Welcome back to Snafu with Robin Zander.

In this episode, I’m joined by Miki Johnson – coach, facilitator, and co-founder of Job Portraits, a creative studio that helped companies tell honest stories about their work and culture.

Today, Miki leads Leading By Example, where she supports leaders and teams through moments of change – whether that’s a career shift, new parenthood, or redefining purpose. We talk about how to navigate transition with awareness, why enjoying change takes practice, and what it means to lead with authenticity in uncertain times.

Miki shares lessons from a decade of coaching and storytelling – from building human-centered workplaces to bringing more body and emotion into leadership. We also explore creativity in the age of AI, and how technology can either deepen or disconnect us from what makes us human.

And if you’re interested in these kinds of conversations, we’ll be diving even deeper into the intersection of leadership, creativity, and AI at Responsive Conference 2026.

If you’re interested, get your tickets here! https://www.responsiveconference.com/

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00:00 Start 01:20 Miki's Background and Reservations about AI

Miki hasn’t used AI and has “very serious reservations.”

She’s not anti-AI – just cautious and curious.
Her mindset is about “holding paradox”, believing two opposing things can both be true.

Her background shapes that approach.

She started as a journalist, later ran her own businesses, and now works as a leadership coach.
Early in her career, she watched digital technology upend media and photography – industries “blown apart” by change.

When she joined a 2008 startup building editable websites for photographers, it was exciting but also unsettling.
She saw innovation create progress and loss at the same time.

Now in her 40s with two sons, her focus has shifted.

She worries less about the tools and more about what they do to people’s attention, empathy, and connection – and even democracy.
Her concern is how to raise kids and stay human in a distracted world.

Robin shares her concerns but takes a different approach.

He notes that change now happens “day to day,” not decade to decade.
He looks at technology through systems, questioning whether pre-internet institutions can survive.

“Maybe the Constitution was revolutionary,” he says, “but it’s out of date for the world we live in.”

He calls himself a “relentless optimist,” believing in democracy and adaptability, but aware both could fail without reform.

Both worry deeply about what technology is doing to kids.

Robin cites The Anxious Generation by Jonathan Haidt and says, “I don’t believe social media is good for children.”
He and his fiancée plan to limit their kids’ screen time, just as Miki already does.

They see it as a responsibility: raising grounded kids in a digital world.

Robin sees AI as even more transformative – and risky – than anything before.

“If social media is bigger than the printing press,” he says, “AI is bigger than the wheel.”
He’s amazed by its potential but uneasy about who controls it.

He doubts people like Sam Altman act in the public’s best interest.
His concern isn’t about rejecting AI but about questioning who holds power over it.

Their difference lies in how they handle uncertainty.

Miki’s instinct is restraint and reflection – question first, act later, protect empathy and connection.
Robin’s instinct is engagement with vigilance – learn, adapt, and reform systems rather than retreat.

Miki focuses on the human and emotional.
Robin focuses on the structural and systemic.

Both agree technology is moving faster than people can process or regulate.

Miki uses curiosity to slow down and stay human.
Robin uses curiosity to move forward and adapt.

Together, they represent two sides of the same challenge: protecting what’s most human while building what’s next.

10:05 Navigating the Tech Landscape

Miki starts by describing how her perspective has been shaped by living in two very different worlds.

She spent over a decade in the Bay Area, surrounded by tech and startups.
She later moved back to her small hometown of Athens, Ohio—a progressive college town surrounded by more rural areas.

She calls it “a very small Austin”, a blue dot in a red state.
She loves it there and feels lucky to have returned home.

Robin interrupts briefly to highlight her background.

He reminds listeners that Miki and her husband, Jackson, co-founded an employer branding agency called Job Portraits in 2014, the same year they got married.
Over eight years, they grew it to around 15 full-time employees and 20 steady contractors.

They worked with major startups like DoorDash, Instacart, and Eventbrite when those companies were still small—under 200 employees.
Before that, they had started another venture in Chicago during Uber’s early expansion beyond San Francisco.

Their co-working space was right next to Uber’s local team setting up drivers, giving them a front-row seat to the tech boom.

Robin points out that Miki isn’t coming at this topic as a “layperson.”

She deeply understands technology, startups, and how they affect people.

Miki continues, explaining how that background informs how she sees AI adoption today.

Her Bay Area friends are all-in on AI.

Many have used it since its earliest days—because it’s part of their jobs, or because they’re building it themselves.
Others are executives leading companies developing AI tools.

She’s been watching it unfold closely for years, even if she hasn’t used it herself.
From her position outside the tech bubble now, she can see two clear camps:

Those immersed in AI, excited and moving fast.
And those outside that world—more cautious, questioning what it means for real people and communities.

Living between those worlds—the fast-paced tech culture and her slower, more grounded hometown—gives her a unique vantage point.

She’s connected enough to understand the innovation but distant enough to see its costs and consequences.

16:39 The Cost of AI Adoption

Miki points out how strange it feels to people in tech that she hasn’t used AI.

In her Bay Area circles, the idea is almost unthinkable.
Miki understands why it’s shocking.

It’s mostly circumstance—her coaching work doesn’t require AI.
Unlike consultants who “all tell leaders how to use AI,” her work is based on real conversations, not digital tools.
Her husband, Jackson, also works at a “zero-technology” K–12 school he helped create, so they both exist in rare, tech-free spaces.

She admits that’s partly luck, not moral superiority, just “tiny pockets of the economy” where avoiding AI is still possible.

Robin responds with his own story about adopting new tools.

He recalls running Robin’s Café from 2016 to 2019, when most restaurants still used paper timesheets.

He connected with two young founders who digitized timesheets, turning a simple idea into a company that later sold to a global conglomerate.
By the time he sold his café, those founders had retired in their 20s.
“I could still run a restaurant on paper,” he says, “but why would I, if digital is faster and easier?”

He draws a parallel between tools over time—handwriting, typing, dictation.

Each serves a purpose, but he still thinks best when writing by hand, then typing, then dictating.
The point: progress adds options, not replacements.

Miki distills his point: if a tool makes life easier, why not use it?

Robin agrees, and uses his own writing practice as an example.

He writes a 1,000-word weekly newsletter called Snafu.

Every word is his, but he uses AI as an editor—to polish, not to create.
He says, “I like how I think more clearly when I write regularly.”

For him, writing is both communication and cognition—AI just helps him iterate faster.

It’s like having an instant editor instead of waiting a week for human feedback.
He reminds his AI tools, “Don’t write for me. Just help me think and improve.”

When Miki asks why he’s never had an editor, he explains that he has—but editors are expensive and slow.

AI gives quick, affordable feedback when a human editor isn’t available.

Miki listens and reflects on the trade-offs.

“These are the cost-benefit decisions we all make,” she says—small, constant choices about convenience and control.
What unsettles her is how fast AI pushes that balance.

She sees it as part of a long arc—from the printing press to now—but AI feels like an acceleration.
It’s “such a powerful technology moving so fast” that it’s blowing the cover off how society adapts to change.

Robin agrees: “It’s just the latest version of the same story, since writing on cave walls.”

20:10 The Future of Human-AI Relationships

Miki talks about the logical traps we’ve all started accepting over time.

One of the biggest, she says, is believing that if something is cheaper, faster, or easier – it’s automatically better.
She pushes further: just because something is more efficient doesn’t mean it’s better than work.
There are things you gain from working with humans that no machine can replicate, no matter how cheap or convenient it becomes.
But we rarely stop to consider the real cost of trading that away.

Miki says the reason we overlook those costs is capitalism.

She’s quick to clarify – she’s not one of those people calling late-stage capitalism pure evil.
Robin chimes in: “It’s the best of a bunch of bad systems.”
Miki agrees, but says capitalism still pushes a dangerous idea:

It wants humans to behave like machines—predictable, tireless, cheap, and mistake-free.

And over time, people have adapted to that pressure, becoming more mechanical just to survive within it.
Now we’ve created a tool—AI—that might actually embody those machine-like ideals.

Whether or not it reaches full human equivalence, it’s close enough to expose something uncomfortable:

We’ve built a human substitute that eliminates everything messy, emotional, and unpredictable about being human.

Robin takes it a step further, saying half-jokingly that if humanity lasts long enough, our grandchildren might date robots.

“Two generations from now,” he says, “is it socially acceptable—maybe even expected—that people have robot spouses?”

He points out it’s already starting—people are forming attachments to ChatGPT and similar AIs.

Miki agrees, noting that it’s already common for people under 25 to say they’ve had meaningful interactions with AI companions.

Over 20% of them, she estimates, have already experienced this.
That number will only grow.

And yet, she says, we talk about these changes as if they’re inevitable—like we don’t have a choice.

That’s what frustrates her most:

The narrative that AI “has to” take over—that it’s unstoppable and universal—isn’t natural evolution.
It’s a story deliberately crafted by those who build and profit from it.
“Jackson’s been reading the Hacker News comments for 15 years,” she adds, hinting at how deep and intentional those narratives run in the tech world.

She pauses to explain what Hacker News is for anyone unfamiliar.
It’s one of the few online forums that’s still thoughtful and well-curated.

Miki says most people there are the ones who’ve been running and shaping the tech world for years—engineers, founders, product leaders.

And if you’ve followed those conversations, she says, it’s obvious that the people developing AI knew there would be pushback.

“Because when you really stop and think about it,” she says, “it’s kind of gross.”

The technology is designed to replace humans—and eventually, to replace their jobs.
And yet, almost no one is seriously talking about what happens when that becomes real.

“I’m sorry,” she says, “but there’s just something in me that says—dating a robot is bad for humanity. What is wrong with us?”

Robin agrees.

“I don’t disagree,” he says. “It’s just… different from human.”

Miki admits she wrestles with that tension.

“Every part of me says, don’t call it bad or wrong—we have to make space for difference.”

But still, something in her can’t shake the feeling that this isn’t progress—it’s disconnection.

Robin expands on that thought, saying he’s not particularly religious, but he does see humanity as sacred.

“There’s something fundamental about the human soul,” he says.
He gives examples: he has metal in his ankle from an old injury; some of his family members are alive only because of medical devices.

Technology, in that sense, can extend or support human life.
But the idea of replacing or merging humans with machines—of being subsumed by them—feels wrong.

“It’s not a world I want to live in,” he says plainly.

He adds that maybe future generations will think differently.

“Maybe our grandkids will look at us and say, ‘Okay boomer—you never used AI.’”

24:14 Practical Applications of AI in Daily Life

Robin shares a story about a house he and his fiancée almost bought—one that had a redwood tree cut down just 10 feet from the foundation.

The garage foundation was cracked, the chimney tilted—it was clear something was wrong.
He’d already talked to arborists and contractors, but none could give a clear answer.
So he turned to ChatGPT’s Deep Research—a premium feature that allows for in-depth, multi-source research across the web.

He paid $200 a month for unlimited access.
Ran 15 deep research queries simultaneously.
Generated about 250 pages of analysis on redwood tree roots and their long-term impact on foundations.

He learned that if the roots are alive, they can keep growing and push the soil upward.
If they’re dead, they decompose, absorb and release water seasonally, and cause the soil to expand and contract.
Over time, that movement creates air pockets under the house—tiny voids that could collapse during an earthquake.

None of this, Robin says, came from any contractor, realtor, or arborist.

“Even they said I’d have to dig out the roots to know for sure,” he recalls.

Ultimately, they decided not to buy that house—entirely because of the data he got from ChatGPT.
“To protect myself,” he says, “I want to use the tools I have.”

He compares it to using a laser level before buying a home in earthquake country: “If I’ll use that, why not use AI to explore what I don’t know?”
He even compares Deep Research to flipping through Encyclopedia Britannica as a kid—hours spent reading about dinosaurs “for no reason other than curiosity.”

Robin continues, saying it’s not that AI will replace humans—it’s that people who use AI will replace those who don’t.

He references economist Tyler Cowen’s Average Is Over (2012), which described how chess evolved in the early 2000s.

Back then, computers couldn’t beat elite players on their own—but a human + computer team could beat both humans and machines alone.
“The best chess today,” Robin says, “is played by a human and computer together.”

“There are a dozen directions I could go from there,” Miki says.

But one idea stands out to her:

We’re going to have to choose, more and more often, between knowledge and relationships.

What Robin did—turning to Deep Research—was choosing knowledge.

Getting the right answer.
Having more information.
Making the smarter decision.
But that comes at the cost of human connection.

“I’m willing to bet,” she says, “that all the information you found came from humans originally.”

Meaning: there were people who could have told him that—just not in that format.

Her broader point: the more we optimize for efficiency and knowledge, the less we may rely on each other.

32:26 Choosing Relationships Over AI

Robin points out that everything he learned from ChatGPT originally came from people.

Miki agrees, but says her work is really about getting comfortable with uncertainty.

She helps people build a relationship with the unknown instead of trying to control it.
She mentions Robin’s recent talk with author Simone Stolzoff, who’s writing How to Not Know—a book she can’t wait to read.

She connects it to a bigger idea: how deeply we’ve inherited the Enlightenment mindset.

“We’re living at the height of ‘I think, therefore I am,’” she says.
If that’s your worldview, then of course AI feels natural. It fits the logic that more data and more knowledge are always better.

But she’s uneasy about what that mindset costs us.

She worries about what’s happening to human connection.

“It’s all connected,” she says—our isolation, mental health struggles, political polarization, even how we treat the planet.

Every time we choose AI over another person, she sees it as part of that drift away from relationship.

“I get why people use it,” she adds. “Capitalism doesn’t leave most people much of a choice.”

Still, she says, “Each time we pick AI over a human, that’s a decision about the kind of world we’re creating.”
Her choice is simple: “I’m choosing relationships.”

Robin gently pushes back.

“I think that’s a false dichotomy,” he says.

He just hosted Responsive Conference—250 people gathered for human connection.

“That’s why I do this podcast,” he adds. “To sit down with people and talk, deeply.”

He gives a personal example.

When he bought his home, he spoke with hundreds of people—plumbers, electricians, roofers.

“I’m the biggest advocate for human conversations,” he says.
“So why not both? Why not use AI and connect with people?”

To him, the real question is about how we use technology consciously.

“If we stopped using AI because it’s not human,” he asks,
“should we stop using computers because handwriting is more authentic?”
“Should we reject the printing press because it’s not handwritten?”

He’s not advocating blind use—he’s asking for mindful coexistence.
It’s also personal for him.

His company relies on AI tools—from Adobe to video production.

“AI is baked into everything we do,” he says.

And he and his fiancée—a data scientist—often talk about what that means for their future family.

“How do we raise kids in a world where screens and AI are everywhere?”

Then he asks her directly: “What do you tell your clients? Treat me like one—how do you help people navigate this tension?”

Miki smiles and shakes her head.

“I don’t tell people what to do,” she says. “I’m not an advisor, I’m a coach.”

Her work is about helping people trust their own intuition.
“Even when what they believe is contrarian,” she adds.

She admits she’s still learning herself.

“My whole stance is: I don’t know. I don’t know. I don’t know.”

She and her husband, Jackson, live by the idea of strong opinions, loosely held.

She stays open—lets new conversations change her mind.

“And they do,” she says. “Every talk like this shifts me a little.”

She keeps seeking those exchanges—with parents, tech workers, friends—because everyone’s trying to figure out the same thing:

How do we live well with technology, without losing what makes us human?

37:16 The Amish Approach to Technology

Miki reflects on how engineers are both building and being replaced by AI.

She wants to understand the technology from every angle—how it works, how it affects people, and what choices it leaves us with.

What worries her is the sense of inevitability around AI—especially in places like the Bay Area.
“It’s like no one’s even met someone who doesn’t use it,” she says.

She knows it’s embedded everywhere—Google searches, chatbots, everything online.
But she doesn’t use AI tools directly or build with them herself.

“I don’t even know the right terminology,” she admits with a laugh.

Robin points out that every Google search now uses an LLM.

Miki nods, saying her point isn’t denial—it’s about choice.

“You can make different decisions,” she says.

She admits she hasn’t studied it deeply but brings up an analogy that helps her think about tech differently: the Amish.
“I call myself kind of ‘AI Amish,’” she jokes.

She explains her understanding of how the Amish handle new technology.

They’re not anti-tech; they’re selective.

They test and evaluate new tools to see if they align with their community’s values.

“They ask, does it build connection or not?”

They don’t just reject things—they integrate what fits.

In her area of Ohio, she’s seen Amish people now using electric bikes.

“That’s new since I was a kid,” she says.

It helps them connect more with each other without harming the environment.

They’ve also used solar power for years.

It lets them stay energy independent without relying on outside systems that clash with their values.

Robin agrees—it’s thoughtful, not oppositional.

“They’re intentional about what strengthens community,” he says.
Miki continues:

What frustrates her is how AI’s creators have spent the last decade building a narrative of inevitability.

“They knew there would be resistance,” she says, “so they started saying, ‘It’s just going to happen. Your jobs won’t be taken by AI—they’ll be taken by people who use it better than you.’”

She finds that manipulative and misleading.

Robin pushes back gently.

“That’s partly true—but only for now,” he says.

He compares it to Uber and Lyft: at first, new jobs seemed to appear, but eventually drivers started being replaced by self-driving cars.

Miki agrees.

“Exactly. First it’s people using AI, then it’s AI replacing people,” she says.

What disturbs her most is the blind trust people put in companies driven by profit.

“They’ve proven over and over that’s their motive,” she says.
“Why believe their story about what’s coming next?”

She’s empathetic, though—she knows why people don’t push back.

“We’re stressed, broke, exhausted,” she says.
“Our nervous systems are fried 24/7—especially under this administration.”

“It’s hard to think critically when you’re just trying to survive.”

And when everyone around you uses AI, it starts to feel mandatory.

“People tell me, ‘Yeah, I know it’s a problem—but I have to. Otherwise I’ll lose my job.’”
“Or, ‘I’d have bought the wrong house if I didn’t use it.’”
That “I have to” mindset, she says, is what scares her most.

Robin relates with his own example.

“That’s how I felt with TikTok,” he says.

He got hooked early on, staying up until 3 a.m. scrolling.
After a few weeks, he deleted the app and never went back.

“I probably lose some business by not being there,” he admits.
“But I’d rather protect my focus and my sanity.”

He admits he couldn’t find a way to stay on the platform without it consuming him.

“I wasn’t able to build a system that removed me from that platform while still using that platform.”

But he feels differently about other tools.

For example, LinkedIn has been essential—especially for communicating with Responsive Conference attendees.

“It was our primary method of communication for 2025,” he says.

So he tries to choose “the lesser of two evils.”

“TikTok’s bad for my brain,” he says. “I’m not using it.”
“But with LLMs, it’s different.”

When researching houses, he didn’t feel forced into using them to “keep up.”

To him, they’re just another resource.

“If encyclopedias are available, use them. If Wikipedia’s available, use both. And if LLMs can help, use all three.”

41:45 The Pressure to Conform to Technology

Miki challenges that logic.

“When was the last time you opened an encyclopedia?”
Robin pauses. “Seven years ago.”
Miki laughs. “Exactly. It’s a nice idea that we’ll use all the tools—but humans don’t actually do that.”

We gravitate toward what’s easiest.

“If you check eBay, there are hundreds of encyclopedia sets for sale,” she says. “No one’s using them.”

Robin agrees but takes the idea in a new direction.

“Sure—but just because something’s easy doesn’t mean it’s good,” he says.

He compares it to food:

“It’s easier to eat at McDonald’s than cook at home,” he says.
But easy choices often lead to long-term problems.

He mentions obesity in the U.S. as a cautionary parallel.

Some things are valuable because they’re hard.

“Getting in my cold plunge every morning isn’t easy,” he says. “That’s why I do it.”
“Exercise never gets easy either—but that’s the point.”

He adds a personal note:

“I grew up in the mountains. I love being at elevation, off-grid, away from electricity.”
He could bring Starlink when he travels, but he chooses not to.

Still, he’s not trying to live as a total hermit.
“I don’t want to live 12 months a year at 10,000 feet with a wood stove and no one around.”
“There’s a balance.”

Miki nods, “I think this is where we need to start separating what we can handle versus what kids can.”

“We’re privileged adults with fully formed brains,” she points out.
“But it’s different for children growing up inside this system.”

Robin agrees and shifts the focus.

Even though you don’t give advice professionally,” he says, “I’ll ask you to give it personally.”

“You’re raising kids in what might be the hardest time we’ve ever seen. What are you actually practicing at home?”

45:30 Raising Children in a Tech-Driven World

Robin reflects on how education has shifted since their grandparents’ time

Mentions “Alpha Schools” — where

AI helps kids learn basic skills fast (reading, writing, math)
Human coaches spend the rest of the time building life skills

Says this model makes sense:

Memorizing times tables isn’t useful anymore
He only learned to love math because his dad taught him algebra personally — acted like a coach

Asks Miki what she thinks about AI and kids — and what advice she’d give him as a future parent

Miki’s first response — humility and boundaries

“First off, I never want to give parents advice.”

Everyone’s doing their best with limited info and energy

Her kids are still young — not yet at the “phone or social media” stage

So she doesn’t pretend to have all the answers

Her personal wish vs. what’s realistic

Ideal world:

She wishes there were a global law banning kids from using AI or social media until age 18
Thinks it would genuinely be better for humanity
References The Anxious Generation

Says there’s growing causal evidence, not just correlation, linking social media to mental health issues
Mentions its impact on children’s nervous systems and worldview

It wires them for defense rather than discovery

Real world:

One parent can’t fight this alone — it’s a collective action problem
You need communities of parents who agree on shared rules

Example: schools that commit to being zero-technology zones
Parents and kids agree on:

What ages tech is allowed
Time limits
Common standards

Practical ideas they’re exploring

Families turning back to landlines

Miki says they got one recently

Not an actual landline — they use a SIM adapter and an old rotary phone
Kids use it to call grandparents

Her partner Jackson is working on a bigger vision:
Building a city around a school

Goal: design entire communities that share thoughtful tech boundaries

Robin relates it to his own childhood

Points out the same collective issue — “my nephews are preteens”

It’s one thing for parents to limit screen time
But if every other kid has access, that limit won’t hold

Shares his own experience:

No TV or video games growing up
So he just went to neighbors’ houses to play — human nature finds a way

Says individual family decisions don’t solve the broader problem

Miki agrees — and expands the concern

Says the real issue is what kids aren’t learning

Their generation had “practice time” in real-world social interactions

Learned what jokes land and which ones hurt
Learned how to disagree, apologize, or flirt respectfully
Learned by trial and error — through millions of small moments

With social media and AI replacing those interactions:

Kids lose those chances entirely
Results she’s seeing:

More kids isolating themselves
Many afraid to take social or emotional risks
Fewer kids dating or engaging in real-life relationships

Analogy — why AI can stunt development

“Using AI to write essays,” she says,

“is like taking a forklift to the gym.”
Sure, you lift more weight — but you’re not getting stronger

Warns this is already visible in workplaces:
Companies laying off junior engineers
AI handles the entry-level work

But in 5 years, there’ll be no trained juniors left to replace seniors

Concludes that where AI goes next “is anybody’s guess” — but it must be used with intention

54:12 Where to Find Miki

Invites others to connect

Mentions her website: leadingbyexample.life
Visitors can book 30-minute conversations directly on her calendar

Says she’s genuinely open to discussing this topic with anyone interested

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