In this episode I cover how AI access and permissions have changed since ChatGPT launched back in 2022, from zero connections and basically zero worry to the current YOLO approach of vibe coders and early adopters. I share what I currently give Claude access to, what my biggest concern is, and offer a read/write/act framework that you can use to decide what your AI should touch.

• How AI access sentiment has changed over 4 years
• 2022: ChatGPT with zero connections
• 2023: Bard connects to Gmail, Docs, Drive, Maps
• MCP and the "AI in my email" era
• Agentic AI, Claude Code, and Claude Cowork
• What I currently give Claude access to
• Prompt injection: my biggest concern
• Read/write/act framework
• Privacy, client data, and benefit vs. risk
• How I used AI this week: Claude-Descript connector and pulling quotes from transcripts

• Listen to Ep. 51: WTF is MCP
• 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.

• (00:00:05) - Intro and Episode Overview
• (00:01:32) - Early AI Access: ChatGPT and Bard Origins (2022-2023)
• (00:04:16) - MCP and the Rise of Agentic AI (2024-2025)
• (00:06:23) - Claude Cowork and Mainstream Agentic Adoption
• (00:08:23) - Personal Evolution in Granting AI Access
• (00:10:15) - Prompt Injection Risks Explained
• (00:11:20) - A Framework: Read, Write, Act and Whose Data
• (00:13:38) - Privacy Concerns vs Personal Comfort
• (00:15:01) - Training Data Concerns
• (00:15:28) - Handling Clients' and Others' Data
• (00:17:08) - Healthcare, Therapy, and Sensitive Data Gray Areas
• (00:18:34) - Benefit vs Risk: The Big Picture on AI Access
• (00:20:26) - Final Thoughts on What Your AI Should Access
• (00:20:58) - How I Used AI This Week: Claude and Descript
• (00:23:10) - Outro and Sign Off

Is AI actually going to kill us all?There's been a ton of talk about this topic in the media lately, and so I'm dedicating an episode to sharing my thoughts. Spoiler alert, no, I don’t think that AI is going to kill us, but that doesn’t mean that this technology has no risk. I walk through the Jacob Coxon resignation thread and the fact that Anthropic's own alignment team admits there's genuine risk, then get into why the doom talk feels more irresponsible than credible. I don't think regulation is coming to save us anytime soon, but to me, the answer isn't fear, it’s curiosity.

• Directly answering the question: Will AI kill us all?
• Jacob Coxon's resignation thread on X
• Evan Hubinger's tweets on AI risk
• Defining superintelligence and recursive self-improvement (RSI)
• Moving the goalposts from AGI to superintelligence
• AI's coding and hacking capabilities
• Jake Handy's prediction about a coming AI crisis
• Why the AI-doom talk feels irresponsible
• Regulation and data centers as oil
• Dario Amodei's blog post
• Change doesn't happen in a vacuum
• How I used AI this week: Replacing my Jeep’s thermostat housing

• Read Jacob Coxon's resignation thread on X
• Listen to Ed Zitron's podcast episode about AI and regulation
• Read Dario Amodei's blog post, "We Must Pace the Frontier"
• 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.

• (00:00:05) - Intro and today's topic: will AI kill us all?
• (00:03:29) - Background: Jacob Cox's resignation and Anthropic's Evan Hubinger
• (00:05:18) - Defining superintelligence and recursive self-improvement
• (00:07:19) - Why the doom claims seem overblown right now
• (00:10:39) - Hacking risks and predictions of a coming AI-caused crisis
• (00:12:15) - Irresponsible messaging and the case for transparency
• (00:13:24) - Government incentives, profit motives, and the China narrative
• (00:17:24) - Dario Amodei's regulation plan and skepticism about government action
• (00:19:10) - Staying a realist: humans, open source, and hope for the future
• (00:21:11) - How I Use AI This Week: the rattling thermostat story
• (00:23:17) - Closing thoughts and sign-off

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.

• Jacob Coxon's resignation and AI regulation warnings
• Anthropic's Fable 5.1 and Mythos 5.1 updates
• OpenAI's GPT-6 Astra release
• Astra's "Critical" cybersecurity capability rating
• AGI throwback to Episode 7
• Meta Muse launch: everyone gets an agent
• Meta Muse access, pricing, and privacy details
• Why Meta Muse is a terrible idea
• How I used AI this week: Gemini AI Overviews

• Read Jacob's statements on X
• Listen to Ep. 7: What is AI?
• Subscribe to the Prompting Curiosity newsletter
• Submit a Question
• Visit the Website
• Feeling curious AND generous? Click here to support the podcast.

• (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

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.

• AI as holding up a mirror
• Defining cheating
• Why the school/sports rulebook framing doesn't fit AI
• Why AI is an easy punching bag right now
• Breaking down disclosure, rules, and trust
• Questions worth asking
• Is someone less trustworthy if they use AI?
• How I used AI this week: Reverse image search to find desk assembly instructions

• Listen to Ep. 3: Is ChatGPT Killing Creativity?
• 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.

• (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

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.

• WTF is a frontier model?
• Most people's assumption vs. the technical definition
• Origin of the term: the Frontier Model Forum (July 2023)
• FMF's official definition of "frontier model"
• EU AI Act's compute-based definition
• Who made the rules
• FMF today: expanded membership, safety research, AI Safety Fund
• Why forming the FMF actually benefited these companies
• Open weight models and "frontier-grade" labels
• How I used AI this week: building my mom a workout tracker

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

• (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

In this episode I break down the best way to teach Claude how to complete specific tasks in a repeatable way: Claude Skills. I explain how Skills work, walk through how to build your own, and cover the real differences between Skills and Projects. As per always, the best way to understand this stuff is to try it yourself first hand, but hopefully this episode will give you some ideas and a nice jumpstart.

• What Claude Skills are
• Definition of Skills (from Anthropic)
• How Skills load and fire automatically
• Progressive disclosure explained
• Claude's skill directory and the GitHub skills repo
• How to create a skill
• Creating skills via Settings
• My client-debrief skill example
• Skills vs. Projects
• How I used AI this week: Granola and the Granola MCP

• Listen to Ep 51: WTF is MCP?
• Listen to Ep. 45: Stop Tying, Start Speaking: Wispr Flow Explained
• 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.

• (00:00:05) - Prompting Curiosity: The AI Curious
• (00:00:38) - Episode 58
• (00:02:24) - Anthropic Skills: What is a Skill?
• (00:08:10) - Claude 2.8: Creating a Skill
• (00:14:56) - Skills and Projects in ChatGPT
• (00:17:16) - How I Use AI to T transcribe my Calls
• (00:21:33) - How to Use AI in the Podcast

In this episode I get into AI watermarking, starting with Claude's new invisible watermark and Substack's "Scan for AI text" feature with Pangram. I break down the EU AI Act rules driving this, how OpenAI, Google, Meta, Microsoft, Mistral, and xAI are (or aren't) handling it, and my thoughts as to the actual motives behind why companies are rolling out these changes.

• AI models escaping sandbox testing
• Substack's "Scan for AI text" feature with Pangram
• Anthropic's new invisible Claude watermark
• The EU AI Act and Article 50
• How OpenAI, Google, Meta, Microsoft, Mistral, and xAI stack up
• China's mandatory AI disclosure laws
• Problems with AI detectors and false positives
• The "why" behind watermarking
• How I used AI this week: AI-generated sound effects in Descript

• Listen to Ep. 2: ChatGPT and the Environment: Energy, Water, and Carbon Emissions
• 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.

• (00:00:05) - Promoting Curiosity: The AI Curious
• (00:00:38) - AI Watermarking
• (00:04:43) - AI Watermarking
• (00:06:16) - Anthropic's Cloud Watermarking
• (00:07:58) - Deepfakes and Text Watermarking
• (00:13:08) - AI Watermarking: Concerns
• (00:18:15) - How I Used AI This Week
• (00:19:15) - Questions For Curious People

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.

• Celebrating one year of Prompting Curiosity
• Riffing on unfiltered thoughts about AI in August 2026
• The Threads discourse on AI
• General thoughts on AI and unequal benefits
• AI as capitalism's easy scapegoat
• Funny money and bubble talk
• Fin-tech burnout and no predictions
• Forced adoption and the "no great use case" problem
• AI's impact on search and generational usage differences
• Why I'm not willing to give up AI
• Blaming the individual vs. corporate accountability
• What amazes me
• How I used AI this week: Google NotebookLM use-case for blogging

• Listen to Ep: 25 - Google NotebookLM: The Best AI Tool You've Never Heard Of
• 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.

• (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