Burn The Map

In This Episode:

We talk to Grant Fuellenbach about the part of growth most operators ignore until it starts setting money on fire: the back office. Grant works with builders and trades businesses where the work is real, the margins matter, and the systems are often being held together with duct tape, habit, and optimism. He breaks down what actually happens when a company starts growing before its workflows do—and why more leads, more projects, and more hires can make the business worse if the backend never catches up.

We also get into the difference between useful AI and shiny-object AI. Grant walks through how he diagnoses workflow bottlenecks, why most businesses have no idea where their time is actually going, and how tools like NotebookLM, AI-native CRMs, and simple automations can make a business dramatically more functional—if you use them with discipline. This is a practical conversation about systems, signal vs. noise, and why most automation templates floating around online are, frankly, trash.

What We Cover:

• Why the trades are still massively underserved by software—and what that breaks downstream

• How to diagnose workflow problems before blindly throwing AI at them

• The "do, delegate, delete, defer" framework for figuring out where your time actually goes

• Why CRM bloat is creating more friction than value

• How Grant uses NotebookLM for learning, competitor research, and content planning

• The difference between real automation and brittle template theater

• Why long-form content still has an edge in an internet filling up with AI slop

• How weekly reviews and feedback loops help operators stop guessing and start improving

Enjoy the episode. This show is brought to you by Wrench.ai.

Guest Bio:

Grant Fuellenbach is an automation and workflow operator focused on the construction and trades space. He helps growing businesses clean up their backend systems, optimize CRM workflows, improve pipeline visibility, and use AI in ways that actually reduce chaos instead of creating more of it. He also hosts the podcast Beyond The Bid, where he explores systems, growth, and operational efficiency for builders and service businesses.

Follow Dan: LinkedIn:https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Grant:

LinkedIn:https://www.linkedin.com/in/grantfuellenbach/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky:https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• Grant Fuellenbach on LinkedIn: https://www.linkedin.com/in/grantfuellenbach/

People and Organizations Mentioned:

• Wrench.ai

• HubSpot

• Salesforce

• Day.ai

• Claude

• NotebookLM

• Gamma

• Opus

• Todoist

• JobTread

• Alex Hormozi

• GE

• Jack Welch

• Beyond The Bid

Show Notes & Timestamps:

• 00:08 — Beard talk, builders, and why the trades deserve better software

• 01:00 — Why Grant got into the construction workflow space

• 02:20 — Diagnosing systems instead of pretending every problem is unique

• 04:25 — Pipeline accuracy, tracking, and getting real-world data into CRM

• 05:47 — HubSpot, Salesforce, GoHighLevel, and CRM fatigue

• 06:51 — Why AI-native CRM interfaces may eat traditional SaaS

• 08:46 — Agentic tools, second-mover advantage, and avoiding shiny-object traps

• 10:48 — Time audits and the "do, delegate, delete, defer" framework

• 12:04 — Using NotebookLM to summarize YouTube and kill the fluff

• 14:03 — Grant's AI stack: Gamma, NotebookLM, and fast podcast repurposing

• 16:21 — Competitor research and building 90-day content calendars with NotebookLM

• 18:17 — How to use AI to learn faster, not just produce faster

• 19:31 — Why audiences hate AI content when they can smell the shortcut

• 21:59 — Inbound growth through diagnostics and assessments

• 23:47 — Personality models, employee satisfaction, and where psych frameworks break

• 25:19 — Turning personality reports into practical weekly planning

• 26:57 — Matchmaking, communication patterns, and sales velocity

• 29:16 — Working yourself out of a job through better systems

• 30:07 — The RICE framework for prioritizing what matters

• 32:22 — What AI gets wrong, and how Grant cross-checks models

• 34:21 — Long-form vs short-form in the age of AI-generated content

• 35:29 — Why most automation templates are garbage

• 39:53 — Todoist, swipe files, and building an automated second brain

• 41:58 — Feedback loops, weekly reviews, and actually learning from your own work

• 45:40 — Where to find Grant and his podcast, Beyond The Bid

In This Episode:

We sit down with Christian Hammer (Founder & CEO of Ngentix) to talk about the unsexy problem that breaks AI in the real world: execution across messy systems. Christian calls what he's building "AI plumbing in the wall"—the infrastructure layer that connects tools, enforces policy, and kills the drudgery (think: PDF → QuickBooks copy/paste hell) without pretending an LLM is magically reliable.

This one is for product-minded builders: we get into why "agents" can make operations worse if you don't have a system of record, why momentum beats velocity, and how the future UI probably isn't another dashboard—it's zero UI. Tech fades into the background, humans get their time back.

What We Cover:

• Why tech disruption isn't new—the speed is what's brutal now

• LLMs as the next abstraction layer (and why that's a once-in-a-generation shift)

• Evergreen skills that won't get obsoleted: engineering thinking, empathy, philosophy

• The missing piece in most companies: a system of record for execution

• "Sarah's time off": the human router bottleneck hiding inside every org

• Why most teams get faster at doing the wrong thing (and call it "progress")

• Agile vs "Fragile": why momentum (mass + velocity) is the metric that actually matters

• Zero UI / ambient automation: software shouldn't be the center—you are

• Authenticity backlash: why AI-generated everything makes human-made more valuable

Guest Bio:

Christian Hammer is the founder and CEO of Ngentix (https://ngentix.ai), building "AI plumbing in the wall"—automation infrastructure that connects systems, eliminates business drudgery, and creates a system of record for execution when humans (and agents) need to know what happened, why it happened, and what to do next. He's also an inventor, author, podcaster, and working artist focused on making technology feel less like "the tyranny of the terminal" and more like something humans can actually live with.

Enjoy! This show was Brought to you by Wrench.ai

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Christian:

LinkedIn: https://www.linkedin.com/in/chammer1/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• Ngentix: https://ngentix.ai

• Christian's hub: https://christianhammer.io

• Christian's art: https://c-hammer.com

People and Organizations Mentioned:

• Christian Hammer

• Dan Baird

• Ngentix

• Wrench.ai

• Claude / Claude Code

• Crab & Oyster painting: https://c-hammer.com/oilpaintings/oyster-shooter-crab-dinner-oil-on-wood-panel-painting/

Show Notes & Timestamps:

• 02:53 - Tech disruption isn't new—it's the speed that's different now

• 04:11 - LLMs as the next abstraction layer (and why that matters)

• 07:45 - Evergreen skills: engineering mindset, critical thinking, empathy, and philosophy

• 11:18 - What Christian is building: a system of record for execution (because agents don't magically fix ops)

• 13.28 - "Chief": why the real unlock is clarifying intent and defining "done"

• 16.49 - Why Christian doesn't trust LLMs (and why you shouldn't either—without guardrails)

• 17:17 - The drudgery thesis: OCR + NER + automation to kill the "PDF → QuickBooks" nonsense

• 19:14 - "Sarah's time off": the hidden human routers inside every company

• 23:34 - Agile vs. "Fragile": velocity is incomplete—momentum (mass + velocity) is the real metric

• 32:51 - The future: tech disappears into the background—plumbing in the wall, more human-to-human value

• 35:07 - Art, authenticity, and the pullback from AI-generated everything

• 36:30 - Zero UI / ambient automation: the tool shouldn't be the center—you are

In This Episode:

We talk to David Espindola about the part of the AI boom most companies keep trying to skip: the boring, unsexy work that makes AI real—problem definition, strategy, governance, and trust.

David's written two books (The Exponential Era and Soulful) and spends his time thinking about what happens when exponential tech stops being a keynote and starts breaking things in production. We get into why "go do AI" is an executive-level failure mode, how to decide whether you're a maker, shaper, or taker, and what it actually takes to build AI agents you can trust—especially when incentives (ads), privacy, and security start pulling the strings.

What We Cover:

• Why "we must be an AI company" is a terrible mandate if you can't name the problem you're solving

• The Makers / Shapers / Takers framework (and why most teams should aim for "shaper," not "maker")

• Why AI ROI is so messy right now (and how bad benchmarking + vague goals make it impossible)

• Agents and non-determinism: the uncomfortable truth that "it worked 26 times" means nothing

• How David built Zena, his AI colleague—using RAG to ground the assistant in his knowledge, values, and working style

• The trust-killers: ads, misaligned incentives, weak security, and "agents in prod" without guardrails

Guest Bio:

David Espindola is the author of Soulful and The Exponential Era, and the creator of Zena, an AI colleague built around a simple premise: if you can't trust the system, it's not helping—you're just outsourcing risk. David works at the intersection of AI strategy, change management, and human–AI collaboration, with a practical bias toward governance, security, and using AI where it actually fits (not where it looks good in a board meeting).

Enjoy! This show was Brought to you by Wrench.ai

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow David:

LinkedIn: https://www.linkedin.com/in/davidespindola/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• David's website: https://davidespindola.com/

• Brainyus: https://brainyus.com/

• Chat with Zena: https://brainyus.com/zena

• Podcast: Conversations with Zena, my AI colleague

People and Organizations Mentioned:

• David Espindola

• Dan Baird

• Wrench.ai

• McKinsey (makers / shapers / takers framework, referenced)

• OpenAI

• Anthropic

Show Notes & Timestamps:

• 00:57 — Why The Exponential Era came first; the SPX methodology (Agile + design thinking + more)

• 04:41 — Soulful: what AI is / isn't; emotional intelligence, trust, and turbulence ahead

• 07:51 — Biggest implementation mistake: "AI" as mandate vs starting with the problem

• 08:xx — Makers / Shapers / Takers strategy framework

• 12:26 — Abundance vs "trickle down"; why ROI is messy in early days

• 16:43 — 50-year hindsight: today will look primitive

• 19:46 — The myth that tech automatically reduces hours worked

• 23:12 — Zena: training an AI colleague; trust as the core feature

• 24:54 — Ads and incentives: when agents stop being trustworthy

• 26:26 — How David trains Zena (RAG, memory improving)

• 29:28 — Non-determinism: why testing AI isn't like testing traditional software

• 31:35 — When "agents" turn back into old-school software (APIs, reliability, cost)

• 33:52 — Where to find David + Brainyus + Zena

In This Episode:

We talk to Allen Martinez—founder at Noble Digital and author of The Brand Experience AI Operating System (BX AI OS)—about why so many "AI initiatives" are basically expensive science projects with a chatbot slapped on top.

Allen's take is refreshingly unforgiving: if you don't close the governance gap, the identity gap, and the accountability gap, you're not deploying AI—you're launching brand chaos at machine speed. We get into what it takes to turn AI from a black box into something you can actually run, audit, and improve… without letting marketing, sales, and support ship three different personalities to the same customer.

What We Cover:

• The three gaps that kill AI projects: governance, identity, and accountability—and why you need all three, not "we'll do that later"

• Why "we deployed a chatbot" is not a strategy (and how to think in terms of an AI operating system instead)

• How brand collisions happen when every department optimizes its own AI tool—and why customers feel it as pure friction

• Why "good enough at scale" becomes AI slop, and how taste + point of view becomes the real competitive edge

• What it means to make AI auditable ("glass box," not black box) before a regulator—or your CFO—comes calling

• The Chevy chatbot "legally binding $1 deal" story as a cautionary tale: not a meme, a governance failure

Guest Bio:

Allen Martinez is a founder at Noble Digital and the author of The Brand Experience AI Operating System (BX AI OS), a practical framework for taking AI from chaotic experimentation to scalable, brand-safe deployment. With a background spanning film/commercial directing and systems-driven brand execution, Allen focuses on the real-world mechanics of AI in production: behavioral governance, encoded brand identity, and accountability systems that produce receipts—not surprises.

Enjoy! This show was Brought to you by Wrench.ai

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Allen:

LinkedIn: https://www.linkedin.com/in/allenmartinez/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• https://nobledigital.com/

• https://allenmartinez.net/

• https://bxaios.com/

• Shadow Ledger assessment: https://bxaios.com/shadow-ledger

• The Brand Experience AI Operating System: https://www.amazon.com/dp/B0FWBSDMVR

• Free Access to the First Chapter: https://preview.mailerlite.io/forms/1780848/170432170750379532/share

People and Organizations Mentioned:

• Allen Martinez

• Noble Digital

• Wrench.ai

• ArtCenter College of Design (Pasadena)

• Linda Weinman / lynda.com (mentioned)

• Razorfish (training mentioned)

Show Notes & Timestamps:

• [~09:38] Why "brand" isn't your logo, it's the coherence layer that prevents org-wide collisions

• [~11:12] What are the "three gaps" that kill AI projects (governance, identity, accountability)?

• [~13:50] What does it mean to turn AI from a "black box" into a "glass box"?

• [~26:30] The Chevy chatbot "$1 legally binding deal" story—and why it's a governance failure, not a meme

• [~36:28] Why "good enough at scale" becomes brand death by a thousand cuts

In This Episode:

We talk to Jaime Jay about going from the 82nd Airborne to homelessness (more than once), to building a company that helps founders get their time back without blowing up quality, trust, or accountability.

Jaime is a hard-nosed systems thinker and one of the founders of Bottleneck Distant Assistants—where they train "distant assistants" (real humans, not "digital assistants") using a framework he calls Delegation Intelligence. We get into the unsexy truth: delegation isn't "hire a VA and pray." It's building a repeatable system so the business stops pinging you for every micro-decision. We also go deep on category design ("name it / frame it / claim it"), and why the real AI bottleneck isn't the model—it's behavior change inside the org.

What We Cover:

• What the military teaches you about structure, trust, and pain tolerance (and how that maps to founder life)

• How to build a delegation department (not just outsource tasks until everything breaks)

• Jaime's 4-step Delegation Intelligence loop: name it, confirm instructions, review/approve, create the signal

• Category design as a competitive weapon: market the problem, not your product

• AI in ops: why "ChatGPT can do it" is often cope, and where AI burnout shows up fast

• Hiring at scale + vetting trust: what it takes to screen thousands without inviting chaos into your systems

Guest Bio:

Jaime Jay is a military veteran (82nd Airborne), founder, and category-minded operator focused on one thing: helping leaders stop getting crushed by the day-to-day. He's one of the founders of Bottleneck Distant Assistants, where their team trains and places "distant assistants" using a structured delegation framework ("Delegation Intelligence") built to reduce admin drag, improve follow-through, and make delegation actually stick.

Enjoy! This show was Brought to you by Wrench.ai

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Jaime:

LinkedIn: https://www.linkedin.com/in/jaimejay/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• Bottleneck Distant Assistants: https://bottleneck.online

• Delegation IQ Blueprint: https://bottleneck.online/delegationiq-blueprint/

• Quit Repeating Yourself (book): https://a.co/d/0cUUqYtH

• Military CreatorCon Event: https://www.militarycreatorcon.com/

People and Organizations Mentioned:

• Jaime Jay

• Bottleneck Distant Assistants

• 82nd Airborne

• Christopher Lockhead (mentioned as "godfather of category design")

• James Amar (Military CreatorCon)

• Brian Scudamore (1-800-GOT-JUNK; Dragon's Den)

• Whole Foods, Amazon, GoPro (category examples)

• David Goggins (grit example)

Show Notes & Timestamps:

00:08 — Dan's intro: Jaime's background (founder, veteran, systems thinker) 01:34 — Homelessness, Army, divorce, and walking from Rancho Cucamonga to Huntington Beach 04:31 — Why Jaime loved the 82nd Airborne; structure, training, and failing RIP 06:10 — Failure, pain tolerance, and why entrepreneurs keep going 13:57 — What homelessness teaches you about people, pride, and getting a "leg up" 16:48 — Category design: name it / frame it / claim it; "market the problem" 19:33 — "Delegation Intelligence" + the core problem: founders trapped running vs. growing 22:41 — The 4-step delegation system: name it, confirm instructions, review/approve, create the signal 27:09 — Hiring + vetting at scale: 7,000 interviews, 658 presented (Jaime's numbers from interview) 30:03 — "Distant assistants" (not digital); 93-video certification; six roles they support 31:44 — AI shifts roles; calculators-in-class analogy; avoid AI overwhelm/burnout 35:22 — Dan on AI's real challenge: behavior change + implementation, not just "the model" 43:21 — Why "Burn The Map" isn't "ignore the map"—it's "outgrow it" 43:49 — Military CreatorCon + category design intensive with Christopher Lockhead 47:32 — Where to find Jaime; Delegation IQ Blueprint 48:11 — Jaime's book: Quit Repeating Yourself

In This Episode:

We sit down with Monica Marquez, co-founder of Flipwork AI and the unofficial change management therapist every modern exec wishes they had on speed dial. Monica's resume is a "who's who" of places that love an acronym—NYU, Goldman Sachs, EY, Bank of America—so trust me, she's seen every flavor of corporate resistance to tech you can imagine.

Monica calls out the dirty little secret of AI in the enterprise: Buying the tech is easy; getting humans to actually use it (without mangling your workflows and ROI) is the real Olympic sport. She dishes on why middle managers are often the AI adoption bottleneck, how automation at scale can make your mistakes embarrassingly public, and why "working harder" stopped mattering the second AI walked in the door.

What We Cover:

• The very real gap between AI purchase and AI adoption—why executives fret and middle management digs in its heels

• How Monica's "Duolingo meets Deloitte" approach gets humans and agents collaborating, not colliding

• Why your old playbook is officially dead, and how agentic humans will reshape the org chart (bye, endless middle management layers)

• The sneaky cultural reasons why some employees see AI as "cheating" (and how to flip that mindset)

• How to AB-test workflows and build custom agents your team will actually use—because shelfware isn't a KPI

• Behind-the-scenes stories on avatars in HR, bias in screening, and why writing an erotic Victorian cover letter won't get you that ML ops job (but it might make you laugh)

• Monica's tactical stack of must-have AI tools: what she actually uses, what's just hype, and why you still need to get your hands dirty

Guest Bio:

Monica Marquez is the co-founder of Flipwork AI—a company that specializes in getting humans and AI to work together without burning the place down. A recovering head of talent and champion for diversity in tech, Monica spent 20+ years wrangling people problems everywhere from big banks to Big Four consultancies. She sits on the board of ALFA (Association of Latin Professionals for America, for Latinas in Tech) and publishes the "Ay Ay Ay AI" newsletter—because yes, she's always the first to kick the tires on new tools, and she's not afraid to tell you what actually works. If you want tips, tough love, and truths about closing the gap between AI hype and real change—Monica's your person.

Enjoy! This show is brought to you by Wrench.ai.

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/

X: https://x.com/mrdanbaird

Follow Monica:

LinkedIn: https://www.linkedin.com/in/themonicamarquez/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast

Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/

TikTok: https://www.tiktok.com/@burnthemappodcast

BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• Monica's site/newsletter: themonicamarquez.com

• Flipwork AI

• "Ay Ay Ay AI" Newsletter

People and Organizations Mentioned:

• Monica Marquez

• Flipwork AI

• EY, NYU, Goldman Sachs

Show Notes & Timestamps: 00:00 — Why "implementing AI" will break you if you skip change management 06:00 — The hidden ROI-killers nobody benchmarks 13:00 — Psychological barriers: cultural myths, effort vs. impact, and why your team thinks using AI is cheating 20:00 — Reinventing workplaces: agentic humans, clones, and eliminating monotony 30:00 — Bias in hiring, avatars in interviews, and why everyone suddenly has a "perfect" resume 40:00 — Tools Monica actually uses—and which ones are overrated 46:00 — Why middle management is now an endangered species 49:00 — How to find Monica, and why you'd better DM with something interesting

In This Episode: We sit down with Elizabeth Bieniek: accidental innovator, corporate plane-repairer at 30,000 feet, and author of Cake on Tuesday, a book for people who like their business advice with more real talk and less corporate fluff. Elizabeth walks us through her unpredictable path—from getting an MBA at Babson and tumbling into the tech world, to launching a stealth startup inside Cisco, and then finally distilling years of chaos into 25 lessons for unlocking corporate innovation. Why Cake on Tuesday? Because frankly, what's the point of slogging through strategy sessions if you're not enjoying the ride (and the cake)?

What We Cover:

• How to build a "startup inside the mothership" when corporate just wants you to stop asking why

• Why communication—not just coding—makes or breaks innovation

• The hard (but hilarious) truth about decision-making, feedback, and why you shouldn't listen to every single "mentor"

• Stories from the trenches: flying the plane while building it, collecting callouses (not just LinkedIn endorsements), and why you need to laugh, especially when everything's on fire

• How Elizabeth's book, Cake on Tuesday, became a survival guide for intrapreneurs, founders, and anyone allergic to syrupy corporate motivational posters

Guest Bio: Elizabeth Bieniek, author of Cake on Tuesday and host of the Cake on Tuesday podcast, is the kind of leader who asks "why"—loudly, persistently, and (let's be honest) a bit annoyingly—for the good of slapping sense into business as usual. A veteran of making new things happen inside giant corporations, she's passionate about helping real doers cut through the noise and actually get things done. Find her at CakeOnTuesday.com

Enjoy! This show was brought to you by Wrench.ai.

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Elizabeth:

LinkedIn: https://www.linkedin.com/in/elizabethbieniek/

Cake On Tuesday LinkedIn: https://www.linkedin.com/company/cake-on-tuesday/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast

Twitter/X: https://x.com/BurnTheMapPod

Instagram: https://www.instagram.com/burnthemappodcast/

TikTok: https://www.tiktok.com/@burnthemappodcast

BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• Cake on Tuesday

• ElizabethBieniek.com

• "Cake on Tuesday: 25 Lessons to Unlock Corporate Innovation"

• Wrench.ai

People and Organizations Mentioned in This Episode:

• Elizabeth Bieniek

• Dan Baird

• Cisco, WebEx Hologram

• Cake on Tuesday

• Wrench.ai

Show Notes & Timestamps:

• (00:17) How an ex-holography expert became the go-to for founders who don't want to crash their planes (or their projects)

• (03:29) Sneaking into Cisco as an English major: No, you don't have to write code to shake up big tech

• (07:18) Building startups inside the belly of the beast—less "special projects," more "just fix it already"

• (10:41) Writing post-mortems (the good kind, not the HR kind): How Cake on Tuesday became a book for people who'd rather laugh than cry

• (14:53) Why innovation is 90% persuasion and 10% trying not to strangle a "waffler"

• (18:49) The chapter everyone quotes: Don't Be a Flat Squirrel (you know who you are)

• (22:16) Reframing disagreement: Be disagreeable, just not a jerk

• (24:29) How to spot—and work with—actual doers (Hint: They're busy, but they'll still answer your call)

• (35:21) Staying sane: mantra walls, daily stoicism, and refusing to take yourself too seriously

In This Episode: We sit down with Dr. Craig A. Kaplan, the PhD-wielding brains behind Predict Wall Street (and, apparently, the patron saint of retail investors everywhere). Craig walks us through 14 years in the financial trenches, building tech to turn the "dumb money" crowd into a collective force that could actually beat Wall Street at its own game—at least until the hedge funds caught the scent and crashed the party.

Brace yourself for a story that's equal parts "wisdom of crowds," collective intelligence research, and "what happens when the little guy dares to play with the big boys." If you still think your hot stock tip has a shot, prepare to have that illusion gently (okay, not-so-gently) shattered.

What We Cover:

• How Craig built Predict Wall Street out of pure force of will (and maybe a touch of ignorance-is-bliss)

• Why smart money and dumb money aren't as predictable as you think

• How to use crowd signals, sentiment, and psychology for an actual edge (no, really)

• Why everyone else told him this was "impossible" (spoiler: Nobel laureates are not always right)

• The only three real ways to make money in the stock market—and why almost everyone gets it wrong

• What collective intelligence really means when the crowd is full of both geniuses and, well... not-geniuses

Guest Bio: Dr. Craig A. Kaplan isn't your average Wall Street whisperer—he's a pioneer in collective intelligence and the founder of Predict Wall Street, the platform that gave retail investors their brief moment in the sun before the hedge funds rained on the parade. Craig's research and tech have changed how people think about market signals, crowd psychology, and "dumb money" (newsflash: it isn't always so dumb). When he's not upending financial orthodoxy, you'll find him connecting the dots between AI, data science, and what's actually possible when you trust a million random brains more than a dozen "experts."

Enjoy! This show was brought to you by Wrench.ai

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Craig:

LinkedIn: https://www.linkedin.com/in/craigakaplan/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• Dr. Craig Kaplan LinkedIn

• Predict Wall Street

• The Wisdom of Crowds by James Surowiecki

People and Organizations Mentioned:

• Dr. Craig Kaplan

• Dan Baird

• TD Ameritrade

• Schwab

• NASDAQ

• "Dumb money" (sorry, retail investors—it's a Wall Street thing…)

Show Notes & Timestamps:

• The myth and math of "wisdom of crowds"

• Getting 14 years' worth of scars in fintech

• Why Wall Street's "smart money" can be its biggest liability

• How to mine "dumb" opinions for real alpha

• The limits of quant funds and why the real edge never lasts

• Financial luck, stubborn optimism, and the fine art of not giving up (even when everyone with a Nobel tells you not to bother)

• Why you should never underestimate the power of a good old-fashioned jelly bean guess

In This Episode:

We sit down with Dr. Craig Kaplan—the guy who was building AI before your favorite "disruptor" learned to tie their shoes. Dr. Kaplan takes us on a wild ride from the OG days of artificial intelligence (when data lived on floppy disks and having a "machine learning" project meant you had actual machines to move) to his current crusade: making sure superintelligence doesn't wreck the joint for the rest of us.

Kaplan lays out what everyone's too scared—or too clueless—to admit: if you wouldn't leave your wallet with a random LLM, why are you ready to entrust the future of humanity to black-box mega-brains? Spoiler: the answer isn't "more GPUs." Dr. Kaplan's been in the room with the legends, built systems Wall Street still wishes it could copy, and now he's here to torch lazy thinking about AI safety, collective intelligence, and why your Marcus Aurelius quotes aren't enough to save you from an existential AI oopsie.

What We Cover:

• The difference between "tool" AI and "worker" AI (yes, there's a difference—catch up).

• Why "superintelligence" doesn't need another buzzword conference, it needs democratic crowdsourcing (and a human in the loop so we don't all end up starring in a low-budget Skynet reboot).

• The messiness of teaching ethics to machines—and why handing off responsibility to Silicon Valley's overcaffeinated 20-somethings is, frankly, a terrible plan.

• The not-so-humble history of AI: mentoring with Nobel laureates, building for Wall Street, and knowing when the hype cycle is actually a warning sign.

Guest Bio:

Dr. Craig Kaplan—founder of superintelligence.com, patent-holding AI risk-mitigator, and straight-up legend in the AI world. He's been in the game since the 1980s (seriously, he worked with Herbert freakin' Simon), has built AI that beats Wall Street's "best," and still has the patience to explain to the rest of us why we should care before it's too late. Want to know what's coming next for AI? He's been calling it for decades.

Enjoy the episode. This show is brought to you by Wrench.ai.

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Craig:

LinkedIn: https://www.linkedin.com/in/craigakaplan/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• superintelligence.com (Craig's digital lair)

• Wall Street collective intelligence

• Jensen Wang's "AI is workers" GTC speech

People and Organizations Mentioned:

• Craig A. Kaplan

• Herbert Simon

• Jeff Hinton

• Marvin Minsky

• Anthropic and "the chosen 20 at Google"

• Nvidia

• Wall Street's unfortunately clueless quant crowd

Show Notes & Timestamps:00:04 — Dr. Kaplan invents "AI before it was cool" 06:15 — The limitations of everyone's favorite LLMs 17:50 — A sharp left turn into AI ethics and why Danbot needs therapy 31:00 — Why your future coworkers might be called "bots" (and outsmart you) 39:16 — The AI flywheel, the AGI endgame, and how to not get flattened 41:09 — How collective intelligence saved billions (and Dan's blood pressure)

"I was the daughter of a mechanic and a librarian—I know a thing or two about fixing things, building things, and making sense of way too much information." —Dr. Lisa Dieker

In This Episode: We talk to Dr. Lisa Dieker about why the future of learning isn't robots replacing teachers—it's humans and AI teaming up (with a little extra caffeine and a lot of biometric gadgets thrown in). As the Williamson Family Distinguished Professor at the University of Kansas and Director of the FLITE STEM Center, Lisa's on a mission to hack how we teach, learn, and support every kind of mind out there.

She takes us for a walk through her real-life MacGyver childhood, her family's journey navigating disability, and her relentless pursuit to democratize access to education technology. If you've ever wondered whether "second brains" (read: AI copilots, fancy wearables, and those heart rate monitors you pretend you understand) actually help kids learn, or just give parents more to stress about—yeah, she'll set you straight. Why are so many teachers burning out? Why can't schools just teach to everyone's strengths? And are spelling tests just baby boomer torture devices at this point?

What We Cover:

• How to blend AI, gritty human teaching, and biometric feedback to finally move the education world out of the floppy disk era.

• Why kids with learning differences (dyslexia, ADHD, neurodivergence—you name it) shouldn't have to hack their own school success.

• What today's "second brain" tools like AI copilots and wearables are actually good for (hint: not just tracking your steps).

• The future of classrooms: predictive dashboards, teacher biohacks, and why we should all be a little more forgiving with ourselves (and our kids).

• How Lisa's own story—first-gen college kid, sibling with disabilities, mom to one helluva creative gymnast—shapes everything she does.

Guest Bio:

Dr. Lisa Dieker is the Williamson Family Distinguished Professor of Special Education at the University of Kansas and heads up the FLITE STEM Center, where she's busy making education accessible, equitable, and just a little less stuck in the 1980s. Lifelong advocate for students with disabilities, simulation geek, and accidental expert in the hacking of biometric gadgets, Lisa's here to make you rethink everything you thought you knew about learning.

Follow Dan: LinkedIn: https://www.linkedin.com/in/danbaird/ X: https://x.com/mrdanbaird

Follow Lisa:

LinkedIn: https://www.linkedin.com/in/lisadieker/

Follow the Pod: YouTube: https://www.youtube.com/@burnthemappodcast Twitter/X: https://x.com/BurnTheMapPodInstagram: https://www.instagram.com/burnthemappodcast/ TikTok: https://www.tiktok.com/@burnthemappodcast BlueSky: https://bsky.app/profile/burnthemappodcast.bsky.social

Selected Links From This Episode:

• FLITE Center at University of Kansas (Flexible Learning Through Innovations in Teaching and Education)

• Project RAISE - https://www.ucpcfl.org/projectraise

• DeBruce Foundation – Agilities Workforce Curriculum

• Conmigo AI Tutoring (Affordable, AI-driven support tool for learners)

• Diffit for Teachers (AI-powered educational content platform mentioned as a resource for differentiated, individualized instruction)

• https://flite.ku.edu/ai-advocates-podcast

• https://specialedu.ku.edu/people/lisa-dieker

• https://aai.ku.edu/centers/flite

People and Organizations Mentioned in This Episode:

• The DeBruce Foundation (Agilities curriculum)

• Google Vision Team (referenced for their work in computer vision, mentioned in collaboration context)

• Meta (for metaverse glasses/hardware experiments)

• Polar (wearable biometric devices)

• Biopac (biometric ring for physiological data collection)

• University of Kansas (Lisa's academic affiliation)

• U.S. Department of Education (funding source for portions of Lisa's research)

Show Notes & Timestamps:

• 6:00 - Why your "second brain" might be a game changer if you're bored (or neurodiverse)

• 12:00 - The myth (and reality) of AI replacing teachers

• 22:00 - Biometric trackers: cool for athletes, secretly more useful for stressed-out teachers

• 35:00 - Why the real education revolution starts by hacking the system, not just the software

• 49:00 - Lisa's secret sauce for making learning accessible, plus why some spelling rules are made to be broken