HAIA Agents: From the Definition Problem to Running Code

Every organization that puts AI to work makes the same choice, whether it names the choice or not. It can let agents carry the work with machines checking machines, or keep human agency in the work, with a named person holding authority at checkpoints and answering for what comes out. This Deep Dive on Basil C. Puglisi's article walks through Responsible AI as the factory and AI Governance as the handmade product, where each one belongs, and the rule each one carries. It covers why presence is not authority, the inspection mark a handmade product can carry, and cases that run from an airline chatbot to Australia's Robodebt scheme. It also weighs what research on disclosure and labels has found and what none of it has tested, along with the procurement question any officer can answer. It then covers the EU AI Act and how an SEC enforcement action, Colorado's new law, and New York's court rule reach the same line by other routes. https://basilpuglisi.com/agents-agency-transparency/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using the HAIA Ecosystem

Tesla now calls itself a physical AI company, and its own record makes it the clearest live test of what autonomous really means. This deep dive follows the Optimus humanoid robot from the 2024 We, Robot demonstrations, where humans remotely operated much of the interaction, to Elon Musk's January 2026 statement that Optimus was not contributing to manufacturing work in any material way, and on to the new Fremont lines that feed an Optimus Academy for training data. It then follows the Robotaxi from its June 2025 launch with a passenger-seat safety monitor to the March 2026 letter in which Tesla told Senator Edward Markey how remote operators can redirect, command, and, as a last resort, control its vehicles. The episode covers NHTSA's audit of the Cybercab self-certification, the engineering analysis of Tesla's camera-based driving system, the capital behind the bet, and the investors and researchers who read the same record in opposite ways. The takeaway is that one word, autonomous, covers six operating modes, and every claim needs its mode, its date, its source, and a named human who decides. Read the full article: https://basilpuglisi.com/physical-ai-platform-shift/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using the HAIA Ecosystem

Chat made AI legible to every board. Robots that see, plan, and act now make it consequential in warehouses, labs, hospitals, and homes, where a wrong output moves mass instead of words. This episode works through the case that physical AI is the next platform shift, and through the reasons the deployment ledger still trails it. It covers the investor thesis that robot learning, autonomous science, and new human-machine interfaces are the next compounding domains beyond language and code. It weighs that thesis against independent economic evidence that robots can perform most physical work tasks in at least some settings yet are cost-competitive for only a small fraction of job tasks today. The hosts walk the model build path from NVIDIA Isaac GR00T, Google DeepMind's Gemini Robotics, and Physical Intelligence's π₀ through their 2026 successors, and why vendor results stay condition-specific. They work through the reliability arithmetic that decides whether a multi-step robot task survives production, and what a real deployment's hardware ledger reveals. They also cover why classical automation keeps the burden of proof on the learning system, and why every learned cell needs a tested fallback. The episode closes on governance. A weekly evidence cadence ends with a named person who decides to accept, modify, or reject, and who answers for the result. Model capability, deployment economics, and functional safety stay separate, and the checkpoint sits above engineered safety rather than replacing it. Read the full article: https://basilpuglisi.com/physical-ai-platform-shift/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using the HAIA Ecosystem

This episode is a story, told for entertainment. Teresa writes grant proposals for a food bank with a machine open on the second screen. Her brother-in-law Dale builds the air systems that keep hospitals breathing and has never typed a prompt. Over one backyard argument he asks the question every AI user hears, and her answer runs through Tron in 1982, Phil Tippett and the dinosaurs of Jurassic Park in 1993, and the two adaptations of The Shining, before it lands on the three old reasons people refuse a new tool. The history in the story is real and sourced. The people at the table are invented. Read the full story at https://basilpuglisi.com/intelligent-why-use-ai/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using the HAIA Ecosystem

Two trials gave students the same kind of AI tutor and got opposite results. When most instructors left the tutor on its default setting, grades and participation fell. When researchers built the tutor on practices from learning research, it produced more than double the median learning gains of an in-class active learning lesson. What changed between the two was the method around the tool. This episode works through what an AI literacy program built on methods education already trusts would look like. It covers active learning, scaffolding withdrawn on schedule, and metacognition, and what recent research on AI and cognitive offloading adds to them. It then walks the program itself, from ground rules before any AI use to a first assignment that builds the habit of challenge. At its center is the Checkpoint Session, six steps from Human First to Own. The last step ends with a named human who accepts, modifies, or rejects the work and signs for it. The hosts cover how learners would be measured, including with the tools removed, why signed records are never edited, and why each program follows its graduates into work. They walk three programs that carry one standard from high school through an associate degree to a professional certificate. The episode closes on what remains unproven, because the design has not yet been tested and the evaluation belongs to people who did not design it. Read the full article: https://basilpuglisi.com/ai-education-methods/ Podcast: The Other AI: Audio Briefings on Augmented Intelligence and AI Governance Spotify: https://open.spotify.com/show/033dvhzMIcWLdY7IUgsu7F Apple Podcasts: https://podcasts.apple.com/us/podcast/id1896506152 Amazon Music: https://music.amazon.com/podcasts/923d1a79-533f-4623-bae3-e2ba83453dfb YouTube playlist: https://www.youtube.com/playlist?list=PLchpU2bIYoEEBh2hdY-BVP9ckyTPiHOAQ Generated using NotebookLM. Content may have inaccuracies. For full detail refer to the original paper, document, or article. These are AI generated under NotebookLM as audio overviews not polished products. #AIassisted using the HAIA Ecosystem