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.

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.

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.

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.

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.

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.

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.

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.

• What open weight and open source models actually are
• Why open models matter: market pricing and individual sovereignty
• Open weight vs. open source definitions
• Why it's called "open weight" (parameters refresher)
• Who's releasing open weight models
• Why companies release open weight models
• Why individuals would choose an open model
• How to try an open weight model yourself
• Nvidia CEO Jensen Huang's open letter and Anthropic's response
• How I used AI this week: Claude's Scheduled Tasks feature

• Listen to Ep. 17: Will ChatGPT Get Old Navy'd?
• 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.

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.

After years of not knowing what to do with it, I finally decided to give deep research mode a try. In this episode I break down what deep research actually is, how it works under the hood, and how ChatGPT, Gemini, Claude, and Grok stack up against each other. I also walk through real use cases, prompting tips for getting a better report, and a safety reminder about hallucinations and bad citations.

• What deep research actually is
• Release dates
• How deep research works
• Prompting tips
• Example use cases for deep research
• The tool landscape: ChatGPT, Gemini, Claude, Grok
• How to use Research mode
• Safety reminder: hallucinations and bad citations
• How I used AI this week: Identifying podcast topics in the AI space

• Listen to Ep. 52: AI Agents Explained (for Non-coders)
• Listen to Ep. 25: 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.