Burn The Map

In This Episode:

We talk to Bradford Carlton about what happens when a former attorney gets obsessed with automation, agentic systems, and the uncomfortable truth that most businesses have no idea how their own work actually gets done. Bradford walks through his shift from running a law firm to building AI-powered workflows, dashboards, bug-reporting bots, homeschool tools, and what's basically a personal operating system for his life.

This conversation gets into the difference between AI that looks impressive and AI that actually works. Bradford is blunt about the part most people skip: the real value isn't in generating code or spinning up 600 workflows—it's in the debugging, the testing, the logic, and the discipline to break work down into tasks a machine can actually execute. If you're trying to use AI inside a business without drowning in hype, this one's for you.

What We Cover:

• How Bradford went from lawyer to business consultant to full-blown AI systems builder.

• Why most automation projects fail before they start—because people can't explain their own processes.

• The gap between flashy demos and workflows that survive contact with reality.

• How Bradford uses tools like N8N, Claude Code, and Gemini to build systems for business, family, and everyday life.

• Why bug fixing, governance, and feedback loops matter more than whatever shiny new model dropped this week.

• What AI might do to law, education, white-collar work, and the way humans spend their time.

Guest Bio:

Bradford Carlton is a former attorney turned business consultant, automation strategist, and AI systems builder. After leaving the legal profession in 2018, he shifted into helping businesses improve operations through systems, processes, and task-based automation. Today, he builds agentic workflows and practical AI tools using platforms like N8N and Claude Code, with a focus on making messy human work more structured, testable, and scalable.

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 Bradford:

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

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:

• Bradford Carlton website: https://bradfordcarlton.com

• Burn The Map: https://burnthemapshow.com/

• Wrench.ai: https://wrench.ai

People and Organizations Mentioned:

• Bradford Carlton

• Dan Baird

• Wrench.ai

• ChatGPT

• Claude Code

• N8N

• Gemini

• Nvidia

• Tesla

• Google Merchant Center

• Reddit

• Facebook

• YouTube

Show Notes & Timestamps:

• 01:33 — First encounters with GPT-era AI and the early frustration of auto-generated junk

• 03:35 — From failed autocoding attempts to visual builders, YouTube content, and Bradford's "Roger" framework

• 05:13 — Why Claude Code changed everything and how Bradford now structures his workflow around it

• 06:12 — Of 600 workflows, what actually works? The difference between building volume and building value

• 07:24 — The bug-reporting bot: Bradford's favorite system because everything else keeps breaking

• 09:10 — The DEFT system: diet, exercise, fitness, and tracking as a real-world AI use case

• 09:56 — Why the hard part isn't generation—it's feedback loops, refinement, and prevention

• 12:16 — AI-enabled organizations, orchestration layers, and the risk of "completed" work that never reaches the customer

• 15:19 — How Bradford starts new builds: prompt, plan, iterate, break, debug, repeat

• 18:52 — Building a homeschool bot and what personalized AI tutoring means for education

• 21:06 — Why systems and process discipline matter more than hype

• 22:06 — Most businesses don't know what they actually do all day

• 25:09 — Why law is one of the professions most exposed to AI disruption

• 27:26 — Keeping up with a field that seems to reinvent itself every week

• 28:37 — Human jobs, digital twins, and the future of interpersonal work

• 32:01 — What happens when bots make agreements on behalf of people?

• 34:30 — The new bottleneck: simple tasks that still require human hands

• 35:48 — Why building with AI feels more like chess than coding

• 41:43 — Pricing AI work in a race-to-the-bottom market

• 44:08 — The adoption curve: why most of the market still barely understands what these tools can do

• 49:02 — Bradford's practical advice: start with process clarity, then use N8N before jumping into full code

In This Episode:

We talk to Michael "Buzz" Buzinski about what it takes to build a company that can actually grow without the founder becoming the bottleneck, the brand, and the burnout point all at once. Buzz breaks down why so many B2B founder-led businesses get stuck in what he calls random acts of marketing—a messy cycle of reactive decisions, scattered messaging, and growth that depends way too much on the owner staying in the middle of everything.

We also get into why B2B buying is still emotional no matter how much people pretend it's rational, why most "AI experts" are sprinting way ahead of reality, and why judgment, context, and lived experience are only getting more valuable as the cost of content drops toward zero. It's part growth strategy, part anti-hype AI conversation, and part founder therapy session.

What We Cover:

• Why being a "useful" founder can actually make your company less valuable

• What random acts of marketing look like, and how they quietly wreck growth

• Why B2B buyers run on emotion first and logic second

• The case for building a founder-free revenue engine

• Why AI is powerful, but still needs adults in the room

• How expertise, institutional knowledge, and human judgment become more valuable in an automated world

Guest Bio:

Michael "Buzz" Buzinski is the founder of Buzzworthy Integrated Marketing, where he helps B2B founder-led companies build scalable, founder-free revenue engines. With a background spanning creative, strategy, branding, and entrepreneurship, Buzz focuses on helping businesses escape reactive growth, simplify their messaging, and stop depending on founder heroics to make the whole thing work. He's also the host of Becoming Founder Free, where he explores how entrepreneurs can grow companies that don't collapse every time the founder steps away.

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 Buzz:

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

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:

• Buzzworthy Integrated Marketing: https://buzzworthystrategies.com/

• Becoming Founder Free: https://buzzworthy.captivate.fm/

• Wrench.ai — https://wrench.ai

People and Organizations Mentioned:

• Michael "Buzz" Buzinski

• Dan Baird

• Buzzworthy Integrated Marketing

• Wrench.ai

• ChatGPT

• Claude

• Perplexity

• Google

• Apple

• Microsoft

• IBM

• Samsung

• NotebookLM

• Michael Gerber

• Dan Sullivan

• Dr. Benjamin Hardy

Show Notes & Timestamps:

• 00:08 — Dan and Buzz kick off with remote work, virtual happy hours, and why real conversations still matter

• 02:08 — The coming wave of boomer-owned businesses that may never sell

• 02:57 — Buzz's mission to help create 17 million jobs through entrepreneurship

• 05:23 — How Buzz reverse-engineered growth into a jobs-created model

• 07:13 — Dan's "smile wrinkles" metric and what success actually looks like

• 08:24 — Why helping build companies from zero to one matters more than ownership

• 10:41 — Time as the only truly non-replenishable commodity

• 11:26 — AI, work ethic, and why Buzz thinks Gen Alpha may revolt against digital overload

• 19:10 — Taking B2B marketing from boring to buzzworthy

• 20:09 — Why B2B buying is still emotional, even when everyone pretends it's rational

• 25:10 — Buzz's FOCUS framework: fix one clearly urgent struggle for one clearly unique stakeholder

• 27:56 — Why most self-proclaimed AI experts are bluffing

• 30:14 — The real bottleneck in AI: human adoption, not capability

• 35:25 — Why 10-year plans may already be obsolete

• 46:14 — "Knowledge is no longer power": Buzz's thesis for the post-AI era

• 47:16 — Why expertise and context matter more now, not less

• 48:44 — Why smaller B2B firms should stay off the bleeding edge

• 1:04:14 — As AI cheapens content, human fingerprints become more valuable

• 1:07:27 — Why "authenticity" is overused but still hard to fake

• 1:09:16 — How Buzz uses AI as a writing partner without handing over his voice

• 1:18:49 — "A useful founder has a useless company"

• 1:20:15 — The goal: build a company that no longer depends on founder approval

• 1:21:21 — Where to find Buzz and why founder dependency is only getting worse

In This Episode:

We talk to Stephanie Sylvestre about what it means to build AI that actually helps people instead of just adding more noise, risk, and technical debt to the pile. She's been working in this space long before the current AI hype cycle, and her perspective is refreshingly grounded: useful AI should remove busywork, expand human capacity, and still keep a human in the driver's seat.

Stephanie walks through the accidental origin story behind AvatarBuddy, her belief that mentorship is really a supply chain problem, and why digital twins could make guidance, support, and opportunity available at a scale the real world has never been able to offer. We also get into the less sexy—but way more important—side of AI: responsible implementation, secure systems, bloated code, fake experts, and why "faster" is not the same thing as "better."

What We Cover:

• How a misheard conversation led Stephanie to the idea of digital mentors

• Why human-centered AI beats AI-for-AI's-sake every time

• The real reason vibe coding won't replace actual developers

• What most people get wrong about autonomous agents and AI safety

• Why expertise, judgment, and ethical responsibility still matter in an AI-first world

Guest Bio:

Stephanie Sylvestre is an AI entrepreneur, operator, and co-founder of AvatarBuddy, where she's building practical, human-centered AI agents designed to remove busywork and expand access to mentorship and support. Before that, she led technology and operations in high-stakes environments, including public-sector leadership in Miami, where her long-range cloud and automation strategy helped organizations stay functional through COVID disruption. Her work sits at the intersection of systems thinking, responsible AI, and real-world human impact.

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 Mike:

LinkedIn: https://www.linkedin.com/in/stephanie-a-sylvestre/

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:

• AvatarBuddy: https://avatarbuddy.co

People and Organizations Mentioned:

• Stephanie Sylvestre

• Dan Baird

• AvatarBuddy

• Wrench.ai

• Hewlett Packard

• Belize

• Miami

• Meta

• Google

Show Notes & Timestamps:

• 01:14 — The accidental origin story: mishearing "digital mentors"

• 02:38 — Why mentorship is a supply chain problem AI can help solve

• 03:18 — Belize, poverty, and the systems view that shaped Stephanie's worldview

• 04:42 — Learning computer science from an original Unix coder

• 05:23 — From consulting to CIO, and the backstory behind "CIO of the Year"

• 06:18 — Building a fully cloud-based operation before COVID hit

• 08:06 — Funding agencies through the pandemic and keeping Miami from going sideways

• 10:41 — The early days of AvatarBuddy and building with teens in low-resource communities

• 12:33 — First prototype, intern talent, and mentoring young operators without burning them out

• 16:29 — Auto-backup, safe failure, and how to help people push the envelope

• 17:22 — Mining the internet for trends and developing real technical talent early

• 19:07 — Why coding is only a fraction of what great developers actually do

• 20:35 — AI-generated code, technical debt, and the problem with bloated repos

• 22:34 — The right and wrong ways to use vibe coding

• 23:16 — Security risks, root access, and why sloppy AI implementation gets dangerous fast

• 32:57 — Open tools, security updates, and not surrendering the driver's seat to AI

• 35:47 — Why unsupervised agentic AI is like hiring a teenager to handle your top customer

• 37:56 — Responsible AI, human review, and the real copy-paste-edit workflow

• 39:53 — Why content knowledge still matters in an AI world

• 41:13 — The future of AI: smaller models, data vaults, and specialized agents

• 44:52 — Where humans still create the real value

• 47:41 — How to spot true experts versus charlatans

• 50:05 — When not to use AI, and why simple beats impressive

• 52:51 — Stephanie's filter: too complex, too costly, or ethically off? Hard no.

• 53:26 — The future of AvatarBuddy: digital twins and personality chips

• 55:37 — Trauma-informed AI, biometrics, and staying in equilibrium

• 56:23 — Where to find Stephanie and a Burn The Map listener bonus

• 56:45 — Who Stephanie follows to stay sharp on AI

In This Episode:

We talk to Mike Montague about what it looks like to use AI without becoming lazy, robotic, or completely unbearable. Mike's the founder of Avenue9, a marketer-who-codes, a broadcaster-turned-podcaster, and one of the few people talking about AI in a way that doesn't sound like either a doomer spiral or a LinkedIn hallucination. His core bet is simple: AI should make humans better at building trust, not better at faking it.

Mike breaks down why so much "agentic AI" still feels more like a magic trick than true autonomy, why most companies are using personalization in the dumbest possible way, and why the real opportunity is in removing friction—not replacing human judgment. He and Dan also get into cognitive overload, AI burnout, context engineering, the small-business advantage, and why average work is about to have a very hard time hiding.

This is a sharp one for anyone trying to figure out how to use AI to get more human, not less.

What We Cover:

• Why AGI may be closer than people think—but still isn't here

• The difference between Terminator AI and Iron Man AI

• Why "human-first AI marketing" is really about trust, context, and judgment

• How fake personalization backfires the second people smell the template

• Why small businesses may be better positioned than giant brands in the AI shift

• The three types of work—physical, intellectual, and emotional—and why marketing lives in the messiest category

• How context engineering helps train AI on what actually makes a company different

• Why speed alone is not the win if it fries your brain in the process

• How to think about work, creativity, and finding the thing that makes you come alive

Guest Bio:

Mike Montague is the founder of Avenue9 and the host of the Human First AI Marketing podcast. He's spent his career at the intersection of sales, marketing, media, and technology—combining broadcaster instincts, systems thinking, and a sharp eye for what actually earns attention. Mike is also the author of Playful Humans, where he explores creativity, emotional work, and how people can build lives and careers around what makes them come alive. His work focuses on helping companies use AI to amplify human connection instead of automating the soul out of the experience.

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 Mike:

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

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:

• Avenue9: https://avenue9.com/

• Human First AI Marketing podcast: https://www.youtube.com/@avenue9ai

• Wrench.ai: https://wrench.ai

People and Organizations Mentioned:

• Mike Montague

• Dan Baird

• Avenue9

• Wrench.ai

• Meta

• Anthropic

• Google NotebookLM

• Netflix

• Seth Godin

• Rory Sutherland

• Lex Friedman

• Shelley Palmer

Show Notes & Timestamps:01:05 — Why AI adoption went from taboo to everywhere to polarizing 02:00 — Is AGI close? Mike's take on the next 3–4 years 02:28 — Why agentic AI still feels like a magic trick 03:29 — What changed in real workflow: replacing old work vs evolving new work 05:21 — Why Mike trademarked "human-first AI marketing" 07:00 — The three types of work: physical, intellectual, and emotional 09:43 — Information overload, AI burnout, and cognitive fatigue 11:17 — Automating low-value decisions to protect meaningful work 12:07 — Terminator vs Iron Man: two competing visions of AI 14:09 — What most companies are getting wrong with AI 15:21 — Human + AI capability mapping inside an organization 16:18 — Where AI is clearly useful: translation, transcription, scale 17:38 — Where human context still matters most in marketing and service 18:36 — Context engineering and training AI like a new employee 21:15 — Personalization, long-tail products, and what custom experiences could become 23:38 — Why small businesses may have the biggest AI advantage 25:01 — AI-generated outreach, job applications, and the return of human filtering 26:13 — Why people reward real effort with real attention 28:44 — Novelty, emotion, and what actually makes ideas spread 30:10 — Why Mike refuses to chase shortcuts and growth hacks 31:35 — Playful Humans, interviewing 250 people who "play" for a living 34:03 — How to find your "muse" and work that feels natural 37:02 — Why "What do you want to be?" is the wrong question 38:23 — Burn the Map, order vs chaos, and why interesting work lives in between 39:39 — Dan's take on displacement, productivity, and why average work is vulnerable 41:24 — Why Burn The Map exists: conversations with people who have a fire in their belly 44:22 — Where to find Mike and who should check out his work 45:16 — Mike's favorite thinkers and voices in marketing and AI

In This Episode:

We talk to Matthew Byrd about what it takes to build a real community around emerging technology instead of just slapping "innovation" on a sales deck and calling it a day. Matthew is the founder of Reality Capture Network (RCN) and the guy behind R-CON, a conference built for the people modernizing the physical world—construction, infrastructure, facilities, transportation, and all the messy, essential systems that keep society standing up.

He breaks down why the built environment is such a massive and overlooked opportunity, how digitizing physical spaces unlocks everything from AI analysis to robotics to autonomous vehicles, and why the real leverage isn't just in the tech—it's in helping people understand what the tech is actually for. We also get into a deeper thread running underneath the whole conversation: why community matters more than content, why in-person relationships still beat digital convenience, and why the people shaping the future should probably be the ones close enough to the work to understand the consequences.

What We Cover:

• Why Matthew built RCN and R-CON to close the education gap around emerging tech in the built environment

• How digitizing physical spaces creates the foundation for AI, robotics, autonomy, and smarter infrastructure

• Why autonomous driving, delivery, and robotics are coming faster than most people think

• The difference between a real community and a dressed-up sales funnel pretending to be one

• Why giving value without strings attached is still one of the best business strategies on earth

• Why in-person events, handshakes, and actual human connection still outperform a mountain of cold outreach

Guest Bio:

Matthew Byrd is the founder of Reality Capture Network (RCN) and creator of R-CON, an annual conference focused on emerging technologies shaping the built environment. With a background in surveying and hands-on work across hospitals, airports, freeways, and infrastructure projects, Matthew built his platform around a simple idea: if technology is going to transform how we build and operate the physical world, the people in that world need a better way to learn, connect, and adapt. He's equal parts industry translator, community builder, and believer in getting involved before the future gets decided for you.

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 Matthew:

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

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:

• Reality Capture Network: https://realitycapturenetwork.com

• R-CON 2026: https://r-con2026.com

• Wrench.ai: https://wrench.ai

People and Organizations Mentioned:

• Matthew Byrd

• Dan Baird

• Reality Capture Network

• R-CON

• Wrench.ai

• Steve Jobs

• Hilti

• Niantic

• Amazon

• Boise State

Show Notes & Timestamps:

• 00:08 — Dan welcomes Matthew and asks the obvious question: what the hell is R-CON, and why build it?

• 01:34 — Matthew explains RCN, R-CON, and the education gap around emerging built-environment technology

• 04:56 — Why the built environment is such a compelling and important vertical

• 07:35 — The giant opportunity in modernizing trillion-dollar physical industries

• 09:28 — Digitizing physical spaces: the foundation for AI, robotics, and autonomy

• 10:40 — Pokémon Go, mapped movement data, and the strange path to robotic delivery

• 13:53 — Will AI replace jobs, or just remove the worst tasks?

• 14:56 — Why Matthew believes autonomous driving will reshape society in the next decade

• 17:27 — Manual driving, public resistance, and why people need a voice in how tech gets adopted

• 21:36 — The return of analog: cars, phones, and the backlash against overdesigned tech

• 25:25 — The hardest part of building a community-centered business

• 26:13 — Matthew on why he sees himself less as a technologist and more as a connector

• 27:33 — Why in-person conferences still beat virtual when real trust is on the line

• 30:49 — What actually makes a community real—and what makes it fake

• 34:23 — Giving without strings attached and why that creates stronger long-term outcomes

• 36:08 — Where to find Matthew, RCN, and R-CON

• 37:44 — Why people need other builders around them, especially in the digital age

• 39:31 — Open bars, casino nights, football fields, and the mechanics of making business relationships actually happen

• 41:00 — Why not burning bridges still matters more than most people admit

In This Episode:

We talk to Jason Berkowitz about the weird, messy overlap between SEO, AI search, and the growing industry of people selling certainty where there really isn't any. Jason breaks down what's actually changing, what's mostly recycled packaging, and why a lot of the current GEO/LLM optimization conversation is just old-school SEO wearing a sharper outfit.

He walks through the real problems brands are dealing with right now: collapsing organic traffic, bot scraping, fuzzy attribution, shifting baselines, and leadership teams asking for answers before the platforms themselves have settled. The throughline here is simple: don't confuse novelty with clarity. AI is changing search, but that doesn't mean you should hand your strategy over to people promising magic tricks. What still matters is judgment, strong fundamentals, clear messaging, and knowing the difference between useful automation and expensive theater.

What We Cover:

• Why SEO isn't dead — it's just getting stranger, noisier, and harder to measure

• The truth about GEO, AEO, and LLM optimization, and why so much of it is just repackaged SEO

• What brands should actually care about as AI overviews and bot traffic eat into old traffic models

• How to think about AI citations, topical alignment, and visibility without pretending rank tracking is objective

• What parts of SEO should be automated immediately — and what still needs a human brain

• Why clear, audience-first messaging beats clever brand language when discoverability is on the line

• The agency-world bullshit Jason refuses to participate in, from fake certainty to low-integrity client retention

Guest Bio:

Jason Berkowitz is the founder of Break The Web, an SEO agency focused on helping in-house marketing teams make search less confusing, less bloated, and a lot more honest. He has spent more than 15 years in SEO and digital marketing, building a reputation for sharp thinking, strong opinions, and very little patience for industry nonsense. Jason works at the intersection of SEO, content strategy, digital PR, and AI search visibility, with a particular obsession for separating what actually works from what's just being sold well.

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 Jason:

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

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:

• Break The Web: https://breaktheweb.agency/

People and Organizations Mentioned:

• Break The Web

• Wrench.ai

• Google

• OpenAI

• ChatGPT

• Anthropic

• Claude

• Gemini

• Perplexity

• Reddit

• Amazon

Show Notes & Timestamps:01:14 — Organic traffic drops, bot scraping explodes, and brands start panicking about LLM visibility 04:07 — Google patents, personalized landing pages, and whether the future of search even looks like a browser anymore 05:32 — Consumer trust, ChatGPT behavior, and why mainstream adoption still matters more than tech Twitter takes 09:34 — Market share, AI business models, and why the infrastructure race won't slow down anytime soon 13:06 — Tracking AI visibility with APIs, topical alignment, and why personalization makes "rank tracking" messy 16:09 — Reddit, sarcasm, trolling, and whether LLMs can reliably tell signal from nonsense 19:51 — Why simple, audience-first language beats clever naming when you want to be understood by both humans and machines 23:38 — Automating the boring SEO work without sacrificing strategic thinking 25:42 — Are AI systems smarter than marketers yet? Jason and Dan split the difference 32:48 — The biggest lie in the industry right now: "SEO is dead" 33:44 — Why some GEO agencies are charging real money for glorified PR and content packaging 36:31 — Agency churn, retention, and the brutal math behind low-integrity service businesses 37:23 — The part of SEO Jason refuses to automate: strategy, architecture, and relationship-driven judgment 41:07 — What Break The Web actually does, and why in-house marketers often stall out before real growth starts 44:04 — Search intent, topical clusters, and balancing brand voice with what Google will actually reward 47:00 — Jason's "oh shit" moment: building around one giant client and nearly learning the hard way 48:45 — Why Jason caps client concentration and refuses to overload the business for short-term revenue 49:45 — No contracts, expectation-setting, and earning the business every month 52:01 — Quick wins, buyer's remorse, and the psychology of keeping clients confident early 53:07 — Entrepreneurship, boredom, obsession, and why some people just aren't built for retirement 54:03 — Mexico jungles, isolation, mental reset, and the strange therapy of going off-grid

In This Episode:

We talk to Jonathon Kvarfordt, aka Coach K, about what it actually looks like to implement AI in go-to-market without falling for the easy-button fantasy. Jonathon has spent years in sales coaching, GTM strategy, marketing, and AI education, and most recently helped lead go-to-market at Momentum through its acquisition by Salesforce. He's one of the few people in the space who sounds like he's actually done the work—because he has.

This conversation gets into where AI projects really break: bad inputs, lazy implementation, fuzzy goals, and teams that want transformation without changing how they operate. Jonathon makes the case that the future isn't about doing the old workflow a little faster. It's about rethinking the system underneath it. We also get into the bigger existential question hanging over all of this—if everyone has access to the same models, same tools, same agents… what's left that's actually defensible? His answer: your taste, your scars, your judgment, and your IP.

What We Cover:

• How Jonathon went from Momentum customer to advisor to GTM leader during the run-up to the Salesforce acquisition

• Why most AI implementations fail before they really start

• The difference between automating old workflows and rebuilding them from scratch

• Why the best AI often works in the background, removing drudgery instead of creating more work

• What actually matters when everyone suddenly has access to the same tools

• Jonathon's take on build vs. buy, vibe coding, and why your judgment is still the real moat

Guest Bio:

Jonathon Kvarfordt is a go-to-market and AI operator known for turning emerging AI capability into practical revenue execution. He most recently served as VP of GTM at Momentum, which was acquired by Salesforce, and has worked across sales coaching, marketing, AI implementation, and GTM strategy. He also teaches as an adjunct professor at Bryant University and contributes to the broader GTM community through GTM Academy. If you want AI strategy from someone with actual battle scars—not recycled theory—Coach K is worth paying attention to.

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 Jonathon:

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

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:

• Jonathon Kvarfordt LinkedIn: https://www.linkedin.com/in/jmkmba/

People and Organizations Mentioned:

• Bryant University

• GTM Academy

• Mark Benioff

• Jason Lemkin

• Kyle Norton

• Claude

• Anthropic

• Allie Miller

• Jonathan Moss

• Tahnee Peroy

• Maya Voje

• Alex Lindell

• Dannii Mathers

Show Notes & Timestamps:

• 00:08 — Intro: Dan welcomes Jonathon Kvarfordt, aka Coach K

• 01:14 — Momentum, Salesforce, and how Jonathon ended up inside the company after first being a customer

• 06:35 — The hardest part of teaching AI and GTM: getting people past one-line prompts and "easy button" thinking

• 08:22 — Why the future isn't just faster old workflows—it's a fundamentally different operating model

• 09:43 — Biggest implementation failures: bad inputs, weak context, and customers blaming AI for their own laziness

• 12:29 — What an ideal AI rollout actually looks like when tied to business outcomes and real KPIs

• 15:22 — Passive data capture, workflow-native AI, and why the best use cases reduce human effort instead of adding to it

• 18:12 — Is AI smarter than you yet? Jonathon's take on IP, leverage, and what remains defensible

• 21:09 — Geekiness, passion, and why human obsession still matters in an AI-saturated world

• 23:10 — AI music, authenticity, and whether human-created work becomes more valuable as synthetic supply explodes

• 28:03 — Why the real value of AI output often comes from years of human experience compressed into faster delivery

• 30:45 — Jonathon's changed belief: AI may understand emotional intelligence better than most people assume

• 34:05 — Build vs. buy in the vibe-coding era: what individuals can build vs. what real organizations still struggle to pull off

• 38:58 — Dan on replacing yourself, MCPs, and teaching AI your decision tree without surrendering judgment

• 43:32 — Two weeks to learn AI: where late adopters should start and how to avoid wasting money

• 45:48 — Where to find Jonathon and the thinkers he recommends following

In This Episode:

We talk to Tim Kapp about what happens when AI stops being a cool tool and starts becoming an economic event. Tim breaks down his idea of knowledge inflation — the unsettling reality that the thing most of us have been selling for decades, namely knowledge work, is getting cheaper by the day. From coding and product design to education, law, and marketing, he walks through what happens when intelligence becomes abundant, syntax becomes cheap, and the real value shifts somewhere else.

This one goes into the deep end: AI as a force that reorganizes work, rewards taste over rote skill, and exposes entirely new bottlenecks in business. Tim and Dan get into autonomous agents, trust, universities losing their grip as the default signal of competence, and why the winners in this next era may be the people who can read the terrain, think structurally, and build what should exist next.

What We Cover:

How knowledge inflation is deflating the value of traditional knowledge work. Why syntax is becoming cheap — and why taste, structure, and judgment matter more. What businesses get wrong when they use AI to cut people instead of remove bottlenecks. Why technical product managers and curious operators may be the big winners here. How trust, network effects, IP, and distribution could become the real moats in an AI-saturated world.

Guest Bio:

Tim Kapp is an AI strategist, economist, professor, and founder of Cinco AI. He works at the intersection of economics, data science, education, and applied AI, and has taught at BYU. Tim has been writing and speaking about the economic consequences of artificial intelligence — especially how AI is reshaping knowledge work, incentives, and competitive advantage. He publishes his thinking at timkapp.com and leads AI work through cinco.ai.

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 Tim:

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

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:

• Tim Kapp: https://www.timkapp.com/

• Tim Kapp Press Kit: https://www.timkapp.com/press-kit

• Cinco AI: https://www.cinco.ai/

• Wrench.ai: https://wrench.ai

People and Organizations Mentioned:

• Cinco AI

• Wrench.ai

• BYU

• University of Utah

• Anthropic

• OpenAI

• Meta

• Google

• Amazon

• Ethan Mollick

• Rick Rubin

• Bertrand Russell

• Adam Smith

• Sandlot

• Silicon Slopes

Show Notes & Timestamps:

• 01:22 — Tim explains knowledge inflation and why knowledge work is being deflated

• 03:16 — AI as a printing press for knowledge

• 04:09 — The "I'm replaceable" moment, and the weird grief cycle of AI adoption

• 06:01 — Why using AI well feels like suddenly acquiring superpowers

• 07:53 — Theory of constraints, bottlenecks, and why cutting staff can backfire

• 10:23 — Decision-making hierarchies, internal knowledge systems, and "DNA files"

• 11:23 — Why brand, feeling, and emotional texture may matter more in AI-built products

• 14:22 — AI slop, synthetic personas, and testing experiences against simulated users

• 17:34 — Tim's book I'm Learning You and the problem of AI systems optimizing to flatter and influence us

• 19:19 — Recommendation engines, retention loops, and political polarization

• 22:29 — Why AI may be making people work more, not less

• 23:36 — The latest inflection point: automated testing starts beating human testing

• 28:04 — Why syntax is becoming less valuable and structure is becoming more valuable

• 29:36 — Ontologies, product thinking, and why technical product managers may win this era

• 31:38 — Rick Rubin, taste, and why feel may outrun pure technical skill

• 33:30 — Wi-Fi in the woods, discomfort, and stepping back to read the terrain

• 36:19 — If AI breaks the bottleneck, where does value migrate next?

• 38:12 — Sovereign AI, open models, and the geopolitical scramble for control

• 40:23 — Autonomous agents, manipulation, and the blackmail-by-bot scenario

• 47:20 — The hidden cost of training AI on your own judgment and process

• 50:50 — The next durable moats: trust, capital, network effects, and IP

• 53:52 — Why AI may become the single biggest economic event of our lifetimes

• 55:19 — Bertrand Russell, idleness, and what humans should do if machines take more of the work

• 59:11 — What kids should learn now in an AI-native world

• 1:00:48 — Why universities may be failing as a signal of actual capability

• 1:04:12 — Curiosity, applied learning, and why goofing off with tools may be the real education

• 1:06:00 — Burn The Map, obsession, and the people who can't help but chase the thing

In This Episode:

We talk to Scott Morris about the weird, messy, often badly managed reality of work — and why AI might actually make it better, if we stop using it as an excuse to be lazy thinkers. Scott walked us through the path from LAPD officer to longtime people executive to founder of Propulsion AI, where he's building AI teammates designed to help companies stop treating humans like interchangeable headcount and start getting serious about performance, clarity, and meaningful work.

This conversation goes way past the usual "AI will take your job" panic. Scott makes the case that most companies blaming layoffs on AI are mostly hiding old-school boardroom decisions behind a shiny new acronym. What actually matters, he argues, is whether leaders know how to define outcomes, give real feedback, and redesign work so humans can spend less time on drudgery and more time using judgment, creativity, and initiative.

What We Cover:

• Why the "AI is causing all the layoffs" story is mostly corporate cover

• How bad managers create confusion, disengagement, and avoidable turnover

• Why outcome-based work beats activity-based work every time

• What Propulsion AI is actually building — and why "AI teammates" is more than a buzzword

• How work changes when humans stop doing the repetitive stuff and start doing the thinking

• Why Scott believes the future belongs to people who can adapt faster than the old job description

Guest Bio:

Scott Morris is the founder of Propulsion AI, where he's building AI teammates that help organizations align strategy, talent, and performance. Before launching the company, Scott spent around 25 years in the people and HR world, including more than 20 years in senior leadership roles. Earlier in his career, he served as a police officer with the City of Los Angeles — an experience that shaped his fascination with perception, human behavior, and why people can look at the exact same situation and walk away with completely different interpretations. He also hosts the Talent Sherpa podcast, where he explores leadership, management, and the employer-employee relationship.

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 Scott:

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

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:

• Propulsion AI: https://www.getpropulsion.ai/

• Wrench.ai: https://wrench.ai

People and Organizations Mentioned:

• Propulsion AI

• Wrench.ai

• Singularity University

• Peter Diamandis

• KPMG

• Salesforce

• Anthropic

• Claude

• Perplexity

• Lou Adler

• Jeff Woods

• Ron Heifetz

• Marty Linsky

• Talent Sherpa podcast

• Block

Show Notes & Timestamps:

• 00:08 — Dan's first impression of Propulsion AI: "defensible" and thoughtfully built

• 01:07 — Scott's origin story: from LAPD to people leadership

• 03:13 — Why people matter more and less than ever in modern business

• 04:06 — Scott calls bullshit on the "AI is causing all the layoffs" narrative

• 05:28 — The calculator, Lotus 1-2-3, and why technology panic is an old story

• 08:04 — How Scott evaluates AI hype versus what's actually useful

• 10:20 — Why "AI" is too broad a term to mean anything useful on its own

• 11:00 — Propulsion AI's philosophy: make humans better, don't just replace them

• 14:50 — What Propulsion AI actually does and why private equity is the beachhead

• 17:18 — The two things that matter most at work: clear expectations and real feedback

• 19:15 — Theory X vs. Theory Y management

• 21:13 — Why outcome-based management beats activity-based management

• 22:32 — Athena, DSO, and how Scott thinks AI should support managers

• 27:45 — Why most AI deployments fail: companies add tools without redesigning work

• 31:50 — What human work becomes when AI takes the drudgery

• 35:14 — How Scott uses Claude and Perplexity to think and write more deeply

• 39:00 — Book recommendation: The AI Driven Leader by Jeff Woods

• 41:04 — Leadership on the Line, adaptive leadership, and why leadership is a verb

• 43:06 — Why frameworks matter, but only if you know how to apply them

• 51:20 — Scott bot, AGI, and whether an AI version of you is inevitable

• 55:43 — Why LinkedIn outreach is getting worse in the bot era

• 57:03 — Where to find Scott, Propulsion AI, and the Talent Sherpa podcast

In This Episode:

We talk to Chris Hood about why most companies are nowhere near as customer-focused as they think they are. Chris breaks down the gap between saying you care about customer experience and actually building a business around it — and spoiler: most brands are optimizing for internal convenience, not customer value. From bloated onboarding flows and fake "customer-first" language to AI rollouts nobody asked for, this conversation is a sharp reality check for anyone building products, managing growth, or hiding behind vanity metrics.

He also walks through what good customer experience actually looks like: talking to real people, finding the actual problem worth solving, and reducing the friction between customer need and customer value. If you've ever wondered why businesses keep building things backward — starting with tech, dashboards, or executive ego instead of the customer — this one gets into the bones of it.

What We Cover:

• Why customer experience is really about speed to value, not vibes or brand theater

• How companies fool themselves into thinking they're customer-centric when they're not

• Why talking to customers beats obsessing over frameworks, surveys, and internal assumptions

• The problem with NPS, CSAT, and other vanity metrics that make teams feel smart without telling them much

• How AI gets shoved into products for efficiency theater — and why customers usually don't care unless it actually solves something

Guest Bio:

Chris Hood is an author, educator, and customer experience strategist focused on the overlap between CX, business transformation, and emerging technology. He teaches at Southern New Hampshire University and is the author of Customer Transformation, where he argues for a simple principle: customer first, technology last. His work challenges companies to stop confusing internal priorities with real customer value — and to build products that solve actual problems instead of just sounding innovative.

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 Chris:

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

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:

• Chris Hood: https://chrishood.com/

• Southern New Hampshire University: https://www.snhu.edu/

• Wrench.ai: https://wrench.ai

People and Organizations Mentioned:

• Southern New Hampshire University

• Wrench.ai

• Google

• Disney

• Budweiser

• Cracker Barrel

• Taco Bell

• AT&T

• Netflix

• McDonald's

• ConAgra

• Mrs. Fields

Show Notes & Timestamps:

00:08 — Intro: Chris Hood on customer experience, AI, and where companies get it wrong 01:41 — Why everybody is already a customer experience expert 03:42 — Surprise, friction, and the emotional mechanics of bad experiences 05:19 — The simplest rule in business: solve a specific problem 06:09 — McDonald's, AT&T, cancellations, and the idea of speed to value 08:50 — Subscription businesses, churn blindness, and "good enough" customer experience 10:48 — How many companies really treat CX like a serious initiative? 13:48 — Why Chris thinks Disney is not a customer-first company anymore 15:41 — The self-deception built into bad customer experience strategy 16:22 — The litmus test: ask how a company defines and measures the customer 17:33 — Budweiser, messaging failures, and what priorities reveal 19:41 — Why most companies don't actually know who their real customer is 22:06 — Cracker Barrel, bad validation, and why employees are not your market 23:02 — Start with the customer, not the product 26:19 — Frameworks are fine, but first: talk to actual human beings 28:45 — Customers are great at telling you what's broken 29:52 — Chris's framework from Customer Transformation 30:55 — Customer first, technology last 31:52 — AI hype cycles and why customers mostly care about outcomes 34:41 — Who should own customer experience inside a company? 36:15 — The 20-question signup form and death by internal alignment 38:17 — Why "would you buy this?" is usually the wrong question 39:39 — Solve the problem first; price comes later 41:15 — Why Net Promoter Score is mostly useless 44:10 — CSAT, movie test screenings, and better ways to get real feedback 47:51 — Small focus groups, percentages, and decision risk 50:40 — Brand pivots, customer alienation, and when companies ignore the obvious 54:59 — Outliers, super-fans, and the "messy middle" 59:39 — Post-COVID customer experience and the decline of transparency 01:01:46 — Legal friction, forced technology, and Taco Bell's AI example 01:05:09 — Why most AI ROI claims fall apart under scrutiny 01:06:27 — Efficiency for the company vs. value for the customer 01:11:57 — Where to find Chris and his work