I Have Some AI Questions (With Justin Coats) Episodes

Justin Coates, co-founder of LearnAir, demos ChatGPT’s new always-on, voice-driven AI agents (Dots) and the “Space” work hub, and explores what changes when work becomes something you can direct and supervise while you are actually living your life. 🧭 Conversation Highlights Dots and related always-on agents connect to your digital work stack, so they can keep working using context from what you’ve linked. The episode centers on real demos: updating a podcast run-of-show doc, fixing broken int...

Erik and Justin dig into whether today’s AI risks are being overstated by headlines, and what a practical approach should look like for pacing, alignment, and cybersecurity hardening as AI agents grow more capable. 🧭 Conversation Highlights Erik challenges the “frontier labs prove everything is catastrophic” framing, arguing that real-world harm requires unusual capability, access, and resources. Justin counters with a “toy rocket vs frontier rocket” analogy: risk is real, but the systems most...

Justin Coats joins Erik for another take of their weekly issue of the AI Questions section. This time, joined as well by Rebecca Maloney, Director of IT at Hayden Homes. She shares how they drove real AI adoption by starting with process and culture, building governance and training before expanding tools, and using human conversations to unlock faster handoffs across the home-building chain. 🧭 Conversation Highlights AI adoption at Hayden started with where work is getting duplicated across ha...

Erik and Justin unpack why the “AI wrote it” controversy hit so hard, and what “human-in-the-loop” should realistically mean going forward. They land on traceability, disclosure, and an explicit “human floor” rather than moral panic or blind purism. 🧭 Conversation Highlights They separate the question of content quality from the authorship and disclosure expectations behind high-trust publishing. Justin argues responsible AI use is fine when the human guides, edits, and owns the intent, but he...

Erik and Justin reset the conversation from AI tactics back to the “grand dream,” sharing optimistic, near-term business use cases, especially in healthcare and logistics/robotics. 🧭 Conversation Highlights Erik and Justin contrast doom narratives about AI with what they see in adoption and day-to-day workflow changes. Justin argues healthcare will feel AI gains as improved care and reduced administrative friction, not mass job loss. They dig into the “separate human from digital” idea: let A...

Asher Albertini, an 18-year-old high school senior and former LearnAir intern, shares what AI has changed for him in school, friendships, and career thinking, and how his generation should prepare for a future where entry-level work gets redefined. 🧭 Conversation Highlights AI detectors and grading: detectors are often inaccurate and only really target essay-style work, while better approaches include timed writing and drafts/version history. Entry-level roles are changing: Asher sees AI takin...

With Erik out, Justin Coats steps into the host chair for a conversation with veteran creative Carl Loeb about what happens when generative AI enters the creative process—and why the answer isn’t to resist it or surrender to it. Carl draws on nearly 40 years in advertising, branding, and technology to make the case that AI is an extraordinary thinking partner, but humans still bring something essential to the work: taste, discernment, emotion, ownership, accountability, and lived experience. T...

Justin Coats breaks down the idea of “super apps” for AI and what that really means for corporate adoption, change management, security, and tokenomics. 🧭 Conversation Highlights Justin defines super apps as AI workspaces that combine model access, agents, and computer or browser use in one interface. Erik pushes on the human side of adoption and asks whether waiting for the tech to mature actually reduces the real cost. They discuss how change management needs education, executive buy-in, an...

Erik and Justin tackle viewer-submitted AI questions in a practical Q&A focused on trust, compliance, meeting recording boundaries, and how to scale an AI pilot without losing control. 🧭 Conversation Highlights Trust AI at work by treating it like human trust: start slow, use tasks you can verify, and measure over repetition. For compliance constrained data, begin with low-risk admin work, then use governance, vendor requirements, and existing industry frameworks to guide decisions. Decide wh...

Erik and Justin dig into how fast-moving AI platforms are changing (sometimes without warning) and what business leaders can do to avoid broken workflows, plus a few concrete examples like GPT Live voice, ChatGPT Work, and Atlas being retired. 🧭 Conversation Highlights AI updates follow iterative deployment, so changes land when features are ready, not on a schedule, and teams often notice only when something breaks. Justin argues for an “AI champion” steward who monitors release notes, tests ...

Erik and Justin unpack Paul Rotzer’s AI maturity “eight pillars” and use it to frame what leaders should do after the hype: step back, explore what AI can do, choose a priority problem, then build vision, strategy, governance, literacy, and measurement in that order. 🧭 Conversation Highlights AI adoption is a forcing function: excitement about what AI can do often triggers the harder question of what the business should actually solve first. Justin argues for a mindset shift from “pick the per...

Erik and Justin talk through why AI agents get stuck when teams cannot articulate how work is done, and why the answer is iterative agent deployment with guardrails, sandbox testing, and ongoing process refinement. 🧭 Conversation Highlights Most professionals struggle to explain the steps of their work, which blocks automation and agent adoption. Agents feel hard to hand off to because people fear losing control, making mistakes, or looking foolish. A practical path forward is iterative proce...

Erik shares how he’s running a week-one “vibe coding” summer curriculum for his 10- and 7-year-old daughters using voice-first ChatGPT. He and Justin unpack what’s working, what friction to watch for, and how to think about learning, iteration, and human responsibility as AI becomes the new interface. 🧭 Conversation Highlights Erik’s kids start with voice prompts to generate images, then turn them into stories and comic panels. When they hit “out of ideas,” they switch to a question-driven loop...

Erik and Justin take a practical tour through AI “tools that actually ship.” They start with Lovable to build a real landing page fast, then move to NotebookLM for source-grounded research and repackaging, and finish with Spinach AI for meeting intelligence that turns conversations into executable next steps. 🧭 Conversation Highlights Erik’s Lovable experience: a subsite built in minutes by feeding a prompt and letting the tool pull branding, structure the story, and generate interactive compon...

Erik and Justin unpack what an “AI orchestration layer” actually means when agents move from experiments into day-to-day operations. They focus on the practical shift from building tools to managing systems: mirroring the org chart with digital agents, defining who maintains them, and creating an auditing layer so leaders can trust performance at scale. 🧭 Conversation Highlights Teams are quickly moving from a handful of agents to managing 5 to 10 agents per person, and that forces org design q...

Erik and Justin dig into what it actually means for AI to “become real,” arguing that consumer usage does not equal workplace adoption. The conversation lands on a “pause moment” where organizations are finally forced to address governance, security, policy, and measurement because the tools are now powerful enough to create real operational risk and real operational leverage. 🧭 Conversation Highlights Justin distinguishes massive user counts from meaningful adoption, emphasizing that most peop...

Erik and Justin unpack a recent story about an AI agent deleting a rental car company’s entire database, using it as a real-world forcing function for how leaders should think about agent risk, permissions, and organizational readiness. 🧭 Conversation Highlights Justin frames the incident as evidence of technical limitations, rapid capability growth, and a lack of widespread agent literacy. Erik pushes on the core fear: even if you tell an agent “don’t do that,” an agent with write/delete powe...

This conversation shifts from theory to reality. Erik and Justin move beyond what AI could do and into how it actually works today—and more importantly, how most people are using it wrong without realizing it. From hidden settings that quietly degrade performance to the emergence of AI agents that can act on your behalf, this episode exposes a new layer of the AI conversation: your results are only as good as your setup. The big unlock? AI isn’t just a tool anymore—it’s becoming a customizabl...

In this follow-up to last week's conversation, Erik and Justin tackle one of the most emotionally charged topics in AI: job displacement. But instead of fear-based predictions, they reframe the conversation entirely. The real story isn’t that AI is replacing jobs—it’s that most people don’t understand what parts of their job actually create value. They introduce a powerful lens: “white-collar factory work” vs. truly human work. And once you see that distinction, everything changes—from how you...

This episode marks the beginning of a new weekly series featuring Justin Coats—AI expert, co-founder of LearnAir™, and now recurring co-host. Erik brings his biggest questions about AI in business, and Justin brings grounded, practical answers. The core tension? AI isn’t the limiting factor—humans are. Specifically, our lack of awareness around how we actually work. Together, Erik and Justin unpack why most businesses struggle to adopt AI, how vague thinking kills automation, and why leadershi...