Will GEO replace SEO? (Spoiler alert: Probably!) We dig into how generative engines are reshaping discovery, why executives are already making decisions from AI answers, and what brands should do now to show up accurately and credibly in AI results.

In this episode of AI-Curious, we sit down with Curtis Sparrer, co-founder and principal at Bospar PR (and president of the San Francisco Press Club). Curtis has been experimenting across models, building a GEO toolkit (“Audit-E”), and advising companies on how to fix AI-age brand visibility—especially when models get facts wrong or elevate low-quality sources.

What we cover

• GEO vs. AEO vs. classic SEO—clear definitions and where each matters
• How AI engines weigh sources (and why third-party, reputable coverage now carries outsized influence)
• The “AI content gold rush”: press releases, FAQs, and AI-first site architecture (schemas, structured info)
• Case study: correcting a widely propagated falsehood about a client (“not dead yet”) and the steps that worked
• Practical GEO hygiene: what to keep from the SEO playbook; what to adapt for AI reasoning
• Pitching in the AI era: why templated, “robotic” outreach backfires and how to use AI for ideation and structure, not the final draft
• Winners & losers: PR-skeptics vs. teams that proactively feed reputable signals to models
• Near-term predictions: from “AI ethics” to emerging AI manners—what will be considered rude or acceptable AI use in comms

Guest

Curtis Sparrer — Co-founder & Principal, Bospar PR; President, San Francisco Press Club.

Bospar:

https://bospar.com/

Forbes coverage of Audit-E launch

https://www.forbes.com/sites/digital-assets/2025/09/25/whats-in-your-search-why-generative-ai-is-the-new-front-door/

If you’re new here, subscribe on Apple, Spotify, or YouTube, drop a five-star rating, and share with a friend who’s wrestling with search-to-answer disruption.

What happens when “space robots” stop being sci-fi set dressing and start punching a clock? We dig into a new breed of microgravity robots that do the unglamorous work—so astronauts can do more science.

In this episode of AI-Curious, we talk with Ethan Barajas (CEO) and Jamie Palmer (CTO), co-founders of Icarus Robots, fresh out of stealth with a $6M raise. Their pitch is simple and radical: put agile, teleoperated robots insidespacecraft like the ISS to handle cargo, inspections, and maintenance—then use the resulting microgravity manipulation data to unlock partial (and eventually full) autonomy. We cover the tech, the economics (why astronaut time is so expensive), the AI roadmap, and a pragmatic path from today’s chores to tomorrow’s orbital factories and lunar bases.

What we cover

• Why astronaut hours are precious—and how robots can “augment” rather than replace them
• The form factor: free-flying, drone-like bodies with dual arms optimized for zero-G dexterity
• Inside first, outside later: a deployment strategy that lowers safety hurdles and accelerates learning
• Data advantage: building the first large microgravity manipulation dataset via continuous teleop
• AI’s role: from human-in-the-loop control to primitives to scalable dexterous manipulation
• Communications and latency: S-band today, laser links tomorrow; what “real-time” actually means
• The “orbital factory” thesis: pharma, semiconductors, fiber optics—and servicing orbital data centers
• Long-horizon forecasts: humans living and working in space; physical labor increasingly done by robots

Guests

• Ethan Barajas — Co-founder & CEO, Icarus Robots
• Jamie Palmer — Co-founder & CTO, Icarus Robots

Why this matters

If half of Earth’s GDP is labor, the space economy scales only when on-orbit labor scales. Teleoperated robots that learn from expert demonstrations—then graduate to safe autonomy—are a credible bridge from today’s stations to tomorrow’s factories, data centers, and off-world bases.

https://www.icarusrobotics.com/

What if “AI teammates” aren’t sci-fi at all, but the next mundane tool that quietly kills Monday dread?

In this episode of AI-Curious, we sit down with David Shim, CEO of Read.ai, to unpack what workers actually want from AI, how teams are adopting agents from the bottom up, and what a practical “digital twin” might do at work—minus the Black Mirror vibes. We cover fast-path ROI (meeting notes → action items), the shift from “prompts” to ambient workflows, and why the most valuable corporate asset may soon be the storage of intelligence—the living record of how your organization thinks and decides.

What we cover

• Why 70% of workers say they want AI agents—and what basic tasks deliver real ROI now
• A crawl-walk-run roadmap: note-taking → briefing → follow-ups → lightweight agents → digital twin
• “Storage of intelligence” as a competitive moat (institutional knowledge that doesn’t walk out the door)
• Guardrails, data separation, and how to make privacy concerns non-negotiable
• Bottom-up adoption: why employees are forcing IT’s hand—and how leaders should respond
• The macro view: augmentation vs. replacement, and the provocative idea that AI replaces computers (as the interface)

If you find this useful, we’d love a rating and a quick share with a teammate who’s piloting AI at work.

Read.AI:

https://www.read.ai/

AI is often framed as a climate problem—energy-hungry data centers, ballooning carbon emissions, and talk of nuclear power just to keep the servers running. But could AI also become part of the solution?

In this episode of AI-Curious, we sit down with Josh Dorfman—climate tech entrepreneur and host of Supercool—to explore how artificial intelligence might help tackle climate change. Josh doesn’t offer hand-wavy promises. Instead, we dive into concrete examples where AI is already making a difference.

What we cover:

• [4:17] Josh’s background at the intersection of technology, climate, and business.
• [8:18] How AI data centers are impacting energy use—and why fossil fuels can’t scale to meet demand.
• [12:30] The role of nuclear, geothermal, and solar-plus-storage in powering AI sustainably.
• [23:25] AI-optimized school buses: how Oakland electrified its fleet with fewer vehicles.
• [27:44] BrainBox AI and smarter buildings: cutting emissions through predictive HVAC optimization.
• [31:42] AI in waste management: from pneumatic trash tubes to AI sorting recyclables.
• [41:17] Big-picture futures: AI efficiency, plummeting solar costs, and the possibility of “trivially cheap” energy.

The conversation blends realism with optimism—grounded in the challenges of energy demand, yet hopeful about AI-driven solutions in transportation, buildings, waste, and renewable power.

If you’ve ever wondered whether AI can be more than an energy drain—and instead help drive sustainability—this episode offers both perspective and inspiration.

🎧 Subscribe to AI-Curious:

• Apple Podcasts
https://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308

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https://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b

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https://www.youtube.com/@jeffwilser

Can artificial intelligence actually be funny, or is humor still a human stronghold? We explore that question with Eric Doyle, co-founder of ComedyBytes, a Brooklyn-based multimedia comedy show where AI and humans face off in roast battles, dating games, and other interactive formats. Doyle combines the craft of stand-up with the tools of generative AI, building AI characters like “AI Kanye West” or “AI Sarah Silverman” that deliver pre-scripted jokes in real time.

In this episode of AI-Curious, we dig into:

• [0:52] The story behind ComedyBytes and its AI-powered format
• [3:46] How AI roast battles work, from concept to stage mechanics
• [7:53] Using tools like ChatGPT, Claude Sonnet, and Gemini AI to write jokes
• [12:55] The art of prompting for humor and boosting the “funny hit rate”
• [16:36] Why specificity matters in generative AI comedy
• [23:43] Inside the “Data-ing Game,” an AI twist on the classic dating game
• [25:58] Can AI really be funny—or just imitate the structure of humor?
• [32:30] The triple, listing technique, and other joke-writing structures AI can learn
• [39:10] Advice for non-comedians using AI to add humor
• [41:24] The future of AI in entertainment and its impact on creators

From the structure and anatomy of a joke to the ethics of deepfake comedy, this conversation blends technology, performance, and the evolving role of AI in creative work. Whether you’re an AI enthusiast, a comedy fan, or simply curious about where these worlds collide, this is a look at AI and humor you haven’t heard before.

Is Kant the new code? If AI can write, code, and even plan, which human skills suddenly become scarce—and valuable?

In this conversation with Robert Capps (former Editorial Director of Wired, contributor to The New York Times Magazine), we dive into his widely shared NYT Mag feature, “AI Might Take Your Job. Here Are 22 New Ones It Could Give You.” We unpack the three big buckets of new work he sees emerging—Trust, Integrators, and Taste—and explore why philosophy majors, auditors, and “AI translators” may be the surprise winners. We also get frank about hallucinations, over-extrapolation, inequality, lethal autonomous weapons, and why Rob still comes out more optimistic.

In this episode of AI-Curious, we:

• Break down Rob’s three buckets of future AI jobs: Trust (auditors, ethicists, legal guarantors), Integrators (the translators who know both your business and the models), and Taste (the Rick Rubin-esque role of vision, judgment, and curation).
• Talk about why Ethan Mollick refuses to let AI write his first drafts—and why that matters for your own thinking.
• Examine how “the tools will be commodities, not the people,” and what that means for founders, creators, journalists, and scrappy upstarts.
• Get into the very real risk of inequality and policy paralysis—and why UBI isn’t a satisfying answer.
• Preview Rob’s documentary on AI weapons and the fight to keep humans in the loop.

Takeaways

• Trust work explodes. Expect a cottage industry of auditors, ethicists, and “legal guarantors” to ensure AI output is accurate, defensible, and compliant.
• Integrators win inside companies. The most valuable people will be those who can translate between business reality and fast-moving model ecosystems.
• Taste is leverage. Vision, taste, and editorial judgment—knowing what good looks like—become the human moat.
• Beware first-draft capture. Letting AI write your first draft can quietly dominate your thinking (Mollick’s rule is worth adopting).
• Inequality is the real threat. Most experts Rob spoke with fear a rapid widening of inequality more than mass permanent joblessness.
• Tools, not people, become commodities. When everyone has Goldman-tier tools, expect disruption from the bottom, not reinforcement of the top.

Rob’s NYT Magazine piece: “AI Might Take Your Job. Here Are 22 New Ones It Could Give You.”

https://www.nytimes.com/2025/06/17/magazine/ai-new-jobs.html

Could AI actually improve public education? Not just automate it, but make it more personalized, more equitable — and even more human?

We explore this possibility with Dr. Michael Everest, founder of edYOU, an AI tutoring platform being piloted in a Denver-area school district. While many worry that AI could become a shortcut for students to avoid real learning, Everest argues the opposite — that AI can reinforce understanding, boost confidence, and offer 24/7 support tailored to each student’s needs.

In this episode of AI-Curious, we dig into the real-world mechanics of how this works — including partnerships with schools, how teachers interact with the platform, and what kind of results they’re seeing so far.

We also ask the tough questions: What about data privacy? What about bias and hallucinations? Is there a risk we’re outsourcing critical thinking? And what does the future of education look like if every student has a lifelong AI companion?

Topics include:

• The promise and pitfalls of AI in classrooms
• edYOU’s pilot program with Adams 14 School District
• How the AI tutoring platform personalizes learning
• The role of teachers in an AI-enhanced education system
• Oversight, privacy, and academic integrity
• The vision of a lifelong AI learning companion

Whether you’re a parent, educator, technologist, or just curious about where education is headed, this conversation offers a grounded, hopeful — and at times provocative — look at the future of learning.

What happens when AI becomes a co-pilot for writers, researchers, and journalists — not in theory, but in practice?

In this episode of AI-Curious, we speak with Bill Wasik, Editorial Director of The New York Times Magazine, who recently oversaw their special issue, “Learning to Live with AI.” We explore how AI is already transforming journalism, nonfiction writing, and historical research — and why the most interesting impacts may come not from content creation, but from how we discover, organize, and interpret information.

We dig into the creative tension between AI and human storytelling, including how historians are using tools like NotebookLM to tackle research projects previously deemed impossible. Bill shares how AI can augment writing workflows without compromising editorial judgment — and why trust and authorship still matter in a world of fast content.

We also cover:

• The risks of over-relying on AI for research (19:45)
• How AI might transform local journalism and accountability (41:30)
• The evolving AI policies at The New York Times (29:40)
• Whether AI could ever win the Booker Prize — and what that would mean (7:30)
• Use cases from historians and academics using ChatGPT (26:00)

Bill's (excellent) piece: "AI is Poised to Rewrite History. Literally."

https://www.nytimes.com/2025/06/16/magazine/ai-history-historians-scholarship.html

The NYT Magazine's Special Issue:

https://www.nytimes.com/2025/06/16/magazine/using-ai-hard-fork.html