AI-Curious with Jeff Wilser

• LinkedIn's Chief AI Officer, Deepak Agarwal, on AI Agents, Building Responsible AI, and the Future of Work

  What does hiring look like when AI is embedded into the world’s largest professional network—and how should leaders, recruiters, and job-seekers adapt?We sit down with Deepak Agarwal, LinkedIn’s Chief AI Officer, for a practical playbook on AI at work: production-grade AI agents for hiring, how semantic job search changes discovery, why “relevance” is the antidote to spammy outreach, and how to build a culture of responsible AI that scales. We unpack where humans stay firmly in the loop—and how AI can reduce friction, close information asymmetries, and free more time for real human connection.Highlights•LinkedIn’s AI agents (incl. Hiring Assistant) are in market with paying customers; routine sourcing drops from ~40 hours to a few, while humans focus on candidate fit and relationship-building.•Semantic job search moves beyond keywords to plain-English intent and better matching across people, jobs, and knowledge.•Responsible AI is baked in: bias detection/mitigation, rigorous pre-launch testing, and governance—treated as a must-have, not an afterthought.•“Relevance is the key currency”: better matching reduces spray-and-pray outreach and AI-to-AI noise.•Guidance for leaders: embrace discomfort, start from the problem (not the tool), choose the right autonomy level, and rethink testing for non-deterministic systems.•Guidance for job-seekers: be authentic, upskill, and optimize for the next five years—not the next five months.•Future of work: AI shrinks the 80% “prep” to expand the 20% creative/strategic work; humans remain in control.If you’re curious about our AI & Leadership event, The Drawing Room at The Explorers Club in NYC, learn more at TheDrawingRoom.ai. If you found this useful, follow the show, rate/review, and share with a hiring leader or job-seeker who needs a clear view of what’s coming.LinkedInAI-Curious

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• Why GEO is the New SEO--And How Businesses Must Adapt--w/ Curtis Sparrer, co-founder of Bospar

  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 coverGEO vs. AEO vs. classic SEO—clear definitions and where each mattersHow 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 workedPractical GEO hygiene: what to keep from the SEO playbook; what to adapt for AI reasoningPitching in the AI era: why templated, “robotic” outreach backfires and how to use AI for ideation and structure, not the final draftWinners & losers: PR-skeptics vs. teams that proactively feed reputable signals to modelsNear-term predictions: from “AI ethics” to emerging AI manners—what will be considered rude or acceptable AI use in commsGuestCurtis Sparrer — Co-founder & Principal, Bospar PR; President, San Francisco Press Club.Bospar:https://bospar.com/Forbes coverage of Audit-E launchhttps://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.

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• Space Robots Are Here *Now*, w/ Icarus Robotics cofounders Ethan Barajas and Jamie Palmer

  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 coverWhy astronaut hours are precious—and how robots can “augment” rather than replace themThe form factor: free-flying, drone-like bodies with dual arms optimized for zero-G dexterityInside first, outside later: a deployment strategy that lowers safety hurdles and accelerates learningData advantage: building the first large microgravity manipulation dataset via continuous teleopAI’s role: from human-in-the-loop control to primitives to scalable dexterous manipulationCommunications and latency: S-band today, laser links tomorrow; what “real-time” actually meansThe “orbital factory” thesis: pharma, semiconductors, fiber optics—and servicing orbital data centersLong-horizon forecasts: humans living and working in space; physical labor increasingly done by robotsGuestsEthan Barajas — Co-founder & CEO, Icarus RobotsJamie Palmer — Co-founder & CTO, Icarus RobotsWhy this mattersIf 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/

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• AI Agents, Digital Twins, and the Future of Work, w/ Read.AI CEO David Shim

  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 coverWhy 70% of workers say they want AI agents—and what basic tasks deliver real ROI nowA 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-negotiableBottom-up adoption: why employees are forcing IT’s hand—and how leaders should respondThe 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/

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• How AI Could Help Solve Climate Change, w/ Climate Tech Expert Josh Dorfman

  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 Podcastshttps://podcasts.apple.com/us/podcast/ai-curious-with-jeff-wilser/id1703130308• Spotifyhttps://open.spotify.com/show/70a9Xbhu5XQ47YOgVTE44Q?si=c31e2c02d8b64f1b• YouTubehttps://www.youtube.com/@jeffwilser

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