained AI kills conversions, even with the same open rates.[13:00] – Bad GPT vs. Bert GPT: real example comparisons.[15:00] – The two most important steps to train your AI.[18:00] – Why AI should be personalized like your phone or car settings.[20:00] – How little time it really takes to get results.[22:00] – Creating different bots for different audiences.[24:00] – Final takeaway: AI as a starting point, not the final draft. In this episode, we cover: The “robot voice” problem – why untrained AI sounds the same. Customization 101 – banned words, tone settings, and style guides. Data feeding – what examples to give AI so it mimics your real communication style. Efficiency vs. authenticity – keeping speed without losing personality. Bert’s personal hacks – different bots for CEOs, long-form content, and quick updates. Style Guide: https://acceleratinghumans.com/episodes/2503-ai-training-guide/

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    AI and Bias- Who's Programming the Rules?

    Episode Summary:In this candid episode, Bert and Julianna dive into the often uncomfortable topic of bias in AI. They unpack how algorithms can inherit human prejudices, why even “neutral” data isn’t neutral, and who gets to decide what’s fair in automated systems. Bert brings the tech angle—how models are trained, what’s possible (and what’s hype). Julianna grounds it in people’s real experiences—especially in HR, hiring, and everyday workplace systems. Whether you're building AI tools or just wondering how they might impact your job or community, this episode gives you a practical and human-centered look at the biases baked into the systems we trust. In This Episode: Why AI isn't as objective as it sounds The “garbage in, garbage out” problem in training data Real examples of biased AI in hiring and finance Why compliance doesn’t mean ethical How companies can approach AI responsibly (without BS buzzwords) What to ask before trusting an algorithm at work Favorite Quote: “Bias doesn’t go away when you automate it. It just gets faster.” Timestamps (for YouTube or chapters): 00:00 – Cold open: “Can AI be racist?” 02:15 – The myth of neutral data 08:40 – HR and hiring tools: built-in bias? 15:10 – Bert’s breakdown of how AI learns 22:00 – Julianna’s “people-first” take on tech trust 28:30 – How to audit and question AI systems 34:00 – What we’d do differently as leaders Stephen Wolfram Thought piece referenced by Bert- https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/

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  11. Change Archetypes: How People React to AI (and What to Do About it)

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    Change Archetypes: How People React to AI (and What to Do About it)

    In this episode, Bert and Julianna unpack the emotional rollercoaster of tech adoption—especially AI—in the workplace. Triggered by a headline claiming AI is “already taking jobs,” they dive into the real issue: how different types of people react to technological change. From early adopters to skeptics, they break down the "change archetypes" you’ll meet in any organization and how to work with each. Whether you’re leading a tech initiative, worried about automation, or just trying to convince your team to stop printing things, this episode gives you a practical lens to understand resistance—and momentum. The Pioneer: All in, excited, tinkering immediately. The Analyst: Needs data, KPIs, and ROI before acting. The Warrior: Afraid tech will take their job—needs reassurance and upskilling. The Guardian: Concerned about ethics, risk, and safety—must be looped in early. The Opportunist: Sees dollar signs—moves fast, sometimes recklessly. The Humanitarian: Focused on fairness and impact—wants equitable outcomes. The Resister: Just wants things to stay the same—change feels like a threat. Identify which archetypes exist in your org. Tailor your messaging and involvement strategies. Empower pioneers and analysts to lead the charge. Involve guardians and warriors early to reduce friction. “People haven’t changed. The tools have.” “Change is risk—but it’s also the way forward.” “Your pioneers are your prophets—find them early.” Julianna compares AI resistance to paper-to-digital onboarding pushback. Bert reminds us: “If legal doesn’t know about your rollout, you’re gonna get shut down.” 00:00 – The AI job-loss headline that sparked the convo 01:30 – Introducing the change archetypes 04:00 – Why AI fear is really just old-school resistance 09:00 – Deep dive on the Pioneer and Analyst 12:00 – How to handle the Warrior archetype 14:00 – Why Guardians are secretly your best allies 18:00 – Pilots, autopilot, and what AI can (and can’t) replace 20:00 – Implementation advice: involve early, iterate often What archetype are you? What about your team? Share this episode with someone who needs help navigating the messy middle of change. Take the quiz here We'd love to here from you. You can contact us at hello@acceleratinghumans.com

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    Accelerating Humans Trailer

    What if tech didn't make life harder—but actually helped us think better, move faster, and stay human in the chaos? Welcome to Accelerating Humans, where we decode the wild intersection of AI, business, and real-life problem solving. Hosts Bert (a no-BS CTO) and Julianna (an HR/ops pro with stories for days) break down what’s real, what’s hype, and how to make smarter moves—at work and beyond. Each episode is: A candid convo, not a keynote. Packed with analogies, insights, and “okay but how?” tactics. Designed to help you say “I can,” even if you’re not a techie. Whether you’re building something big, adapting to change, or just tired of the same jargon-packed LinkedIn posts—this is for you. New episodes weekly. No fluff, just the good stuff.

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What if tech didn't make life harder—but actually helped us think better, move faster, and stay human in the chaos? Welcome to Accelerating Humans, where we decode the wild intersection of AI, business, and real-life problem solving. Hosts Bert (a no-BS CTO) and Julianna (an HR/ops pro with stories for days) break down what’s real, what’s hype, and how to make smarter moves—at work and beyond. Each episode is: A candid convo, not a keynote. Packed with analogies, insights, and “okay but how?” tactics. Designed to help you say “I can,” even if you’re not a techie. Whether you’re building

المعلومات

  • صناع العمل
    Bert Carroll and Julianna Fricchione
  • سنوات النشاط
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  • الحلقات
    ١٢
  • التقييم
    ملائم
  • حقوق النشر
    © Bert Carroll and Julianna Fricchione
  • موقع البرنامج على الويب
    Accelerating Humans