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

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

• YouTube
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.