Prompting Curiosity

Dr. Shanté Cofield aka The Maestro

Prompting Curiosity is a podcast for the AI-curious, no coding background required. Join Dr. Shanté Cofield, also known as the Maestro, to explore what these AI tools actually are, how to use them, and what they might mean for how we think, work, create, and move through life. Tune in every Thursday to get your fix. Stay curious.

  1. 1일 전

    Ep. 61: Everyone Gets an Agent: Meta Muse and the Ongoing Race to AGI

    In this episode I talk about the eleventy billion AI models that dropped in the past few weeks, including Anthropic's Fable 5.1 and Mythos 5.1, OpenAI's GPT-6 Astra, and Meta's new Muse agent. I get into former Anthropic researcher Jacob Coxon's resignation and his warning about AI risk, plus what it actually means that OpenAI just rated Astra "Critical" for cybersecurity capability. I also share why I think Meta Muse is a terrible idea and what all of these model drops say about the direction AI is heading. Main Topics Covered Jacob Coxon's resignation and AI regulation warningsAnthropic's Fable 5.1 and Mythos 5.1 updatesOpenAI's GPT-6 Astra releaseAstra's "Critical" cybersecurity capability ratingAGI throwback to Episode 7Meta Muse launch: everyone gets an agentMeta Muse access, pricing, and privacy detailsWhy Meta Muse is a terrible ideaHow I used AI this week: Gemini AI Overviews Links & Resources for This Episode Read Jacob's statements on X Listen to Ep. 7: What is AI? Subscribe to the Prompting Curiosity newsletterSubmit a QuestionVisit the WebsiteFeeling curious AND generous? Click here to support the podcast. Chapters (00:00:05) - Intro and welcome(00:00:38) - Jacob Coxon's anthropic resignation statement(00:01:41) - Reflections on AI regulation and motives(00:04:56) - Recent model drops overview(00:06:14) - Anthropic's Fable and Mythos updates(00:07:25) - OpenAI's GPT-6 Astra and computer use capabilities(00:10:01) - Astra's critical cyber capability rating(00:11:27) - AGI claims and the race to super intelligence(00:13:46) - Meta's Muse agent launch and concerns(00:15:13) - Muse's privacy and data risks(00:16:44) - Who Meta Muse targets and risks to users(00:17:38) - Companies' true priorities: money over safety(00:18:23) - How I used AI this week: Gemini overviews(00:20:56) - Wrap up and outro

    Ep. 61: Everyone Gets an Agent: Meta Muse and the Ongoing Race to AGI
  2. 9월 10일

    Ep. 60: Is It Cheating if You Use AI?

    Inspired by a podcast episode my girlfriend recently listened to, I use this episode to tackle the question: “Is it cheating if you use AI”? Using the definition of cheating as a springboard, I break down why the school-and-sports framing most of us default when it comes to cheating, and why the topic warrants a more nuanced approach when considering AI. Along the way I discuss the role of the system at large, and round the episode out by diving into an equally exciting topic for me: how AI use affects trustworthiness. Main Topics Covered AI as holding up a mirrorDefining cheatingWhy the school/sports rulebook framing doesn't fit AIWhy AI is an easy punching bag right nowBreaking down disclosure, rules, and trustQuestions worth askingIs someone less trustworthy if they use AI?How I used AI this week: Reverse image search to find desk assembly instructions Links & Resources for This Episode Listen to Ep. 3: Is ChatGPT Killing Creativity?Read this episode's Curious CompanionSubscribe to the Prompting Curiosity newsletterSubmit a QuestionVisit the WebsiteFeeling curious AND generous? Click here to support the podcast. Chapters (00:00:05) - Prompting Curiosity: The AI Curious(00:00:38) - Is It Cheating If You Use AI in Your School?(00:02:39) - Is It Cheating to Use AI?(00:03:39) - Is It Cheating If You Use AI?(00:06:47) - I Don't Care If You Use AI(00:07:44) - Does AI Make You Cheat?(00:10:06) - Why Do We Care About AI Cheating?(00:10:59) - Is It Cheating if You Use AI?(00:14:40) - How I Used Claude for AI This Week(00:16:24) - Crowning the Curious: A Tech Podcast

    Ep. 60: Is It Cheating if You Use AI?
  3. 9월 3일

    Ep. 59: WTF Is a Frontier Model?

    In this episode I break down WTF a frontier model actually is, starting with what most people assume the term means versus the real technical definition. I cover how "frontier model" got coined in 2023, and why the term even came about at all, and how self-naming benefitted its creators. A bit of an etymology episode, this episode is more about the background of the term, and explores how new open weight models are challenging the definition. Main Topics Covered WTF is a frontier model?Most people's assumption vs. the technical definitionOrigin of the term: the Frontier Model Forum (July 2023)FMF's official definition of "frontier model"EU AI Act's compute-based definitionWho made the rulesFMF today: expanded membership, safety research, AI Safety FundWhy forming the FMF actually benefited these companiesOpen weight models and "frontier-grade" labelsHow I used AI this week: building my mom a workout tracker Links & Resources for This Episode Listen to Ep. 55: Weight, What? An Introduction to Open Source AI ModelsRead this episode's Curious CompanionSubscribe to the Prompting Curiosity newsletterSubmit a QuestionVisit the WebsiteFeeling curious AND generous? Click here to support the podcast. Chapters (00:00:05) - Prompting Curiosity: The AI Curious(00:00:38) - Predicting Curiosity: Frontier Models(00:01:30) - The Frontier Model Forum and its Impact(00:05:56) - Frontier: The Frontier Group(00:08:07) - What's the Frontier?(00:10:00) - How I Used Claude for AI This Week(00:14:15) - AI Curious: A Podcast About Curious People

    Ep. 59: WTF Is a Frontier Model?
  4. 8월 13일

    Ep. 56: 1 Year of Prompting Curiosity: My Current Thoughts About AI

    In this episode we’re celebrating one year of Prompting Curiosity and I’m sharing my unfiltered thoughts about where I stand on AI. I get into why the discourse on Threads is such a mess, why AI is an easy target given the enshittification of everything, and why capitalism (not AI capability) is the real driver behind the issues at hand. No predictions, no hype, just my two pennies on data centers, adoption, and why I'm not willing to give up something that genuinely helps my brain and my business. Main Topics Covered Celebrating one year of Prompting CuriosityRiffing on unfiltered thoughts about AI in August 2026The Threads discourse on AIGeneral thoughts on AI and unequal benefitsAI as capitalism's easy scapegoatFunny money and bubble talkFin-tech burnout and no predictionsForced adoption and the "no great use case" problemAI's impact on search and generational usage differencesWhy I'm not willing to give up AIBlaming the individual vs. corporate accountabilityWhat amazes meHow I used AI this week: Google NotebookLM use-case for blogging Links & Resources for This Episode Listen to Ep: 25 - Google NotebookLM: The Best AI Tool You've Never Heard OfRead this episode's Curious CompanionSubscribe to the Prompting Curiosity newsletterSubmit a QuestionVisit the WebsiteFeeling curious AND generous? Click here to support the podcast. Chapters (00:00:05) - Prompting Curiosity: The AI Curious(00:00:38) - It's Been One Year(00:02:13) - Pushing the Discussion On Social Media(00:03:27) - AI: Good or Evil?(00:05:16) - Should We Stop Developing Artificial Intelligence?(00:06:01) - We Do Not Need These Huge Data Centers(00:06:58) - Can Anyone Predict The Future With AI?(00:12:25) - On AI and What We As A Society Do With It(00:18:27) - Teaching and the Future of AI(00:23:23) - The Future of AI Is Full of Fear(00:25:44) - How We Used AI This Week(00:26:40) - Curious About AI

    Ep. 56: 1 Year of Prompting Curiosity: My Current Thoughts About AI
  5. 8월 6일

    Ep. 55: Weight, What? An Introduction to Open Source AI Models

    In this episode I dig into open weight and open source AI models: what they actually are, why they keep showing up in AI news, and why I think they’re central to future-proofing our AI usage. I cover a bit of the technical aspect, the economic factors at play, and make the case that open weight models are a true hedge against getting stuck forever paying whatever a handful of AI companies decide to charge while simultaneously worrying that access could just be stripped away at any moment. Main Topics Covered What open weight and open source models actually areWhy open models matter: market pricing and individual sovereigntyOpen weight vs. open source definitionsWhy it's called "open weight" (parameters refresher)Who's releasing open weight modelsWhy companies release open weight modelsWhy individuals would choose an open modelHow to try an open weight model yourselfNvidia CEO Jensen Huang's open letter and Anthropic's responseHow I used AI this week: Claude's Scheduled Tasks feature Links & Resources for This Episode Listen to Ep. 17: Will ChatGPT Get Old Navy'd?Read this episode's Curious CompanionSubscribe to the Prompting Curiosity newsletterSubmit a QuestionVisit the WebsiteFeeling curious AND generous? Click here to support the podcast. Chapters (00:00:05) - Promoting Curiosity: The AI Curious(00:00:38) - Requiring Curiosity(00:01:07) - Open Source vs Open Weight(00:01:56) - Open Weight Models: Do They Even Work?(00:08:05) - What is an Open Weight Model?(00:12:43) - What are the Open Weight Models(00:14:16) - Open Weight vs Frontier: The Differences(00:17:14) - Open vs Closed PPT: The Pricing(00:18:59) - On OpenAI and its "free" models(00:21:11) - Choosing the right cloud provider(00:22:09) - Local vs. Hosting: More Tech, More Privacy(00:23:13) - Open Weight Models: How to Try them(00:26:02) - Nvidia's CEO on OpenAI and the Future of AI(00:28:51) - How I Used AI This Week(00:31:25) - Coming Soon: The Curious Companion

    Ep. 55: Weight, What? An Introduction to Open Source AI Models
  6. 7월 30일

    Ep. 54: An Introduction to Perplexity, the Answer Engine

    In this episode I get curious about Perplexity, a name I'd heard used a ton in the AI space but never actually knew what the heck it was. I break down what it is, how its citation-first approach set it apart from ChatGPT early on, and what it can actually do today: Deep Research, Labs, and its push into the agent space with Computer, Brain, and Comet. I also cover the legal issues that are serving as a sneak peek into the future of agent wars, and give my honest take on whether Perplexity is worth using. Main Topics Covered Why this episode What Perplexity actually is Pro and Max pricing tiers Who Perplexity is actually for Perplexity's launch and the citations angle The lawsuits over copyright infringement Live search, Deep Research, and Labs Computer: Perplexity's move into agents Brain, Comet, and the Amazon lawsuit Should you bother with it How I used AI this week: Building a custom content tracker Links & Resources for This Episode Listen to Ep. 52: AI Agents Explained (For Non-Coders) Read Curious Companion Ep. 52: AI Agents Explained (For Non-Coders)  Read this episode's Curious Companion Subscribe to the Prompting Curiosity newsletter Submit a Question Visit the Website Feeling curious AND generous? Click here to support the podcast. Chapters (00:00:05) - Prompting Curiosity: The AI Curious(00:00:38) - Perplexity(00:01:49) - Beyond the Chatbot: Perplexity's Real-Time C(00:07:43) - Microsoft's Computer: An AI Agent in Microsoft 365(00:10:59) - Brain and Comment: Perplexity's AI(00:11:49) - Amazon Is Suing Perplexity Over AI-Backed Browser(00:15:11) - How I Used AI to Build a Content Creation Tracker (Again)(00:19:10) - PODCAST: Help Me Find The Podcast(00:19:37) - Curious Companion

    Ep. 54: An Introduction to Perplexity, the Answer Engine

소개

Prompting Curiosity is a podcast for the AI-curious, no coding background required. Join Dr. Shanté Cofield, also known as the Maestro, to explore what these AI tools actually are, how to use them, and what they might mean for how we think, work, create, and move through life. Tune in every Thursday to get your fix. Stay curious.

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