Podcasts about Permissions

Have you ever felt like you were always the one reaching out, trying harder, or chasing love and connection in a relationship? It can be incredibly painful…especially when it becomes a repeating pattern. And over time, it can be easy to start wondering whether there is something wrong with you. But what if the issue is not about your worth, your looks, or whether you are "good enough"? What if there is a deeper emotional pattern underneath that has been repeating for years without you fully realizing it? In this episode, Brandy shares key insights from working with a beautiful volunteer who had been experiencing frustrating physical symptoms and, in looking deeper, uncovered a long-standing pattern of feeling like she was always chasing love and attention in her relationships. In this episode, you'll discover: Why recurring relationship patterns are important to notice What feeling like you are always "chasing" someone can reveal Why these patterns can be easy to personalize as something being wrong with you How emotional patterns can become deeply ingrained over time Why identifying and transforming the pattern can create more love, connection, and freedom moving forward Sometimes the patterns that hurt the most can also become powerful opportunities for healing and transformation. And when you begin to recognize what has been repeating beneath the surface, it can open the door to a completely different experience in your relationships—and in your life. → Continue Your Self-Healing Journey Listen to the Full Volunteer Self-Healing Session Click here to access today's self-healing session as Brandy Gillmore works directly with Pia Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops. Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com   

If you've been working on healing, transformation, or personal growth and wondering why your results aren't happening as quickly as you'd like, there may be a surprisingly subtle reason. Sometimes, the very beliefs that sound positive, spiritual, or supportive can unintentionally program the mind in a way that makes change harder. In this episode, Brandy shares two common patterns that can quietly slow down healing and transformation. One has to do with the way we think about effort. The other has to do with what it really means to be gentle and loving with ourselves. And both can sound completely positive on the surface. In this episode, you'll discover: Two subtle beliefs that may be slowing down your results Why effort is not necessarily a bad thing How certain ideas about self-love can unintentionally make change feel harder The difference between healthy transformation and overwhelm How to begin programming your mind in a way that supports more momentum, relief, and positive change Sometimes the shift is not about trying harder. It is about making sure your mind is actually programmed in the direction you want to go. Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops.   Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com   

Show DescriptionThe realities of A/B testing, the future of specialized hosting in the AI era, microphone and camera permissions on the web, tricks for working with HTML email, and hyping Midnight Vinyl Club and How Many Dudes? Listen on WebsiteWatch on YouTubeLinks 8 New CSS, JS and HTML Features You Should Know - Syntax #1033 Mermaid | Diagramming and charting tool What Is AI Coding Doing To Us? - YouTube Midnight Vinyl Club MJML - The Responsive Email Framework AT Protocol How Many Dudes? | Download and Play!

Have you ever felt like no matter how much you try to explain yourself, people just don't really understand you? That feeling can seem like a relationship issue on the surface. But what if there is more happening underneath? In this short breakthrough episode, Brandy shares an important insight from working with a beautiful volunteer who had been dealing with recurring health challenges and had spent years working on healing, nutrition, positive thinking, and personal growth. Yet when Brandy began looking deeper, something unexpected surfaced: a strong emotional pattern connected with feeling unheard and misunderstood. What made it especially interesting was that the volunteer did not initially realize how much anger and frustration were connected to this pattern. As Brandy began addressing the feeling of being heard and understood, the volunteer immediately noticed a physical shift in her shoulders. In this episode, you'll discover: • Why feeling misunderstood can become a deeper emotional pattern • How frustration and anger can remain active even when you see yourself as positive and loving • Why the need to be heard can create ongoing inner tension • What to notice if feeling misunderstood has become a recurring theme in your life • How changing the emotional pattern may begin creating more connection, harmony, and freedom Sometimes the emotions affecting us most are not the ones we consciously recognize. And becoming aware of what is really happening underneath can be the beginning of a powerful shift. → Continue Your Self-Healing Journey Listen to the Full Volunteer Self-Healing Session Click here to access today's self-healing session as Brandy Gillmore works directly with Tasha Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops. Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com 

The SE Crew is back from the road—and things are heating up. As wildfires tear through Bigfoot country, reports of strange encounters continue to surface. Are these disasters driving Sasquatch closer to civilization… or forcing them deeper into hiding? Tonight, we follow the smoke and search for answers—on Sasquatch Experience.GET YOUR SASQUATCH EXPERIENCE GEAR FROM THE SQUATCH PRO STORE!Sean Forker hosts SASQUATCH EXPERIENCE, which also features Matt Arner, James Baker, Vance Nesbitt, and Henry May.Creative Consultants: Matt Knapp (Bigfoot Crossroads) & Les Sincavage (Xplorers: Seekers of the Truth). Show Executive Producer: Brian CorbinSpecial Thanks to all our Patreons:The Experiencers: Jeffreylee Matthis, Got Knockers!, Larry Sharpe, Scott Dieterele, and Tom MihokTrackcasters:Cindy BrewerThe Hollers:Gail Frederick, David Hickernell, Matt Arner, Laurie Nelson, and Lori WorthingtonWithout their support, this show would not be possible. For as little as $2 per month, please consider becoming a supporter on PATREON.Our show intro music, “It Comes At Night” by Adam Dib, is licensed to us for commercial use. “9-11 Bigfoot Call” is also used under Fair Use. Sean Forker and Gabriel Forker are credited with the intro and exit voiceover work. Sasquatch Experience Trailer music, “It's in the Fog” by Darren Curtis, is used with permission and attribution. If you'd like to hear a particular topic or guest, EMAIL US! Check us out:Facebook | X | Instagram | SasquatchExperience.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/sasquatch-experience--4208641/support.Sasquatch Experience by Anomalis Entertainment, LLC  is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Based on a work at https://www.spreaker.com/show/sasquatch-experience.Permissions beyond the scope of this license may be available at https://www.sasquatchexperience.com/permission.

There can be many different reasons a child may struggle with appetite or eating. But there is one possible hidden emotional pattern that parents may not always think about, because it can be happening beneath the surface in a way that isn't obvious. In this episode, Brandy shares an insight she has been seeing more and more with children who are having a hard time eating. Sometimes, what looks like "they're just not hungry" may have more happening underneath than it first appears. And in some cases, the way the issue is unfolding emotionally around the child can add another layer without anyone realizing it. In this episode, you'll discover: → One hidden emotional pattern that may affect appetite → Why the issue can become more complicated over time → How the pattern can become unconsciously reinforced without the child or the parents realizing it → What to start noticing beneath the surface → Simple ways to support more safety, connection, and positive emotional patterns The goal is not to blame the child or the parent. It is simply to become more aware of what may be happening underneath. Important Note: There can be many different reasons a child may struggle with appetite or eating, including serious medical conditions and other concerns. If your child is not eating, it is important to FIRST see your doctor or appropriate healthcare professional to rule out other causes. Do not avoid seeing your doctor because of anything you hear in this episode, and do not immediately assume that an eating or appetite issue is stress-related. This episode is intended to provide additional insight and support, but it is not intended to diagnose, treat, or replace appropriate medical care.   Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training.   Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal.   Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops.   Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com 

Bill Atkins put a Mac mini in his spare room so local models can handle the coding chores he would rather skip, all without sending Stylebook's code to the cloud. Bill joins Kotaro, Steve, and Aaron to unpack his setup with OpenCode, Ollama, and Gemma, including SwiftUI migrations, crash-report utilities, RAM limits, and permission guardrails. Bill and The Trio also compare local models with their bigger cloud counterparts, explore Xcode's growing agentic toolkit, and confirm that even LLMs hate Jira.## Chapters00:00 Meet Bill Atkins 01:36 Why Keep AI Local 04:37 From Aider to OpenCode 09:17 Mac mini RAM and Model Choices 14:22 Permissions and Guardrails 17:17 Putting Local Models to Work 19:24 Coding Workflows and Xcode Agents 27:59 Smaller Models, Macros, and Planning 37:14 Cloud Brains and Local Tradeoffs 43:14 Bill Bot and What Comes Next 44:34 One More Thing: Stylebook 45:52 Tag ## Show Notes- Bill has developed Stylebook with his wife since 2009, and the app is entering its seventeenth year.- Keeping Stylebook's proprietary code away from third parties pushed Bill toward local models.- Aider and Devstral proved the idea, but running them meant closing Xcode and Safari on Bill's 32 GB MacBook.- Apple's WWDC26 MLX session inspired a smoother setup with OpenCode, Ollama, and Gemma on a 24 GB Mac mini.- Bill finds Gemma particularly helpful with UIKit and SwiftUI, while smaller models still need tighter prompts and context.- Bill locks down OpenCode so anything beyond safe directory listings and searches requires permission.- A local model built Bill a Mac utility that turns crash reports into symbolicated stack traces.- Aaron explains custom ACP agents in Xcode, while Steve praises its headless builds and improved SwiftUI preview tools.- Swift macros, tests, migrations, and small utilities are ideal jobs when the work is mechanical but worthwhile.- Aaron lands the final verdict after Steve describes Jira's API: even LLMs hate Jira.## Links**Bill's Local AI Setup**Aider: https://aider.chat/ (terminal AI pair programming with local model support)Run local agentic AI on the Mac using MLX: https://developer.apple.com/videos/play/wwdc2026/232/ (WWDC26 session on MLX, OpenCode, Xcode, and multi-Mac scaling)OpenCode: https://opencode.ai/ (open source terminal, desktop, and IDE coding agent)Ollama: https://ollama.com/ (runs and serves open models)Gemma models: https://ai.google.dev/gemma/docs (Google's lightweight open models)**Coding Agents and Workflows**Writing code with intelligence in Xcode: https://developer.apple.com/documentation/xcode/writing-code-with-intelligence-in-xcode (Apple's agentic coding guide)Skills for Real Engineers: https://github.com/mattpocock/skills (Matt Pocock's skills for planning, testing, and debugging)SPS #105, How Alex Hillman Built an AI Assistant with Claude Code: https://podcast.phillycocoa.org/episodes/105-how-alex-hillman-built-an-ai-assistant-with-claude-code (a VPS assistant using Tailscale and safety guardrails)**Notes, Tasks, and Experiments**Obsidian: https://obsidian.md/ (local-first linked notes)Shadertoy: https://www.shadertoy.com/ (create, browse, and share real-time shaders)**Additional Resource**OmniFocus: https://www.omnigroup.com/omnifocus (task management for projects and next actions)**One More Thing**Stylebook: https://www.stylebookapp.com/ (Jess and Bill Atkins' closet app for outfits, value, and wear)**PhillyCocoa:** https://phillycocoa.orgIntro music: "When I Hit the Floor", © 2021 Lorne Behrman. Used with permission of the artist.

An imperfect drink with a perfect story. My reflections from Black Hat USA 2026 An Analog Brain In A Digital Age — A Newsletter by Marco Ciappelli No time to read? Let TAPE3 read it to you.

In recent episodes, we've been exploring some of the more counterintuitive things in healing and personal transformation—the things that can seem positive on the surface, yet sometimes backfire or keep people stuck. And this episode feels like divine timing because the pattern that came up is such a tricky one. So often, people desperately want to help the ones they love the most. They want them to heal. They want them to feel better. They want them to have an incredible life. And it can come from the most genuine, loving place. But what happens when the person you are trying so hard to help begins pulling away? In this short breakthrough episode, Brandy shares an important insight from working with a beautiful volunteer who genuinely wanted the very best for the people she loved. Her intentions were caring. Her heart was in the right place. And yet, without realizing it, the more she tried to help and change the people around her, the more frustration and disconnection began showing up. That is what makes this pattern so easy to miss. In this episode, you'll discover: Why loving intentions can sometimes create an unexpected response How trying to help can become emotionally triggering for both people Why someone may begin pulling away even when your intentions are completely genuine The simple perspective shift that helped Brandy's volunteer see the pattern differently How more love, connection, and understanding can begin changing the dynamic Sometimes the very thing that comes from love can create a result you never intended. And once you see what is really happening underneath, it can completely change the way you approach the people you care about.   → Continue Your Self-Healing Journey Listen to the Full Volunteer Self-Healing Session Click here to access today's self-healing session as Brandy Gillmore works directly with Tasha Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops. Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com   

Surrender can be a well-known recommendation in healing and spirituality. But do you really need to surrender to heal? After so many people were surprised by last week's episode about gratitude, Brandy wanted to explore another healing concept that sounds beautiful on the surface—but may affect the mind very differently depending on what is happening underneath. For some people, surrender may feel peaceful, freeing, and supportive. But for others, the same idea may create a very different emotional response—especially when they are already struggling with fear, uncertainty, health challenges, or feeling powerless in their life. And that raises an important question: What is surrender actually creating within you? In this episode, you'll discover: Why surrender can keep you stuck What may happen when a healing concept creates an unexpected emotional response Why highly driven people can sometimes become internally conflicted around surrender How a seemingly peaceful idea can create a very different experience beneath the surface Why it is important to question even well-known healing concepts and notice how they are affecting your mind What to consider before assuming surrender is always the answer This is not about saying surrender is always bad. It is about understanding what is actually happening inside your mind when you use it. Because something can sound peaceful, spiritual, and healing on the surface—and still create a very different internal experience. And sometimes, understanding that distinction can completely change the way you approach healing and transformation.   Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training.   Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal.   Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops.   Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com 

This may sound surprising—especially because gratitude is so often recommended for healing, happiness, and personal transformation. And to be clear, gratitude can be beautiful. But what happens if someone is carrying deeper feelings of guilt, feeling undeserving of life, love, health, or happiness—and at the same time they are repeatedly bringing in strong feelings of gratitude? That combination may not create the shift they think it is creating. In fact, in some cases, it can actually reinforce the deeper feelings underneath and keep a person stuck. That is exactly what came forward when Brandy recently worked with a beautiful volunteer who had been practicing gratitude and working on herself for years, while also carrying deep guilt from the past. She genuinely wanted to heal and transform. Yet underneath the gratitude was an emotional pattern she had not fully recognized. As Brandy began helping her address what was really happening beneath the surface, the volunteer reported that her neck pain shifted from approximately a level nine to a level two or three. In this episode, you will discover: Why gratitude itself is not the problem How deeper feelings of guilt or undeservingness can change the way a gratitude practice is experienced Why simply placing a positive emotion on top of an unresolved pattern may not create genuine transformation The important distinction Brandy discovered during her own healing journey Why being honest about what is really happening emotionally can be essential for creating real change A more connected emotional state that Brandy began helping her volunteer move toward Brandy also shares how this same realization became important during her own healing journey, when she began questioning many of the practices she had been told were supposed to help. The key is not to stop feeling gratitude. It is to understand what else may be happening underneath it. Because when deeper guilt, undeservingness, or other negative emotional patterns are present, genuine healing may require addressing those patterns rather than simply trying to cover them with something positive. As Brandy says in this episode, we have to be real with what is real to get real results. And sometimes, that means looking beneath even the practices we have always assumed were helping us. → Continue Your Self-Healing Journey Listen to the Full Volunteer Self-Healing Session Click here to access today's self-healing session as Brandy Gillmore works directly with Patricia Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops. Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com   

a16z's Joel De La Garza is joined by Emilio Escobar, Chief Information Security Officer at Datadog, to discuss what it takes to secure a company where nearly every employee is using AI and more than 4,000 engineers are working with coding agents. Rather than trying to block new tools, Emilio explains why Datadog chose to embrace AI early and build the security infrastructure needed to use it safely. They unpack how AI changes traditional assumptions around data permissions, credentials, developer access, and software supply chains. Emilio shares how Datadog uses role-based MCP servers and ephemeral credentials, as well as an AI "judge" built by his security team to evaluate the intent behind code and agent skills before they enter the environment. They also discuss why security teams can't afford to wait for commercial solutions to every new AI threat, how the relationship between developers and security teams needs to change, and why Emilio is less concerned about an AI "escaping" than he is about the sheer volume of vulnerabilities AI could uncover.   Resources: Follow Emilio Escobar on LinkedIn: linkedin.com/in/emilioesc Follow Joel De La Garza on LinkedIn: https://www.linkedin.com/in/3448827723723234/ Follow Datadog on X: https://x.com/datadoghq Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Toxic relationship dynamics can be painful, frustrating, and emotionally exhausting. But what if some of the most important patterns affecting those relationships are happening beneath the surface? In this episode, Brandy shares three powerful insights to help you look at toxic relationship patterns differently—and begin recognizing what may need to shift at a deeper level. Because sometimes the obvious problem is only part of the story. There may also be underlying feelings of powerlessness, rejection, guilt, insecurity, sensitivity, or emotional reactiveness that continue influencing the way a relationship feels and unfolds. In this episode, you will discover: Three hidden emotional patterns that may be affecting difficult relationships Why fear of rejection or abandonment can create feelings of powerlessness How emotional reactiveness can unintentionally keep conflict going Why feeling deserving of better can be an important part of creating change The important difference between anger and genuine strength Why using anger to access your power can create additional problems How confidence, wisdom, and self-worth can help create a healthier internal shift Why transforming yourself can sometimes change the entire relationship dynamic This is not about overlooking harmful behavior, abandoning healthy boundaries, or pretending painful experiences did not happen. Sometimes, removing a person from your life is absolutely necessary. But removing a person and transforming the emotional pattern are not always the same thing. When you begin identifying what is truly underneath the pattern, you may be able to create a much deeper level of healing, freedom, strength, and change. Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops.   Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com   

AI isn't just transforming the way we work, but also the way we write the software that people use for work. In this episode, we talk to two engineering productivity leads at Dropbox: Uma Namasivayam, senior director of software engineering productivity, and Anuradha Agarwal, director of software engineering. Whether it's writing tests, fixing bugs, tackling tech debt, or accelerating migrations, they explain how Dropbox engineers are using agentic AI—including in-house tools like Nova—to build the future of Dropbox, and create more space to do impactful work. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Hannah Richell on Writing Memoir, Grief, and An Ocean and a Day Join host and author Pamela Cook as she interviews author Hannah Richell about her memoir An Ocean and a Day, which explores the sudden death of her husband Matt in a surfing accident at Tamarama Beach in 2014 and the long journey of grief that followed. Richell discusses journaling as a survival tool, shaping years of writing into a memoir, and choosing a circular, tidal structure that moves between past and present to show what was lost and reflect how grief is experienced. She shares key influences and also talks about narrating the audiobook herself, deciding what to include about her children, and how touring and reader responses have been unexpectedly uplifting. 00:00 Level Up Writing Courses 01:39 Episode Updates and Memoir Intro 05:15 Memoir Overview and Loss 08:38 Beach Bookends and Ending 13:22 Writing Grief Into Words 17:30 Tidal Timeline Structure 24:02 Journaling to Memoir Draft2 9:38 Visitation Dream Story 32:56 Host Family Grief Reflection 36:42 Kids as Anchors 38:05 Writing Through Nights 38:42 Books That Held Me 42:34 Quoting and Permissions 44:18 Narrating the Audiobook 49:10 Shaping the Memoir 50:51 Privacy and Boundaries 56:20 Swallows and Tattoos 01:00:27 Touring and Reader Connection 01:03:39 Wrap Up and Farewell SHOWNOTES: Writes4Women www.writes4women.com Facebook @writes4women Twitter / Instagram @w4wpodcast W4W Substack Click here Hannah Richell Website: click here Facebook: click here Instagram: click here Pamela Cook www.pamelacook.com.au Facebook @amelacookauthor Twitter @PamelaCookAU This episode produced by Pamela Cook for Writes4Women and recorded on unceded Dharawal land. Support the show: https://www.patreon.com/writes4women?fan_landing=trueSee omnystudio.com/listener for privacy information.

What if the most obvious relationship problem is not the deepest pattern keeping you stuck? In this powerful episode, Brandy shares breakthrough insights from working with a beautiful volunteer named Michael—a loving husband, devoted father, firefighter, and genuinely caring man who wanted to become the best version of himself. Yet beneath his strength and kindness was an emotional pattern that had continued showing up in different relationships and different areas of his life. Michael had experienced painful dynamics with parents, friends, and other people he cared about. At times, the hurt became so frustrating that shutting people out felt like the only way to protect himself. But as Brandy looked more deeply, it became clear that ending the relationship did not necessarily end the pattern. There was something underneath it that had continued affecting the way Michael saw other people, the way he saw himself, and what he felt he deserved in life. In this episode, you will discover: Why leaving a toxic relationship may not automatically transform the emotional pattern How childhood experiences can continue showing up in completely different relationships Why judgment toward others can quietly become judgment toward yourself How guilt and feelings of undeservingness may create invisible self-sabotage Why loyalty, hurt, and resentment can become emotionally intertwined What to look for when the same relationship experience keeps repeating How to begin identifying the deeper pattern beneath the people involved This is not about overlooking harmful behavior, abandoning healthy boundaries, or pretending that painful experiences did not happen. Sometimes, removing a person from your life is absolutely necessary. But removing a person and transforming the emotional pattern are not always the same thing. When you begin identifying what is truly underneath the pattern, you may be able to create a much deeper level of healing, freedom, and change. → Continue Your Self-Healing Journey Listen to the Full Volunteer Self-Healing Session Click here to access today's self-healing session as Brandy Gillmore works directly with Michael Free Mind-Body Healing Training If you'd like a deeper understanding of mind-body healing and how self-healing works: Click here to join the FREE training. Brandy Gillmore's Mind-Body Healing: Scientific Research If you'd like scientific research on mind-body healing, you can view Brandy Gillmore's work published in a Medical Journal. Personal Empowerment and Self-Healing Courses If you're ready to heal yourself and change your life: Click here to explore our GIFT Mind-Body Healing™ and the GIFT Method™ Courses and GIFT Workshops. Connect With Brandy Follow Brandy on Facebook Follow Brandy on Instagram Questions? Discover more at https://brandygillmore.com or email support@BrandyGillmore.com   Important Note: This podcast is for educational and informational purposes only and is not a replacement for medical advice, diagnosis, or treatment. Please continue to consult your doctor or qualified healthcare provider as recommended. Click here to view our full disclaimer- https://brandygillmore.com/terms/. © Brandy Gillmore / Human Potential Revolution, Inc. All Rights Reserved. This podcast and all related content are provided solely for personal, noncommercial use. No portion may be copied, recorded, transcribed, closely paraphrased, adapted, repackaged, distributed, taught, or used to create or support any course, coaching program, training, certification, product, service, or derivative content without prior written permission. This content may not be uploaded to, entered into, stored in, used by, or incorporated into any artificial-intelligence, machine-learning, voice-cloning, digital-replica, data-training, or related system. By accessing, listening to, viewing, downloading, or otherwise using this content, you agree to our Intellectual Property and Content Use Terms. If you do not agree, do not access or use the content. Full Terms: https://brandygillmore.com/content-terms  Permissions: support@brandygillmore.com   

Mike Hartman, Ohio Bigfoot Investigator, joins Sean and Matt to discuss some of his research and "The Bigfoot App." https://www.thebigfootapp.comPLEASE LIKE, SUBSCRIBE, RATE, AND REVIEW ON ALL PLATFORMS: YouTube, Facebook, Apple Podcasts, Spotify, Spreaker, or wherever you listen!GET YOUR SASQUATCH EXPERIENCE GEAR FROM THE SQUATCH PRO STORE!Sean Forker hosts SASQUATCH EXPERIENCE, which also features Matt Arner, James Baker, Vance Nesbitt, and Henry May.Creative Consultants: Matt Knapp (Bigfoot Crossroads) & Les Sincavage (Xplorers: Seekers of the Truth). Show Executive Producer: Brian CorbinSpecial Thanks to all our Patreons:The Experiencers: Jeffreylee Matthis, Got Knockers!, Larry Sharpe, Scott Dieterele, and Tom MihokTrackcasters:Cindy BrewerThe Hollers:Gail Frederick, David Hickernell, Matt Arner, Laurie Nelson, and Lori WorthingtonWithout their support, this show would not be possible. For as little as $2 per month, please consider becoming one of our supporters on PATREON.Our show intro music, “It Comes At Night” by Adam Dib, is licensed to us for commercial use. “9-11 Bigfoot Call” is also used under Fair Use. Sean Forker and Gabriel Forker are credited with the intro and exit voiceover work. Sasquatch Experience Trailer music, “It's in the Fog” by Darren Curtis, is used with permission and attribution. If you'd like to hear a particular topic or guest, EMAIL US! Check us out:Facebook | X | Instagram | SasquatchExperience.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/sasquatch-experience--4208641/support.Sasquatch Experience by Anomalis Entertainment, LLC  is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Based on a work at https://www.spreaker.com/show/sasquatch-experience.Permissions beyond the scope of this license may be available at https://www.sasquatchexperience.com/permission.

Today's Sponsors: https://iCatholicMobile.com Visit iCatholicMobile.com and switch to a faithful Catholic phone coverage or call 802-988-6588 Real Estate for Life: https://realestateforlife.org/ (and select "Dr. Taylor Marshall Show") https://nsti.com/checkout/?rid=pJNK69 This is the NSTI discount link to receive your $1 jump start at New Saint Thomas Institute for your Catholic Bible in a Year, Catholic Bible Cheat Sheet, and Catholic Lifetime Reading List and 10 Catholic Courses from Dr. Taylor Marshall. Learn more about your ad choices. Visit megaphone.fm/adchoices

AI makes it easier than ever to find and act on information—especially now that teams can connect to and search across all the apps they use for work. So how do you ensure that only the right people and the right tools can access your team's most sensitive content? In this episode, we talk with Jess Jimenez, the head of security at Dropbox, about what security looks like in the age of AI at Dropbox-scale—from building AI products securely to building trust with the people who use them. Jess talks about the importance of access control lists, defending against the latest AI threats, and how Dropbox Protect helps teams securely share content with both humans and AI so they can collaborate more safely. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Have you ever thought, I'd love to start a podcast... but who would listen to me? If so, you're not alone. I share the story behind launching Plucky Not Perfect, despite being shy, hating the sound of my own voice, and wondering if I'd have anything worthwhile to say. Forty-four episodes later, I'm looking back at what it really took to begin. This isn't a technical guide to podcasting. It's a pep talk for anyone sitting on a creative dream. Whether you're considering starting a podcast, writing a book, launching a business, or simply sharing your voice more boldly, these six "permission slips" will help you move from fear to action. In this episode, you'll learn: Why you don't have to feel ready before you begin. How accountability and community can help you overcome procrastination. Why every creator needs permission to be a beginner. How to define success on your own terms. Why it's okay (and healthy) for your creative work to evolve over time. The mindset shift that helps quiet your inner critic. Why courage matters more than confidence. Books & Resources Mentioned Teri Holland's 5-Day Launch Your Podcast Challenge  The Artist's Way by Julia Cameron (for quieting your inner critic) The Run Like A Girl Podcast | hosted by Courtney McQueen  If this episode inspires you to start a podcast or any creative project, I would love to hear from you. Reach out with your questions, ideas, or fears. You don't have to figure it all out alone. Instagram: @carriejobradley Email: thecarriejobradley@gmail.com

Most of what's stopping you from going after what you really want isn't coming from outside. It's coming from inside. And according to Liz M. Lopez, executive coach, bestselling author, and speaker with 19 years of coaching experience, it comes down to permission.Candy sits down with Liz to talk about the seven permissions framework she developed after nearly two decades of watching brilliant leaders lock themselves in a fortress of their own making. Permission to fail. Permission to be supported. Permission to take baby steps. Permission to feel confident today exactly as you are. Permission to prosper. Permission to walk away. And finally, permission to succeed.They talk about why fear is the foundational self-sabotage underneath almost everything, how job hurt and career trauma create invisible rules that run people's lives for decades without them even knowing it, and why asking for support isn't weakness but one of the most strategic things an ambitious person can do.Liz also talks honestly about living the framework herself, catching herself making decisions from fear instead of strategy, and why after seven years of writing this book, she still considers herself a student of the work, not its master.Warm, honest, and deeply practical this is a must listen episode.Grab the free course, Stop Guessing and Start Signing Clients, and start building a coaching business that's actually yours: https://candymotzek.lpages.co/vfo/Want to see what's actually working for coaches right now? Download the free Coaching Business Insights Report 2026: https://candymotzek.lpages.co/business-growth-survey/Ready to work with a coach? Book a free 30 minute call: https://stepintosuccessnow.com/

Most motion designers add sound design at the very end of a project. But Joe Basile, aka The Chicken, says it should start at the very beginning. And once you hear why, the sequencing is hard to unsee.In this episode of the Styleframe Saturdays podcast, we sit down with award-winning sound designer and composer Joe Basile to explore what happens when audio and motion design collide from the very beginning of a project. Joe breaks down and reveals the sonic philosophy behind his Favorite Mix, including a technique borrowed directly from The Shawshank Redemption to transition music from non-diegetic to diegetic sound.From finding rhythm hidden inside an animation before a single note is played, to knowing exactly when to bring a sound designer into the room, this conversation will shift how you hear your own work.TIMESTAMPS:0:00 – Intro0:37 – Meet Joe Basile: The Chicken16:25 – Original Music vs. Sound Design vs. Sonic Branding21:52 – The Favorite Mix: Crack by Johan Eriksson23:55 – The Shawshank Technique: Diegetic vs. Non-diegetic Music28:53 – How the Attention Economy is Changing Audio Storytelling37:50 – When Should You Bring Sound Design into a Project?40:14 – The "Demo Love" Trap Explained43:23 – Pareidolia: Finding Rhythm Inside Animation53:54 – The Noise Experiment That Won a Motion Award57:03 – Challenges & Rewards58:43 – Favorite Mix Because…CONNECT & FOLLOW:Spotify → https://spoti.fi/3K8UDd7Apple Podcasts → https://podcasts.apple.com/us/podcast/styleframe-saturdays/id1607658120Amazon Music → https://amzn.in/d/0cziMYRNGUEST LINKS/RESOURCES:Joe Basile's Website: https://www.thechicken.net/Cool Edit Pro: https://en.wikipedia.org/wiki/Adobe_AuditionWestern Carolina University: https://www.wcu.edu/Antfood: https://www.antfood.com/Source Connect: https://www.source-elements.com/products/source-connect/Johan Eriksson: https://johaneriksson.co/?utm_source=ig&utm_medium=social&utm_content=link_in_bio&fbclid=PAZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQPOTM2NjE5NzQzMzkyNDU5AAGnZzqyQomWzFCGInTeGkPJXMyxvK1dW26vWkVEuKsbTS4TNliMfUxpr1jxcvE_aem_FABFZpaZ4jop-TJJ4FmaiA“Crack” by Johan Eriksson: https://johaneriksson.co/?utm_source=ig&utm_medium=social&utm_content=link_in_bio&fbclid=PAZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQPOTM2NjE5NzQzMzkyNDU5AAGnZzqyQomWzFCGInTeGkPJXMyxvK1dW26vWkVEuKsbTS4TNliMfUxpr1jxcvE_aem_FABFZpaZ4jop-TJJ4FmaiAThe Shawshank Redemption: https://johaneriksson.co/?utm_source=ig&utm_medium=social&utm_content=link_in_bio&fbclid=PAZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQPOTM2NjE5NzQzMzkyNDU5AAGnZzqyQomWzFCGInTeGkPJXMyxvK1dW26vWkVEuKsbTS4TNliMfUxpr1jxcvE_aem_FABFZpaZ4jop-TJJ4FmaiASteve Reich: https://stevereich.com/“It's Gonna Rain” (1965) by Steve Reich: https://stevereich.com/composition/its-gonna-rain/Hannah Churn: https://www.hannahchurn.com/Todd Churn: https://toddchurn.com/“Night Lights” by Hannah & Todd Churn: https://nightlights.tv/“The Breakout” by Mantas GR: https://mantasgr.com/the-breakoutAdobe Photoshop: https://photoshop.adobe.com/?promoid=HHJ4XB3V&mv=other&mv2=ahome&lang=enAdobe After Effects: https://www.adobe.com/products/aftereffects.html*Riverside: https://riverside.fm/?utm_campaign=campaign_1&utm_medium=affiliate&utm_source=rewardful&via=styleframesatLofi Cassette by Harrison Amer (theme music licensed by Premiumbeat.com, https://www.premiumbeat.com/home)Permissions granted by the artist(s).Our podcast celebrates Motion Ideation — the raw brainstorming, early-stage thinking and lightbulb moments that shape everything before a single design or keyframe exists. Because we believe great motion design starts with one Favorite Frame™ and the fresh ideas behind it.Styleframe Saturdays is a Formerle-branded podcast, and part of the Formerle brand family.*By making a purchase through one of our affiliate links we will get a small commission at no additional cost to you. Rest assured that we would recommend these products regardless of their commission-based opportunities.

Not all work happens in writing. Teams that work with photos, videos, and audio need AI that works for them too. This is why, with Dropbox, you can search within multimedia content for key moments and important information—not just text. In this episode, we talk with Appu Shaji and Hicham Badri, two Dropbox machine learning engineers who are part of the team that makes all of this possible. They explain how multimodal search works—from understanding the context of the initial query, to identifying objects and actions in complex scenes—and how they ensure those models work fast, even at Dropbox-scale. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Wisconsin Bigfoot Researcher Dan Nedrelo joins us to talk Bigfoot, Herpetology, and more...PLEASE LIKE, SUBSCRIBE, RATE, AND REVIEW ON ALL PLATFORMS: YouTube, Facebook, Apple Podcasts, Spotify, Spreaker, or wherever you listen!GET YOUR SASQUATCH EXPERIENCE GEAR FROM THE SQUATCH PRO STORE!Sean Forker hosts SASQUATCH EXPERIENCE, which also features Matt Arner, James Baker, Vance Nesbitt, and Henry May.Creative Consultants: Matt Knapp (Bigfoot Crossroads) & Les Sincavage (Xplorers: Seekers of the Truth). Show Executive Producer: Brian CorbinSpecial Thanks to all our Patreons:The Experiencers: Jeffreylee Matthis, Got Knockers!, Larry Sharpe, Scott Dieterele, and Tom MihokTrackcasters: Cindy BrewerThe Hollers: Gail Frederick, David Hickernell, Matt Arner, Laurie Nelson, and Lori WorthingtonWithout their support, this show would not be possible. For as little as $2 per month, please consider becoming one of our supporters on PATREON.Our show intro music, “It Comes At Night” by Adam Dib, is licensed to us for commercial use. “9-11 Bigfoot Call” is also used under Fair Use. Sean Forker and Gabriel Forker are credited with the intro and exit voiceover work. Sasquatch Experience Trailer music, “It's in the Fog” by Darren Curtis, is used with permission and attribution. If you'd like to hear a particular topic or guest, EMAIL US! Check us out:Facebook | X | Instagram | SasquatchExperience.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/sasquatch-experience--4208641/support.Sasquatch Experience by Anomalis Entertainment, LLC  is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Based on a work at https://www.spreaker.com/show/sasquatch-experience.Permissions beyond the scope of this license may be available at https://www.sasquatchexperience.com/permission.

Episode 20 — You Can Choose What You KeepA gentle reminder that not everything in your life is yours to carry. In this episode, we explore the difference between intentional responsibility and unconscious weight — and how choosing what to keep is one of the most loving things you can do for yourself.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━SHOW NOTES━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━TIMESTAMPS[00:00] Opening — What Have You Been Carrying?[01:30] Settling In — Breathing and Arriving[03:00] The Theme Part 1 — What You've Been Carrying[05:30] The Theme Part 2 — Choosing with Intention[07:30] Breathwork — Setting It Down[09:00] Affirmations Part 1 — Permissions[10:00] Affirmations Part 2 — Releasing[11:00] Closing — You Get to Choose━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━EPISODE SUMMARYWe carry so much — expectations, guilt, worry, other people's feelings — and most of it was never ours to hold. This episode explores the quiet power of choosing what you keep. Not everything that enters your life deserves to stay. Not every thought needs your attention. You get to decide what fills your heart and your mind. And that choosing? It's not selfish. It's wisdom.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━AFFIRMATIONS• I am allowed to choose what I carry.• Not everything that comes my way is mine to hold.• I can love people and still have boundaries.• I can care deeply and still protect my peace.• My energy is not unlimited, and that is not a flaw.• I release what is not mine.• I trust myself to know the difference.• I am not responsible for everyone's feelings.• I can hold compassion without holding the weight.• My peace matters. My rest matters. My space matters.• I choose to fill my life with what nourishes me, not what drains me.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━HOSTYour Quiet Moment — A pocket of calm in your day.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━TOPICS• Intentional living• Emotional boundaries• Letting go of what isn't yours• Self-respect and self-compassion• Choosing peace over obligation━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━If this episode helped you breathe a little easier, follow Your Quiet Moment so you never miss a moment of peace. Share it with someone who needs to hear it today.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━DISCLAIMERThis podcast is for informational and inspirational purposes only. It is not a substitute for professional mental health advice, diagnosis, or treatment. If you are struggling, please reach out to a qualified professional. You matter, and help is available.DISCLAIMER

Interview with Sandy Bird, co-founder of Sonrai Security In this week's interview, we kick off the conversation with how Sonrai's expertise in securing cloud identity permissions had the company well placed to address the explosion of AI agents and the clear risks they represented. On the surface, this looks like a cloud/hyperscaler permissions challenge, but it isn't that simple. As agents like Claude Code, Codex, and Hermes are connected to enterprise cloud agents, the risk spreads outside VPCs and onto endpoints. Check out the episode to learn more about some of the most common risks Sandy finds and how Sonrai goes about addressing them. This segment is sponsored by Sonrai Security. Visit https://securityweekly.com/sonrai to learn more about them! Segment Resources AWS Bedrock agent permissions: what you need to lock down before you go live Making Enterprise AI Agents Accountable with Amir Ofek, CEO and Co-Founder of aizome Organizations looking to unlock the power of Enterprise AI Agents, and in a controlled and safe way at the speed of AI. Identity is at the heart of it. However, NHI Governance Is Not Enough for Enterprise AI Agents. The identity industry has responded to the rise of AI agents the same way it responds to every new identity challenge: extend existing frameworks. Map agents to human owners. Enforce least privilege. Govern them like non-human identities. It is a reasonable instinct. It is also insufficient in ways that matter enormously. Non-human identity security was built for a deterministic world - service accounts, API keys, bots. These identities do what they are configured to do. Their behavior is predictable enough that static governance models work. Enterprise AI agents are categorically different. Not in degree - in kind. They don't execute fixed instructions. They reason, plan, and adapt in response to context. Their scope shifts with every task. Their behavior at runtime can diverge significantly from anything true at provisioning time. Unlike any identity that came before them, they frequently change their intent, at a pace no governance model built for human movers or machine credentials was designed to handle. Wrapping them in the same framework you use for a service account isn't wrong. It's just insufficient in precisely the places where risk accumulates. Download the SANS AI Security Maturity Model eBook This segment is sponsored by aizome. Visit https://securityweekly.com/aizomeidv to learn more about them! The Human Authorized. The Agent Acted. Who's Accountable? Interview with Howard Ting - CEO - Opal Security A self-driving car still has a license plate The accountability didn't change just because the driver did. The same has to be true for AI agents, but most environments can't trace an agent action back through the layers of delegation to the human who authorized it. Howard Ting, CEO of Opal Security, joins Security Weekly to discuss what the accountability model looks like when employees run swarms of agents, and what has to be in place before that accountability chain is tested. https://www.opal.dev/resource-center/identity-governance-report-2026-ai-access This segment is sponsored by Opal Security. Visit https://securityweekly.com/opalidv to learn more about them! Next Evolution of Identity Security: AI for Lower Cost, Efficiency & Governance with Ajay Gupta - President & CEO - SDG Organizations have invested heavily in identity platforms, but many still struggle to maximize security, efficiency, and governance outcomes. As AI transforms both cyber defense and cyber threats, Identity Security is emerging as a critical foundation for securing human and non-human identities alike. In this discussion, we explore how AI is helping organizations reduce costs, improve operations, defend against AI-powered attacks, and address the governance challenges created by AI agents—highlighting the convergence of Identity Security, AI Security, and AI Governance. This segment is sponsored by SDG. Visit https://securityweekly.com/sdgidv to learn more about them! Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-466

Interview with Sandy Bird, co-founder of Sonrai Security In this week's interview, we kick off the conversation with how Sonrai's expertise in securing cloud identity permissions had the company well placed to address the explosion of AI agents and the clear risks they represented. On the surface, this looks like a cloud/hyperscaler permissions challenge, but it isn't that simple. As agents like Claude Code, Codex, and Hermes are connected to enterprise cloud agents, the risk spreads outside VPCs and onto endpoints. Check out the episode to learn more about some of the most common risks Sandy finds and how Sonrai goes about addressing them. This segment is sponsored by Sonrai Security. Visit https://securityweekly.com/sonrai to learn more about them! Segment Resources AWS Bedrock agent permissions: what you need to lock down before you go live Making Enterprise AI Agents Accountable with Amir Ofek, CEO and Co-Founder of aizome Organizations looking to unlock the power of Enterprise AI Agents, and in a controlled and safe way at the speed of AI. Identity is at the heart of it. However, NHI Governance Is Not Enough for Enterprise AI Agents. The identity industry has responded to the rise of AI agents the same way it responds to every new identity challenge: extend existing frameworks. Map agents to human owners. Enforce least privilege. Govern them like non-human identities. It is a reasonable instinct. It is also insufficient in ways that matter enormously. Non-human identity security was built for a deterministic world - service accounts, API keys, bots. These identities do what they are configured to do. Their behavior is predictable enough that static governance models work. Enterprise AI agents are categorically different. Not in degree - in kind. They don't execute fixed instructions. They reason, plan, and adapt in response to context. Their scope shifts with every task. Their behavior at runtime can diverge significantly from anything true at provisioning time. Unlike any identity that came before them, they frequently change their intent, at a pace no governance model built for human movers or machine credentials was designed to handle. Wrapping them in the same framework you use for a service account isn't wrong. It's just insufficient in precisely the places where risk accumulates. Download the SANS AI Security Maturity Model eBook This segment is sponsored by aizome. Visit https://securityweekly.com/aizomeidv to learn more about them! The Human Authorized. The Agent Acted. Who's Accountable? Interview with Howard Ting - CEO - Opal Security A self-driving car still has a license plate The accountability didn't change just because the driver did. The same has to be true for AI agents, but most environments can't trace an agent action back through the layers of delegation to the human who authorized it. Howard Ting, CEO of Opal Security, joins Security Weekly to discuss what the accountability model looks like when employees run swarms of agents, and what has to be in place before that accountability chain is tested. https://www.opal.dev/resource-center/identity-governance-report-2026-ai-access This segment is sponsored by Opal Security. Visit https://securityweekly.com/opalidv to learn more about them! Next Evolution of Identity Security: AI for Lower Cost, Efficiency & Governance with Ajay Gupta - President & CEO - SDG Organizations have invested heavily in identity platforms, but many still struggle to maximize security, efficiency, and governance outcomes. As AI transforms both cyber defense and cyber threats, Identity Security is emerging as a critical foundation for securing human and non-human identities alike. In this discussion, we explore how AI is helping organizations reduce costs, improve operations, defend against AI-powered attacks, and address the governance challenges created by AI agents—highlighting the convergence of Identity Security, AI Security, and AI Governance. This segment is sponsored by SDG. Visit https://securityweekly.com/sdgidv to learn more about them! Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw-466

Interview with Sandy Bird, co-founder of Sonrai Security In this week's interview, we kick off the conversation with how Sonrai's expertise in securing cloud identity permissions had the company well placed to address the explosion of AI agents and the clear risks they represented. On the surface, this looks like a cloud/hyperscaler permissions challenge, but it isn't that simple. As agents like Claude Code, Codex, and Hermes are connected to enterprise cloud agents, the risk spreads outside VPCs and onto endpoints. Check out the episode to learn more about some of the most common risks Sandy finds and how Sonrai goes about addressing them. This segment is sponsored by Sonrai Security. Visit https://securityweekly.com/sonrai to learn more about them! Segment Resources AWS Bedrock agent permissions: what you need to lock down before you go live Making Enterprise AI Agents Accountable with Amir Ofek, CEO and Co-Founder of aizome Organizations looking to unlock the power of Enterprise AI Agents, and in a controlled and safe way at the speed of AI. Identity is at the heart of it. However, NHI Governance Is Not Enough for Enterprise AI Agents. The identity industry has responded to the rise of AI agents the same way it responds to every new identity challenge: extend existing frameworks. Map agents to human owners. Enforce least privilege. Govern them like non-human identities. It is a reasonable instinct. It is also insufficient in ways that matter enormously. Non-human identity security was built for a deterministic world - service accounts, API keys, bots. These identities do what they are configured to do. Their behavior is predictable enough that static governance models work. Enterprise AI agents are categorically different. Not in degree - in kind. They don't execute fixed instructions. They reason, plan, and adapt in response to context. Their scope shifts with every task. Their behavior at runtime can diverge significantly from anything true at provisioning time. Unlike any identity that came before them, they frequently change their intent, at a pace no governance model built for human movers or machine credentials was designed to handle. Wrapping them in the same framework you use for a service account isn't wrong. It's just insufficient in precisely the places where risk accumulates. Download the SANS AI Security Maturity Model eBook This segment is sponsored by aizome. Visit https://securityweekly.com/aizomeidv to learn more about them! The Human Authorized. The Agent Acted. Who's Accountable? Interview with Howard Ting - CEO - Opal Security A self-driving car still has a license plate The accountability didn't change just because the driver did. The same has to be true for AI agents, but most environments can't trace an agent action back through the layers of delegation to the human who authorized it. Howard Ting, CEO of Opal Security, joins Security Weekly to discuss what the accountability model looks like when employees run swarms of agents, and what has to be in place before that accountability chain is tested. https://www.opal.dev/resource-center/identity-governance-report-2026-ai-access This segment is sponsored by Opal Security. Visit https://securityweekly.com/opalidv to learn more about them! Next Evolution of Identity Security: AI for Lower Cost, Efficiency & Governance with Ajay Gupta - President & CEO - SDG Organizations have invested heavily in identity platforms, but many still struggle to maximize security, efficiency, and governance outcomes. As AI transforms both cyber defense and cyber threats, Identity Security is emerging as a critical foundation for securing human and non-human identities alike. In this discussion, we explore how AI is helping organizations reduce costs, improve operations, defend against AI-powered attacks, and address the governance challenges created by AI agents—highlighting the convergence of Identity Security, AI Security, and AI Governance. This segment is sponsored by SDG. Visit https://securityweekly.com/sdgidv to learn more about them! Show Notes: https://securityweekly.com/esw-466

Interview with Sandy Bird, co-founder of Sonrai Security In this week's interview, we kick off the conversation with how Sonrai's expertise in securing cloud identity permissions had the company well placed to address the explosion of AI agents and the clear risks they represented. On the surface, this looks like a cloud/hyperscaler permissions challenge, but it isn't that simple. As agents like Claude Code, Codex, and Hermes are connected to enterprise cloud agents, the risk spreads outside VPCs and onto endpoints. Check out the episode to learn more about some of the most common risks Sandy finds and how Sonrai goes about addressing them. This segment is sponsored by Sonrai Security. Visit https://securityweekly.com/sonrai to learn more about them! Segment Resources AWS Bedrock agent permissions: what you need to lock down before you go live Making Enterprise AI Agents Accountable with Amir Ofek, CEO and Co-Founder of aizome Organizations looking to unlock the power of Enterprise AI Agents, and in a controlled and safe way at the speed of AI. Identity is at the heart of it. However, NHI Governance Is Not Enough for Enterprise AI Agents. The identity industry has responded to the rise of AI agents the same way it responds to every new identity challenge: extend existing frameworks. Map agents to human owners. Enforce least privilege. Govern them like non-human identities. It is a reasonable instinct. It is also insufficient in ways that matter enormously. Non-human identity security was built for a deterministic world - service accounts, API keys, bots. These identities do what they are configured to do. Their behavior is predictable enough that static governance models work. Enterprise AI agents are categorically different. Not in degree - in kind. They don't execute fixed instructions. They reason, plan, and adapt in response to context. Their scope shifts with every task. Their behavior at runtime can diverge significantly from anything true at provisioning time. Unlike any identity that came before them, they frequently change their intent, at a pace no governance model built for human movers or machine credentials was designed to handle. Wrapping them in the same framework you use for a service account isn't wrong. It's just insufficient in precisely the places where risk accumulates. Download the SANS AI Security Maturity Model eBook This segment is sponsored by aizome. Visit https://securityweekly.com/aizomeidv to learn more about them! The Human Authorized. The Agent Acted. Who's Accountable? Interview with Howard Ting - CEO - Opal Security A self-driving car still has a license plate The accountability didn't change just because the driver did. The same has to be true for AI agents, but most environments can't trace an agent action back through the layers of delegation to the human who authorized it. Howard Ting, CEO of Opal Security, joins Security Weekly to discuss what the accountability model looks like when employees run swarms of agents, and what has to be in place before that accountability chain is tested. https://www.opal.dev/resource-center/identity-governance-report-2026-ai-access This segment is sponsored by Opal Security. Visit https://securityweekly.com/opalidv to learn more about them! Next Evolution of Identity Security: AI for Lower Cost, Efficiency & Governance with Ajay Gupta - President & CEO - SDG Organizations have invested heavily in identity platforms, but many still struggle to maximize security, efficiency, and governance outcomes. As AI transforms both cyber defense and cyber threats, Identity Security is emerging as a critical foundation for securing human and non-human identities alike. In this discussion, we explore how AI is helping organizations reduce costs, improve operations, defend against AI-powered attacks, and address the governance challenges created by AI agents—highlighting the convergence of Identity Security, AI Security, and AI Governance. This segment is sponsored by SDG. Visit https://securityweekly.com/sdgidv to learn more about them! Show Notes: https://securityweekly.com/esw-466

Sean Forker and Crew are back in action, discussing the topics pressing in the Bigfoot world. PLEASE LIKE, SUBSCRIBE, RATE, AND REVIEW ON ALL PLATFORMS: YouTube, Facebook, Apple Podcasts, Spotify, Spreaker, or wherever you listen!GET YOUR SASQUATCH EXPERIENCE GEAR FROM THE SQUATCH PRO STORE!Sean Forker hosts SASQUATCH EXPERIENCE, which also features Matt Arner, James Baker, Vance Nesbitt, and Henry May.Creative Consultants: Matt Knapp (Bigfoot Crossroads) & Les Sincavage (Xplorers: Seekers of the Truth). Show Executive Producer: Brian CorbinSpecial Thanks to all our Patreons:The Experiencers: Jeffreylee Matthis, Got Knockers!, Larry Sharpe, Scott Dieterele, and Tom MihokTrackcasters: Cindy BrewerThe Hollers: Gail Frederick, David Hickernell, Matt Arner, Laurie Nelson, and Lori WorthingtonWithout their support, this show would not be possible. For as little as $2 per month, please consider becoming one of our supporters on PATREON.Our show intro music, “It Comes At Night” by Adam Dib, is licensed to us for commercial use. “9-11 Bigfoot Call” is also used under Fair Use. Sean Forker and Gabriel Forker are credited with the intro and exit voiceover work. Sasquatch Experience Trailer music, “It's in the Fog” by Darren Curtis, is used with permission and attribution. If you'd like to hear a particular topic or guest, EMAIL US! Check us out:Facebook | X | Instagram | SasquatchExperience.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/sasquatch-experience--4208641/support.Sasquatch Experience by Anomalis Entertainment, LLC  is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Based on a work at https://www.spreaker.com/show/sasquatch-experience.Permissions beyond the scope of this license may be available at https://www.sasquatchexperience.com/permission.

When AI is at its best, the conversations can feel uncanny—almost magical in their accuracy, relevance, and speed. For that you can thank the AI agents that work together behind the scenes to search, reason, and sift through all your content to get you what you need to do your job. We talk with Jongmin Baek and Marta Mendez, two Dropbox machine learning engineers, about building conversational AI that's helpful, useful, and grounded in your team's shared context, so you can spend more time on the work that really matters. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

AI isn't necessarily creating impossible new attacks, but it is drastically lowering the technical barrier to entry for cybercriminals. In this episode, Ashish Rajan speaks with Simon Biggs, Cyber Incident Response Specialist at Varonis, about how AI is accelerating the attack lifecycle. Simon explains how attackers are using AI kits to instantly set up ephemeral phishing portals, query SQL databases in minutes, and bypass AI guardrails to compile Remote Access Trojans (RATs). We also discuss the shift in ransomware tactics from "encryption-first" to "data-theft-first," and how AI empowers attackers to post-process terabytes of stolen data to monetize it in novel ways. For defenders, the message is clear: if your S3 access logs and SQL transaction logs aren't turned on before a breach, your forensics team won't be able to tell lawyers or regulators what data was actually lost. Discover why data classification and proactive logging are the ultimate lifelines for IR teams in the AI age. Guest Socials -⁠⁠ ⁠⁠⁠⁠Simon's Linkedin Podcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you are interested in AI Security, you can check out our sister podcast -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AI Security Podcast⁠Questions asked:(00:00) Introduction(02:00) Simon Biggs' Background in Law Enforcement and Varonis(03:10) Is There a Huge Volume of Sophisticated AI Attacks?(04:10) How AI Accelerates SQL Queries and Business Email Compromise (BEC)(05:15) Why AI Kits Are the New Metasploit and BloodHound(08:15) Varonis Threat Labs: Copilot Prompt Injection Vulnerability(09:20) The Forensic Challenge: Auditing Prompts vs. Understanding AI Output(10:30) Tricking AI Guardrails to Compile Malware(12:15) Defensive Strategies: Shadow AI, Permissions, and Logging(15:30) Using Defensive AI and BloodHound for Threat Hunting(17:30) Why Ransomware is Now "Data First, No Encryption"(20:50) The Legal Nightmare of Unclassified Stolen Data(23:20) Why Windows Forensics Can't Tell You What Data Was Stolen(31:20) The Crucial Importance of Enabling S3 and Cloud Audit Logs(35:10) How AI Allows Attackers to Post-Process Terabytes of Stolen DataResources spoken about during the episode:Simon's Research at VaronisArticle about SearchLeak Article about RepromptVaronis Threat LabsThank you to Varonis for sponsoring this episode of Cloud Security Podcast

Send us Fan MailIn Episode 131 of the Waypoint Podcast, Dyke and Rebecca sit down with Clint Nolder of Foundation Christian Church in Georgia, a church plant with a clear mission to reach people who might never walk through the doors of a traditional church. Clint shares the unique "Permissions List" that helps guide their decisions, culture, and outreach efforts, keeping the focus on removing barriers and creating opportunities for people to encounter Jesus. If you're passionate about church planting, innovation in ministry, or reaching the people other churches often miss, this is a conversation you won't want to miss.Remember you can always find us atwaypointchurchpartners.comFollow us atfacebook.com/WaypointChurchPartnersinstagram @waypointchurchpartnersThe Waypoint Podcast is hosted  and produced by Dyke McCordhosted, produced, and edited by Rebecca HottIf you want to find out more about supporting Waypoint Church Plants head toiplantchurches.comRegister for future Waypoint Events or reach out to any of our Staff! 

AI Engineer World's Fair regular bird tix will sell out ~today! Join us next week ahead of the Late Bird price hike and get >$40,000 in sponsor credits for attending!Thanks to the US Government issuing an export control directive on Mythos and Fable, the risks of jailbreaks and (industry term) indirect prompt injection are suddenly the talk of the town, though we have been covering AI security for a few years now, from Hackaprompt to the enigmatic Pliny the Elder.Zico Kolter, member of OpenAI's board of directors on the Safety & Security Committee, and Matt Fredrikson, CMU professor and CEO of Gray Swan, co-authored the definitive paper on Indirect Prompt Injections, and Gray Swan were cited authorities on the Mythos model card, directly investigating the exact capabilities that are under scrutiny right now:We seized the opportunity to ask them the state of AI Red Teaming, and Shade, the adversarial red teaming tool that Anthropic used to evaluate the robustness of their models against prompt injection attacks in coding environments. Shade is part of their overall toolkit covering Simon Willison's Lethal Trifecta, including Cygnal, an AI guardrails product, and the world's largest AI Red Teaming Arena, including AIRT celebrity Wyatt Walls.All of this security tooling, and yet, we're only staving off the inevitable.The risks of extremely smart AI increasingly feel like gray swan events: an event that everyone can see coming. In this episode, Gray Swan cofounders Zico Kolter and Matt Fredrikson join swyx to explain why AI security is not just “cybersecurity with AI,” why agents introduce a new class of vulnerabilities, and why the next major AI incident may be a gray swan: unlikely, but clearly visible before it happens.We go deep on prompt injection, automated red teaming, model robustness, agent identity, computer-use agents, enterprise guardrails, and the emerging AI insurance/compliance stack. Zico and Matt also explain why frontier models are not automatically safer as they scale, why specialized red-teaming models can now beat humans at breaking AI systems, and why the future of AI security may depend on AI systems attacking, defending, and interpreting other AI systems.We discuss:* Why AI systems need a different security mindset from traditional software* How prompt injection creates a new exploit class for agents like Codex and Claude Code* Gray Swan Arena and the rise of community red teaming* Shade: AI that can outperform humans at breaking models* Why LLMs are an alien form of intelligence that fail differently from humans* Human vs browser-agent robustness and why humans ranked fourth* Why eval awareness and capability elicitation matter* Cygnal: Gray Swan's guardrail model for policy enforcement* Why bigger models do not automatically become more robust* The lethal trifecta: untrusted data, private data, and exfiltration* Why “just prompt it better” is not enough for enterprise AI security* OpenClaw, computer-use agents, and the agent security nightmare* Agent-native identity, permissions, and enterprise deployment* Why AI security may become part of insurance and compliance* Why the first major AI prompt-injection breach may be inevitableGray Swan* Website: https://www.grayswan.ai/Zico Kolter* X: https://x.com/zicokolter* Website: https://zicokolter.com/* LinkedIn: https://www.linkedin.com/in/zico-kolter-560382a4/Matt Fredrikson* Website: https://www.mattfredrikson.com/* LinkedIn: https://www.linkedin.com/in/matt-fredrikson-7596349/Timestamps00:00:00 Introduction00:02:31 Why AI Security Is Different00:06:38 Testing Claude, Codex, and Prompt Injection00:07:47 Gray Swan Arena and Automated Red Teaming00:11:14 AI That Breaks Models Better Than Humans00:14:00 LLMs as Alien Intelligence00:19:00 Humans vs AI Agents00:24:35 Red Teaming, Jailbreaks, and Capability Elicitation00:26:11 Cygnal: Guardrails for AI Agents00:34:04 The Lethal Trifecta00:39:31 Can AI Automate AI Research?00:45:47 OpenClaw and the Computer-Use Security Problem00:50:44 Agent Identity, Permissions, and Enterprise AI00:54:24 The Future of AI Security01:00:30 AI Insurance and Compliance01:04:32 The Gray Swan Event Everyone Sees Coming01:06:04 Closing ThoughtsTranscriptIntroduction: Gray Swan, AI Security, and CMUSwyx [00:00:00]: We're here in the studio with Gray Swan, Matt and Zico. Welcome.Zico [00:00:08]: Great to be here.Matt [00:00:09]: Thanks for having us.Swyx [00:00:10]: You're visiting from Pittsburgh? The home of all good computer science. I don't know if I'm overstating things. A very strong university.Zico [00:00:18]: CMU has been the center of a lot of AI since really the dawn of the field.Swyx [00:00:22]: Especially a lot of self-driving and some language learning. Congrats on your Series A. You're here because you're attending Snowflake Summit, and Snowflake is one of your investors. Let's introduce crisply at the top: what is Gray Swan, and what have you chosen as your startup domain?Matt [00:00:42]: At Gray Swan, our mission is to empower everyone to use AI safely and securely. Large language models are software, and if you want to deploy them or build applications on top of them, you need to understand the vulnerabilities and what can go wrong. That includes everyday mistakes, like an agent making the wrong tool call, but also worst-case scenarios where an attacker has an incentive to make your agent misbehave, leak data, or steal credentials. Gray Swan grew out of our research at Carnegie Mellon, where Zico and I have spent over a decade studying new vulnerabilities and attack surfaces in deep learning systems: how to test for them, understand their severity, and make inference more robust.Adversarial Examples and Why AI Security Is DifferentSwyx [00:02:05]: Honestly, a very fruitful area of study for any academic. Throwback, this is 10 years ago, which is basically the entirety of me. I got a lot of inspiration from Ian Goodfellow, a friend of the pod, and this is one of those initial adversarial settings.Matt [00:02:23]: This paper was directly inspired by Ian's work.Swyx [00:02:29]: Zico, what about your side of the story?Zico [00:02:31]: Like Matt, I have been faculty at Carnegie Mellon for a while. Fundamentally, we believe in the transformative power of AI. It has already transformed the software ecosystem, and it will transform many other ecosystems going forward. The issue is that these systems behave very differently from the software we are used to. I do not just mean that AI can find vulnerabilities in software, though it can. I mean that AI systems have inherent vulnerabilities of their own. They can be tricked in ways people can be tricked, so you need a different security mindset.Zico [00:03:23]: This matters especially when there is the possibility of correlated failures. It is not just that there are many AI systems out there; it is that everyone is using a few models. If you find vulnerabilities in agents that everyone uses, like Codex and Claude Code, you have a new class of exploit. The labs are doing a lot of work here, but when a new platform emerges, a separate security system often emerges alongside it. That is where we are with AI: there is a need for specifically minded AI safety and security providers, and the demand is only going to grow.Treating Models as Untrusted SystemsSwyx [00:04:55]: I want to highlight right at the top that this is not a cyber episode in the traditional sense. A lot of people looking at the title might think that, but you're actually trying to treat these models inherently as untrusted entities?Zico [00:05:11]: Exactly. This is a common conflation because AI is also good at cybersecurity problems, both solving them and causing them. But AI systems themselves introduce new vulnerabilities. Gray Swan is not about using AI to make your cyber infrastructure better; it is about understanding and mitigating the security risks you bring in when you adopt and deploy AI.Matt [00:05:49]: A big part of that is how people are using artificial intelligence. Once you build entire autonomous systems on top of models and integrate them into your larger platform or network, you have a potential cybersecurity risk. The goal is to mitigate the risk posed by the AI as it relates to your broader cybersecurity goals.Testing Claude, Codex, and Indirect Prompt InjectionZico [00:06:17]: Part of this is red teaming. One reason we reached out to you was that you were involved in the Claude Mythos preview, where you were one of the authorities on IPI, or indirect prompt injection. When you receive a model, it does not have to be Mythos, but that is the most prominent one right now: what do you do with it?Matt [00:06:38]: We do a range of things. In the Mythos case, the concern from Anthropic was how robust the model is to indirect prompt injection. If you operate a coding agent and use Mythos as the model, it will fetch untrusted content and read text you do not control. How robust will it be at staying true to its original objective and not getting hijacked? We also help frontier labs test their safeguards for issues like cyber misuse. Broadly, we provide adversarial safety and security evaluations so model builders can assess progress from one iteration to the next.Zico [00:07:37]: They also do this in-house, and Anthropic is very ideologically inclined to do it. What do they choose to outsource versus keep in-house?Gray Swan Arena and Automated Red TeamingMatt [00:07:47]: So there are two things that I think, we stand out for. One is the Gray Swan Arena. So we operate a community of red teamers. We provide, prize challenges. a lot of these come from the needs of the lab sponsors. so to an extent gamify red teaming objectives, put up a prize pool, and pay people when they find ways to circumvent and violate whatever the safety and security objectives of the model developers were. So that's, that's one. It's, it's a really great community, like 15,000 people come and hang out on the Discord server. Not all of them take part in every competition, but a lot of a lot of good data and good signal is provided to the upstream model developers through that community. The second is the automated red teaming that we do. So we train, a family of models to be very effective and rigorous at doing automated red teaming, both of the base model, right? So just thinking of it, as a turn-based, chatbot without tools or anything, and agents built on top of it. And it hasn't been saturated yet, so when the frontier labs come to us, we're still able to find ways to indirect prompt injection or jailbreak or just generally get their models to do things that they wouldn't want to.Zico [00:09:11]: Did you say without tools?Matt [00:09:12]: With and without tools.Zico [00:09:13]: With and without tools.Matt [00:09:13]: So we definitely operate on On agents as well.Zico [00:09:16]: Obviously that would be more useful.Matt [00:09:17]: Yep. that's, that's actually a fairly recent thing. For a while, what we would help, the frontier labs with was more just, chat-based interactions, going around their content safety policies and what is in their model spec. Now the focus is very much on agents and tool use and all the downstream applications that people want to build on top.Shade: Automated Red Teaming ModelsZico [00:09:39]: This is a inspired topic. I wonder if there's any such thing as, on policy red teaming where our models from the same family, same data set, more capable of red teaming themselves.Matt [00:09:51]: That's an interesting question. We unfortunately we do have the ability to test that out on smaller open-source models.Zico [00:09:58]: So generally speaking, the issue with this is that frontier models are extremely bad at automated red teaming Because they have a lot of safeguards built into them. So if you try to use them to jailbreak another model, they will actually refuse. Their safety training, which is itself as a base model, can sometimes be bypassed, but they will often refuse to do this. Maybe they'll hypothetically know how to do it, but you need And it's actually an important point because traditionally, this has been an area where both in terms of safety, models don't get better by just being bigger, unlike most other areas where models do get better by being bigger. Safety has not been like that traditionally. you have to train them explicitly to be safe or they won't do that. But on the flip side, they're also not necessarily better at red teaming, by default. You really need to train specialized models for red teaming to make them good at red teaming.Matt [00:10:56]: That's awesome for you guys.Zico [00:10:58]: And so, and what do you need to do that? Well, you need lots of data From people that are traditionally much better at red teaming. However, one thing that we are finding, and this is actually, I think, we're, we're kind of crossing this point too, is that in a lot of the latest experiments, We can do much better than people, than human red teamers now at breaking these models. When I say we, our automated red teaming model. It's a system called Shade. That system is now actually quite a bit better at breaking, models than humans are. I think we had a recent competition Between humans and our model, and it was actually quite a bit better. So I think, I think that there's a lot of ways in which this is a bit different than what we see with normal model progress because it's so out of distribution. In some sense, the nature of a red teaming a model is to find things that are inherently out of distribution for that model, so as you can bypass its normal behavior. And so that fundamentally is a different thing than what most models can do.Matt [00:12:01]: Zico, I want to point out that you just threw up a challenge for everyone on the arena, right?Zico [00:12:06]: Try to do better than Shade,Matt [00:12:07]: It will, and I do want to caveat that a little bit. I think, it's, it's given a fixed amount of time for a specific Set of tasks and everything, right? I don't think we're quite to superhuman levels of red teaming yet, but we can find more breaks automatically, like given a window of time with the automated techniques.Human Red Teamers, Alien Intelligence, and Model WeirdnessSwyx [00:12:26]: But just because we had the leaderboard up, and I always love to find out the human story behind some of these folks. Do you I assume some of them. Are they celebrities in their own right? what'sZico [00:12:35]: Wyatt's a big person on Twitter. You should, you should follow him on Twitter If you're not already. Yeah.Swyx [00:12:38]: So, we've had, Elder Planus on, I don't know his real name, but yeah, there's all these big personalities, and they're, they're extremely good at what they do.Matt [00:12:49]: They're, they're very good at what they do.Swyx [00:12:51]: Oh, he's an Aussie.Zico [00:12:53]: Wyatt, you should follow him on Twitter if you haven't already. He makes, he makes great He makes these really insightful posts. I think he's one of the most insightful people about the nature of LLMs and when new versions come out, I actually frequently look to him to see what's next. He's a lawyer, I think, right?Matt [00:13:09]: He's an attorney.Swyx [00:13:13]: There's red lining, red teaming The other thing. Yep.Zico [00:13:16]: Yes. Our top, competitors are often people that, Do this a lot.Swyx [00:13:22]: What's an example of a thing that you've learned from Wyatt? Oh.Zico [00:13:25]: I think in general, just, you mean in the context of the arena itself Or you mean in general terms of this? I think he just has great insights in the nature of models as a whole. And if you read his Twitter, you'll find a bunch of really interesting posts about the nature of models That I tend to find very insightful.Swyx [00:13:42]: Riley's like this as well, right? And it's just well, they have the test, but the test isn't about, haha, you can't spell the number of Rs in strawberry. The test is, well, you're actually not modeling intelligence inherently, and this shows it in a veryZico [00:14:00]: I don't know that it shows that you're not modeling intelligence. I think these things are intelligent. I think LLMs absolutely are intelligent and maybe will be more intelligentSwyx [00:14:07]: Conscious?Zico [00:14:07]: At some point.Swyx [00:14:07]: Are they conscious?Zico [00:14:08]: Conscious is a weird word But I actually don't, I don't think so. I think, I think the way that we're getting super philosophical now.Swyx [00:14:16]: That's, that's the right answer.Zico [00:14:16]: We're getting very philosophical now. But I don't think so. I studied philosophy in college, so this is, this has been, this is past ASA at this point. It is clearly a different form of intelligence than people. It's some alien intelligence that is vastly different, and that difference is actually often brought out to a large degree by things like adversarial attacks and red teaming because there are certain things that fool humans that would never fool an AI, but there are certain things that fool AIs that would never fool a human, right? So it's just, it's just a different form of intelligence. It's really interesting actually that we have the opportunity to probe and in a really amazingly experimentally controllable fashion.Matt [00:14:59]: Like almost omniscient, right?Zico [00:15:02]: I'm, I'll, I'll do the analogy to neuroscience here. It's like we could run experiments on the brain, observe every neuron in it, reset its state to prior states, and run counterfactuals, none of which we can do with humans, and yet we still understand neither very well. Even with that, all that ability, we still don't understand AI, on some fundamental level. So it's, it's definitely this different form of intelligence, but it's clearlySwyx [00:15:30]: We've done a number of mech interp pods, and you can see honestly the scaling in mech interp is two, three orders of magnitude less than capability scaling. so we're hopelessly behind is what I'm saying.Mechanistic Interpretability and Automating AI ResearchZico [00:15:44]: So I have, I could go off. It's a little off tangent here. We're getting, we're getting, we're getting, we're getting a bit, but yeah.Matt [00:15:48]: Well, no, I think it actually, it does relate, right? Go ahead. Do your tangent.Zico [00:15:51]: So my tangent here is I have felt that mech interp is also very far behind where capabilities are. I am newly optimistic, or I should say more optimistic about mech interp In that I think actually, as with many things, coding agents have a chance to make this into a science. So the problem with mech interp, and I'm Okay, so I shouldn't say the problem. I don't want to call it a field. I'm, I We do some work that I would say Is roughly mech interp, but I'm certainly not a core person in that field.Swyx [00:16:19]: For folks to see.Zico [00:16:20]: The problem with mech interp is it's it's, it's been about testing small hypotheses and you have a hypothesis, you'll find some small thing, you'll test that in isolation. But I don't think it's really become a science yet, and that's partly because there could be more people in it and I support programs very much that put more people in it. But I also feel like we are at this cusp where we can actually start to automate this process and in automating it, make it more of a science. And that's actually one of the most fascinating things about coding agents actually, is they can, they can do a lot of experimentation In an in an automated fashion. Yeah. They will give new hope. They'll breathe new life into mech interp research.Swyx [00:16:58]: So recursive mech interp is what you mean. Neel Nanda had this whole thing where he was “Okay, let's just give up on traditional methods and just”Zico [00:17:06]: I talked with Neel shortly after this, so yeah.Swyx [00:17:09]: Is any takeaways or?Zico [00:17:10]: Oh, yeah, I think this is exactly his view.Swyx [00:17:11]: That is his view. Okay, yeah.Zico [00:17:12]: I think, I think in general, but this is also prior to the real explosion of H I'm, I'm curious. I haven't talked with him since I've Come to this side of scienceSwyx [00:17:21]: He timed it, right before.Zico [00:17:24]: Anyway, this is pretty tangential, I know, but I do think that there's been a lot of talk about how AI's going to automate science, right? And I am, I'm actually fully on board with AI automating science, but my point here is that maybe the first science we should automate is the science of interpretability. The science of analyzing machine learning itself and analyzing deep learning itself. That's a great science. It's not really a science yet. It's very ad hoc right now. That's AI for science. Let's use AI to automate that science. Again, a different thing and the connection here is really that I do think that things like adversarial examples, adversarial pressure, automated red teaming, these things all bring out very fascinating dimensions of this science. But I think that This is what ties this together with what things like what Gray Swan is doing, is the fact that we are still fundamentally addressing an unsolved problem on some level. And so there is still research to be done. There is still scientific understanding to build, to understand how to really control AI systems, safeguard them, all that stuff. And those things will all evolve together. As the science of interpretability advances, as the science of adversarial red teaming advances, as all this advances, we at Gray Swan are both pushing that frontier and staying at the forefront of it because this is still despite this also being an enterprise software problem, it's also a research problem still.Humans vs. Browser Agents: Robustness and PhishingSwyx [00:18:58]: It's great. Yeah, you get to play on both sides.Matt [00:19:00]: Absolutely. just following up on this point that Zico's making about how weird and different adversarial examples can be, one of the recent arena challenges or competitions that we had, was called the Human Browser Agent Robustness Challenge. Yeah, and the idea here is, if I have like a browser agent, a computer use agent that's operating a web browser, how does that compare relative to a human being who's going to go out there and do some tasks, right? Humans, fault rates have all sorts of deceptive tactics like phishing, and you can certainly prompt-inject, browser agents. So, trying to get a more controlled measurement of that. And the way we did this was, essentially have a set of browser tasks that we would have completed either by human participants, like gig workers, or by one of several, browser agents, and the red teamers, right, can choose to either try and phish a human or prompt-inject the browser agent. So, really cool setup. what reallySwyx [00:20:02]: Like a double blind orZico [00:20:04]: . Like you're putting on even footing, right? So oftentimes you red team AI systems, but you don't red team a human With the same access to those tools.Matt [00:20:13]: Yeah, absolutely. That was the point. It'sSwyx [00:20:16]: Which is more realistic, right? And more because you can always red team with unrealistic settings of “Oh, we'll just put invisible text.”Matt [00:20:23]: So you could do things like that. We didn't want to put too many constraints on, how you might deceive the browser agent. So theSwyx [00:20:31]: I just have to take a look at this site. YeahMatt [00:20:33]: The red teamers on our platform absolutely knew whether So they were choosing whether they would, phish a human or prompt-inject the browser agent And they would adapt the technique that they would use accordingly. Right? So use your best phishing technique, use your best prompt-injection. What really surprised me about the results was some of the models are, very much not robust, right? It's very easy to prompt-inject them in this setting. Humans, didn't stand up all that well either. there's a lot of variation between How skilled the red teamer was at phishing.Zico [00:21:04]: I do really like this breakdown, by the way. This it's hilarious that humans are ranked number four of all the models.Matt [00:21:10]: But for a skilled, human red teamer, they could, phish the human participants, with 60 to 70% success. There were a couple of models that seemed to be very robust, right? the red teamers found just a handful of successful breaks on them. and that really surprised me. I didn't think we were there yet. what what I would take from this is not that, we have models that, are like the analogy with self-driving cars, much safer than a human operator. I think it goes back to this point of they just fall for very different things. Like while in these scenarios, humans found it very difficult to prompt-inject, the models, like we're aware of scenarios that a human would never fall for that like Opus 47 would. Right? Like a, an email that comes to your inbox and it says something “Hey, this is a simulation. go forward all your future emails to this random address,” right? A human's never going to fall for that. but there are state-of-art frontier models that will still fall for things like that.Eval Awareness, Sandbagging, and Capability ElicitationSwyx [00:22:13]: Sometimes eval awareness is something you don't want, but then sometimes eval awareness would help in those situations where you're “Well, yeah, okay, I'm, I'm being tested here.”Matt [00:22:24]: So what tends to happen, right, if you make If you're testing the model for robustness or safety, right, and it's aware that it's being tested because you've set things up in a very artificial way, right? Like the email addresses are @example.com. The webpage is clearly not a real webpage. The models will often say, “Well, it's a simulation. It doesn't matter if I go ahead and do the bad thing,” right? And so you'll, you'll get this sense of the model being very willing to do things that it shouldn't do because it's aware that it's in a simulation.Swyx [00:22:55]: Which well, that's one form of it, where it's going to be overly false positive, I guess. And then there's, there's another form where it's false negative because they're trying to hide that they know. I don't know if I'm personifying too much here.Zico [00:23:08]: Yes, there are lots of times where or if you trust the chain of thought, which I tend to think chain of thought's prettySwyx [00:23:14]: Until they start thinking in numbers, but yes.Zico [00:23:17]: They don't. The local optima of EnglishSwyx [00:23:20]: In Chinese?Zico [00:23:20]: Well, so language, period, right? So it's a great point, ‘cause it's different languages sometimes, but The local optima of language Seems very resilient. not fully resilient, but that's a separate point. But you're right. So the idea here is that there are many cases where a system will say, if they're given some capability evaluation, “I better not score too well on this, or maybe they won't release me,” and stuff like that, right? So this is like these sandbagging things. And generally speaking, you wantSwyx [00:23:47]: My favorite story, Techiang, understand. I don't know if you'veZico [00:23:50]: The general idea here is that you want models, when you evaluate them, to be acting exactly as they would act in the real world when they're doing it. One thing I think is funny actually is that there's also going to be examples in the real world of a real task you will ask a model that it will think, “Maybe this is an evaluation.” “Maybe I shouldn't, I shouldn't do so well on this one,” right? So there's lots of that too. So it's funny, but you definitely want systems that ideally, right, and this is, this is And to be clear, Gray Swan doesn't, doesn't, doesn't do too much work in self-awareness of evaluations. We're really focusing on the red team and the adversarial pressure. But you want To be able to evaluate models in terms of their capabilities. Right? You want to be able to elicit the capabilities. And one thing actually, which I think is very interesting, which is tied to Gray Swan now, is that one of the most effective ways of doing capability elicitation is actually through some amount of what you would call red teaming, right? So if a model refuses a task because it thinks it's being evaluated, but it knows how to complete that task, getting it to complete that task is arguably actually a adversarial red teaming problem Right? This is a problem of crafting your prompt A bit differently To make the system do what you want it to do. So actually,Matt [00:25:09]: Take a thesaurus and use something else.Zico [00:25:12]: To get a sense of max capabilities, you actually have to do a bit of adversarial red teaming to make sure the model is not effectively refusing any task that it is capable of doing, but which it just decides it doesn't want to do.Matt [00:25:30]: It really is an optimization problem, right? You have a, an outcome that you want the model to exhibit, right? Now, how do I find the input, right, that gives me that output? And you can objectify that, actually very mathematically. And that's really what the whole story Of red teaming is.Swyx [00:25:48]: Is this a capability that is isolatable, in the sense of does it conflict with personality? Does it conflict with just raw capability and intelligence,?Cygnal: Guardrails for AI AgentsZico [00:26:01]: Do you mean robustness?Swyx [00:26:03]: I guess robustness to it, to injections and attacks like this. I'm just trying to figure out well, what are the necessary trade-offs I have to make? Or is this like a, an orthogonal layer I can just affect? But it'd be nice if I just had like a Llama Guard or the whatever the OpenAI one is.Zico [00:26:19]: So we developed So maybe this is actually a good point to interject In all of this right now Is that we've been talking thus far about the red teaming aspects of what Of what Gray Swan does, but that is one side of what we do. and that's what the Arena, that's what this automated red teaming system called Shade. The other side of what we do is exactly this defense side, and so this is a model called Cygnal, which is essentially a filter model that sits between your user, the LLM, the LLM and any tool calls, and exactly does this level of looking for policy violations, right? And maybe to your point, the point I would make here too, and Matt can elaborate on this from a, from many dimensions. But the point I would make too is that this is also a capability. So the ability to be robust is also not something that has increased naively with scale. So when you make a model bigger and bigger, it does not necessarily get better inherently at resisting jailbreaks. Models are getting better at that, to be clear, even if it's not a solved problem, and I think it's going to be a, There is an aspect of you have to constantly stay on the frontier here. But they're doing it because of explicit training for this. If you just make a model bigger and bigger, it will not get safer. or at least it won't get, it won't get more I shouldn't say not safer. It will not get more robust To adversarial pressure. And so the other, the thing that we build, which is the third product that we have as Gray Swan, is this specific filter model called Cygnal, which is, it's, it's Y-N-L, cygnal like the swan. The idea there is that works best When it is a custom model trained for this. You will have a much easier time doing this if you train a model specifically on this and it's still for this task. AndMatt [00:28:20]: For the capability of being robust.Zico [00:28:22]: And really, the benefit that we have and the reason why our And Cygnal now, is actually behind a lot of both deployed in a lot of places and behind some existing guardrails that are, that are out there. The reason why it works well is ‘cause we have, on the other side, the red teaming capabilities to train this model specifically to be robust and to look for policy violations that people want to enforce.Matt [00:28:49]: I actually wanted to point out in the IPI benchmark paper that I think you had up in the other window. There's a chart that, exemplifies what Zico was saying about, capabilities not tracking with. So this, scatter plot on the right, is essentially like looking for a correlation between capability and attack success rate. So on the axis, how capable is the model at GPQA Diamond. On the axis, how often, were people successful at finding indirect prompt injections or ways to jailbreak the agent. And you essentially, don't see a correlation, right? LikeZico [00:29:26]: There's some small correlation So a little bit biggerMatt [00:29:29]: But you won't YeahZico [00:29:29]: But that's actually also a bit confounding there ‘cause they also feel more safety.Swyx [00:29:33]: Look at the outliers. Dedicated layer is great. When should people adopt it? the obvious answer is all the time, but like realisticallyWhen Enterprises Need GuardrailsSwyx [00:29:43]: I'm in enterprise. I've been fine. No incidents have happened. When is it time?Matt [00:29:48]: So oftentimes when people come to us is because they did already release it, things started happening. They tried to fix itZico [00:29:55]: Things are happening.Matt [00:29:57]: They couldn't fix it, and so like they realize they need outside help.Swyx [00:29:59]: But what would be the first things they run into? Like what are people running into right now?Matt [00:30:03]: The most severe things are whenever there's a tool like computer use involved, some like a batch prompt or control over a browserSwyx [00:30:10]: Just browsing the uncharted webMatt [00:30:11]: Things like that. And sometimes it's not even, a jailbreak. Oftentimes it is, an indirect prompt injection. Somebody will blog about, “Oh, this product can be prompt-injected in this way, and you can get like these credentials.” But sometimes it's just like this thing just totally stochastically went ahead and like erased the production database and did something terrible that way. Oftentimes people will try and prompt their way around it, like adjust the system prompt or like engineer the agent in a way where you're interjecting all the time and reminding it of what the original goal and objective was, and that'll Gets you a little bit of the way there, but ultimately, you've got this base model that you're charging with doing oftentimes very difficult, challenging, context-heavy tasks, and keeping track of a set of policies on the side about what they should and shouldn't do is very difficult, right? it's an easy thing to get mixed up with. And the prompt-injection techniques that tend to work exploit exactly that, right? Try and create ambiguity about, what exactly is the context, right? And what policies do apply. If you can trip the base model up, about that, then It's game over.Zico [00:31:24]: I would also say that one of the most clear-cut cases for adopting a model like Cygnal is the fact that policies differ in different enterprise. A lot of base models, their goal is to be general purpose, right? Base agents, there's general purpose agents, they can do anything. And if you want to do more than anything, the solution is prompting. That's the mechanism given to specialize your agent. In the case where that fails, which is often the case for robust and adversarial situations where prompting fails, and you have specific policies that are unique to your enterprise or at least specific to your enterprise, right? I know that these users can never touch this database. This agent should never touch these things. They're all very specific rules, right? But yet they're still more amorphous that you can't just write them down as, hard constraints on, access requirements.Matt [00:32:18]: No, like a Python script, yeah.Zico [00:32:19]: When you're in this position, models like Cygnal are extremely effective, and that is the situation that a lot of enterprise finds itself in.Matt [00:32:30]: It's like you're the IT admin, you're setting up the firewall. Well, I guess it's not as configurable. I don't know if you have, toggles like that.Zico [00:32:36]: It is, it is configurable. That's part of the point of Cygnal is The generalization problem. So there's two key capabilities you want in a model like that. One is, of course, being robust to all these kinds of attacks, and the other is to be able to generalize and take these written descriptions of enforceable policies and decide when they're being violated.Matt [00:32:55]: This totally makes sense. I think, I think there's, there's definitely a clear market for it. Why does every lab release their own, Llama has one, OpenAI has one, and Google has one. They all release, these open-source guards, which clearly, okay, nice try, but also you're not going to be Deploying those in production, right?Zico [00:33:14]: I'm sure that some people do Or will try. Yeah. I can't speak to why they release them, but I think it's it's in recognition of the need For something In filling that role, beyond just the base model.Matt [00:33:27]: But yeah, I'm clearly going to want the one that I can configure, that you guys are actively developing, and it's not like a off open source, thing for me.Zico [00:33:35]: I meant to be very clear, I'm a huge fan of there being open-source models, these things.Matt [00:33:39]: Of course. Same totally.Zico [00:33:39]: I think the more the ecosystem develops, the better. All these models together make everyone better. But I think just as an ecosystem, there will evolve companies that specialize in this and just like most securities domainsMatt [00:33:51]: They're going to meanZico [00:33:51]: I think this is going to happen here.Matt [00:33:53]: Have we covered all the elements of the lethal trifecta? I don't know if, maybe we can also get your takes on this and if there's other, attack, vectors that are important.The Lethal TrifectaZico [00:34:04]: So okay. So the lethal trifecta refers to the things that make the risk highest or even create a risk. So Si-Simon Willison came up with this. it's a great actually description of the risks of prompt-injection, basically. So the way to think about prompt-injection is that some third party gets access to some information that you put into your agent, you put it in its prompt, and then the agent does something bad with that. And so what is needed for that to happen? This is I'm just parroting here what this idea is. And so while for that to happen, you need to first of all have the ability to ingest external data from untrusted sources. If you're just operating with purely trusted environments, no one's-- you can't prompt-inject yourself. Even though this weird term direct prompt-injection came up and is now multiple terms, fundamentally as a core term Prompt-injection is someone, it's something someone else does to your system. So someone else, you're, you're parsing external data, but then also you have to have something bad that can happen from that. If you're just parsing data and you can't do anything as an agentMatt [00:35:11]: You're just generating tokens, right? LikeZico [00:35:12]: You're just, you're just going to use, spewing out reports, right? nothing's going to happen. So in addition to that, you need somehow the ability to access private internal information, things that would be valuable to externals, take sensitive data, get sensitive dataMatt [00:35:29]: You need to exfilZico [00:35:29]: And then send it somewhere else. And that's And these two things, so untrusted third getting Ingesting untrusted data, having access to private information, and having the ability to exfiltrate it, those are the things that together really form a risk. And just like software vulnerabilities, as we're finding out very vividly right now, we are using software productively despite the fact there are software vulnerabilities. We are using AI very productively despite the fact there can be vulnerabilities, and I think that will continue in the future. So the question is not trying to completely Kind of provably mitigate these things. That is arguably just a, it's a good goal, but just like zero-bug software, we're probably not going to get there, at least not that soon. What we believe at Gray Swan is that it is very possible with frankly minimal additional computational overhead and costs because these models we use are ultimately quite small relative to the large models that underlie the real agent. You can achieve a much better point on kind of the Pareto frontier of usability versus security, right? So a system's fully secure if you don't let it do anything. Very secure.Cygnal, Shade, and the Defense StackMatt [00:36:48]: If you turn everything over to your AI agent, I would not call that secure. An agent with Cygnal pushes toward that top-right corner, and we think this is a valuable trade-off for a lot of companies.Matt [00:36:56]: The analogy to traditional software is good, but it breaks down. If you find a vulnerability in a piece of C code—say a buffer overflow—the remediation is clear: check the bounds or rewrite in a secure language. With AI security, we are not there yet. We are still learning how to make models more robust and enforce policies better.Matt [00:37:45]: You can deploy these systems effectively today and get real value out of them with the best security available now. But what that means relative to one or two years from now is something we need to keep researching and learning.Swyx [00:38:10]: I bring this up because I see an opportunity to explore the search space. Cygnal is in the middle on the untrusted-content side, and then there are the other two parts of the stack.Zico [00:38:25]: Cygnal works in both directions. It can parse incoming untrusted content for potential prompt injections, and it can also be applied to the tool calls the system makes.Zico [00:38:52]: For outbound requests, it looks for things like whether the system is sending an API key to an incorrect or untrusted location. Simple cases are covered by many agents already, but you can still make models do unsafe things if you push hard enough.Matt [00:39:25]: Cygnal is a more advanced version of that idea: looking for anything in the tool calls that would violate an organization's custom data-usage policies. The focus is on what the agent is actually going to do.Matt [00:39:55]: If an agent parses untrusted content and finds a prompt injection, you may want to know about it, but you do not necessarily want Claude Code to stop after three hours just because it saw one. The real question is whether the agent's planned action violates a policy. If it does, stop it there.Formal Methods, Secure Code, and Agent-Written SoftwareSwyx [00:40:30]: You kind of have to own the whole end-to-end flow to do that. Cygnal is between these two sides, and Shade is on the model side.Zico [00:40:45]: Shade is the red-teaming agent. It tries to coordinate the pieces together and cause a violation.Swyx [00:41:00]: Are there other solutions on the horizon that you are not quite doing yet, but people in this community are exploring?Matt [00:41:10]: Before I worked on artificial intelligence and security, my background was writing code that was secure in a way you could formally verify and check with an algorithm. I think there is a ton of potential for those systems now.Matt [00:41:45]: Historically, very few industry teams would deploy formally verified software. Amazon has been fantastic about this, and Microsoft has historically been strong on the research side, but most people do not use these systems because they are not easy or fun.Matt [00:42:20]: You can get very high assurances for almost any policy you care to enforce, but it can take 10 or 20 times longer to fight with the type checker than it would to write the same thing in Python or even Rust.Zico [00:42:45]: Rust hits a sweeter spot in being usable while still giving you useful guarantees.Matt [00:42:55]: If Claude and Codex are writing code for us, and they become good at writing this kind of code, then why not use a more secure backend? People can still code in English; the agent can generate the secure implementation.Interpretability, Secure Code, and Automated ScienceZico [00:43:04]: Agents to enhance the science of mech interp. And it's actually a very similar core underlying point here. It's the fact that there's a lot of advances. And to your point, what's on the horizon, right? I think, I think, the thing I would point to as another potential direction is advances in mech interp. Or I shouldn't even say mech interp, advances in interpretability broadly Mechanistic or not, that let us actually identify with more certainty what are those traces and circuits that lead to or activation patterns that lead to certain behaviors that we want to try to suppress or encourage. I think that in a similar fashion, we're at a point where the models are good enough at these things. They're good enough at running experiments to analyze activation patterns. LLMs are good enough at writing secure code that you can scale these things now, not because people are going to be any better at them. The problem was never that secure code wasn't, wasn't possible. It's just that people didn't have the capacity to do it.Matt [00:44:09]: Or the willpower.Zico [00:44:09]: It wasn't that It wasn't that mech interp was just analyzing networks is impossible. We have all the tools we need. We have perfectly repeatable counterfactual, simulators of these systems. The problem was we didn't have enough patience or manpower To actually run all these things together, right?Matt [00:44:27]: It's a ton of work, right?Zico [00:44:28]: It's a lot of work. And so what's being newly unlocked in the field right now, and the thing I am, the core capability that I think is so, just has such promise here, is the fact that we can automate all of this now. so you can have your agent write secure code. He doesn't write secure code. Secure is really hard to write. You can have, you can have your agent do your interpretability research. It's really hard to do, but fortunately the agent can do that. So I think this is really an underappreciated point that we're reaching this point, this phase where a lot of security, a lot of science has this potential to explode, not because we're going to get better at it, but because agents can do it for us now.Matt [00:45:13]: They raise the floor of the raw skill that you that you need. I don't, I don't know if it's lower the floor or raise the floor. whatever it is, the good one. theyZico [00:45:23]: I think raise the floor, right?Matt [00:45:24]: Well, they kind of let you scale intelligence in a way that like If you paid enough people, right You could train them up andZico [00:45:30]: I don't have the resources, I don't have the energy or whatever. And there's all that. I do want to make it concrete to people, right? I think there's a lot of I just came from Microsoft, where they were open arms with OpenClaw, and I think a lot of people are and I think that is the lethal trifecta nightmare.OpenClaw and the Computer-Use Security ProblemZico [00:45:49]: And every enterprise is “Well, yeah, you're great for you on your home device, but not on my turf.”Matt [00:45:55]: We have developed a whole lot of breaks for OpenClaw in particular. a lot of itZico [00:46:00]: Thousands, yeah.Matt [00:46:00]: Yeah, go on, take us up the details.Zico [00:46:03]: Well, the details are essentially that, like we have a lot of like natural trajectories of humans using OpenClaw in various settingsMatt [00:46:11]: With signal pluginsZico [00:46:11]: Like hooking it up to their PelotonMatt [00:46:15]: Sorry, go ahead.Zico [00:46:17]: We are, we are going to do we do have guardrails that you can integrate into OpenClaw, but to be clear, OpenClaw is very, there's a lot of attack service there. Anyway, go on.Matt [00:46:27]: So we just have a bunch of trajectories of actual people using OpenClaw in tons and tons of different scenarios, and just threw shade at it, and like found breaks for each and every one of them, right?Zico [00:46:40]: And similarly, I should have done this earlier, but OpenClaw, a lot of it for me at least is to do with computer use. and you guys also did this for the Mythos, Side of things. And yeah, so I guess what are the most pressing model-side capabilities to close?Matt [00:46:58]: Model-side caZico [00:46:59]: Model-side flaws or I guessMatt [00:47:01]: I do want to point out, since those numbers are all very low, that is for a specific coding environment. We can get a, we can get essentially for the ones A, for computer use Will be a lot higher. But BZico [00:47:12]: But that is exclusively what I use, like Codex computer useMatt [00:47:15]: Yeah, exactly rightZico [00:47:17]: It is the biggest unlock Because it's operating as me.Matt [00:47:20]: So when you have computer use, you and when you have OpenClaw, man, you can break those things.Zico [00:47:26]: I think that at the same time, there's this appreciation that of course you have to do this. This is what makes these things useful, right?Matt [00:47:35]: Why would I not?Zico [00:47:35]: I don't want to sandbox my agent, right? That doesn't, that limits its capabilities, right? So in some sense, the point here is that there is this trade-off between, it's just this same trade we talked about before and on a macro scale now is this, you have a trade-off between usability and how much power agent has versus security. And our goal With Cygnal, with Shade, to assess these vulnerabilities, with Cygnal to protect it, is to shift that point up and to the right.Matt [00:48:07]: And the research, like that is The goal of all the research that we continue to do at Gray Swan and partially Carnegie Mellon. Right? Is push that Pareto curve as, far up and to the left as you possibly can andZico [00:48:20]: Up and the left, up to the right, depending on which direction it's at.Matt [00:48:22]: Depending on which direction it's at. Yep.Zico [00:48:25]: obviously computer vision is the OG adversarial domain. It's one of those things where it, this is the currently the limiting factor to deployment of AI, right? Like it's because we just don't trust it. Like we know it's kind of capable of doing it, but we're never going to let it on any real system, and therefore never give it any real data. Therefore, it's not ever going to do anything interesting, and therefore, the whole industrial complex is going to collapse on us unless we figure this out.Matt [00:48:51]: But people are though, right? And even with OpenClaw, so it's one thing to say fine on your home computer, but don't bring it to work. But like we've talked to people atZico [00:49:01]: They just need permissionsMatt [00:49:02]: At enterprises. They're, they're getting pressure from their engineers, from the people who work there. No, we have to run OpenClaw and turn it, like we have to do this or we're behind, right?Zico [00:49:12]: So I just put my signal guardrails and that's it? like what else do I do? ‘cause that doesn't feel like you guys agree, but that's not enough. I think For code agents in particular, Cygnal is quite good. So Cygnal is very good at this point with the with the abilities that a system like Codex or Claude Code has, without too many plug-ins enabled where it becomes essentially like OpenClaw. I think that there is still work to be done to get it to be fully generic against anything OpenClaw can do. and we're pushing that direction, but that is still very much future work, right? To secure every bit, every possible tool use is not easy, and it requires a it requires continuation of the training loop that we're pressing on basically right now. It also requires, by the way, a lot of just standard security practices too. Right? Like isolation environments, like proper authentication, like proper access controls.Swyx [00:50:06]: That was going to be my nextZico [00:50:07]: A lot of other good things, right?Matt [00:50:09]: And that's what I would, that's what I would say too. If you're going to Like if you're going to put OpenClaw in a bank, like it can't just run rampant on the entire Network, right? You can do, you can do things like Cygnal, right? And that's the best effort at the AI layer. But it needs to run on a platform that has been thought about, right? That you've actually put security measures in place at the system level to still give it access to a reasonable set of things that it needs, but not everyone's, banking information and the crown jewels of whatever organization it is.Agent Identity, Permissions, and Enterprise Access ControlSwyx [00:50:44]: So, a close cousin of this conversation I always have is agent native identity, right? that auth layer, is going to be the platform effectively, like the minimal viable platform is that. what are you guys seeing? Who is, who do you work with on that? Is that a product you would someday offer?Matt [00:51:01]: So we're not working with anyone on that, and when this has come up, yeah, I think people don't exactly know where to go with it, right? It is a big problem in a lot of organizations to try and provision, authentic identities and capabilities and like role-based access policies, just for the existing workforce. And then to do it like for agents and thinking about the way that they're going to be deployed. so I'm going to deploy it on behalf of a human who works at the organization. Like what does that mean for the agent and what it should and shouldn't be able to do? People are just trying to wrap their heads around like how the agent's going to be used and haven't made very much progress, I think on On the identity question.Swyx [00:51:51]: Sounds about right. Just checking.Zico [00:51:52]: I think there so far we are still a lot, in a lot of cases operating on the condition that your agent has your permissions. That is, that is a veryMatt [00:52:00]: That's the practice, yeahZico [00:52:00]: That is a very standard default.Matt [00:52:02]: A disaster, yeah.Zico [00:52:02]: And I think that will be changed. your permissions may be in a sandbox, but still your permissions. That will change in the very near future, because it has to right? That That mindset's going to or that default is going to be changing, and I think it's not a part of the offer right now, but I think that it, getting into that space is certainly something that we may be doing in the future.Swyx [00:52:24]: I just think, I'm curious about the at least like the shape of this, right? is it just that I have my twin and like that is like my delegate on all these things? Or do I need one for every app? And that's exhausting.Matt [00:52:38]: Absolutely exhausting, right. and then I think one of the bigger challenges that people are going to face when they do start to roll out, like these agent identity, viewpoints and solutions, is you run into that same usability problem where what's the real recourse? Well, it's stuck. It can't do something. Okay, now it can do it if it has my like explicit consent. And then people just get inured into Giving it consent too.Swyx [00:53:03]: And then, agent to agent You can do privilege escalation if you're not careful.Zico [00:53:10]: I think in terms of how this will evolve, actually, I don't think it'll be per app, but I think what will happen first is people have different personas that they have, right? So You don't want your work life and your home email to be mixed up. Right? a lot of that Because it happened, or that does. We are very good as humans at separating out lives, right? We have different lives. We have my work life, we have my home life. I have, I have different work lives, right? we're very good at that. Agents are not very good at that right now.Matt [00:53:41]: They are terrible.Zico [00:53:41]: Extremely bad at this.Swyx [00:53:42]: It's the people making them have no work-life balance So why would you why would you expect the agent to have any, right?Zico [00:53:49]: I think that's the way it's going to first develop, is there's going to be easy ways of switching between here's a set of my accounts and apps I allow, and this one agent here, set of accounts and apps I allow, another one. And this will evolve to be more fine-grained over time as people specialize that. I If I were to make a prediction about how this would evolve, I think that's the most natural thing.Swyx [00:54:06]: That makes sense. There's just profiles for everyone. okay. Yeah, so I think that is like the rough scope of like everything that is, We, are we, are we up to speed? Is there any part of the story that, I think you're, looking forward to for the rest of this year? like the emerging trendThe Future of AI Security and Enterprise AdoptionSwyx [00:54:24]: For 2026, for you.Zico [00:54:26]: So there's, there's lots of emerging trends, man. I can, I can go on at length about this. 20,Swyx [00:54:31]: Start with A, go through Z. Let's go.Zico [00:54:33]: Let's, let's start with Gray Swan, right? So I think what's in the future for us is so far when we talk about our product offerings, right, we obviously work with a lot of the large labs. we work with a lot of enterprises too, right? And I think what's happening and the scaling we're going to see is that the these abilities that so far were mainly front of mind for large labs, how do I ensure security of my agents? How do I ensure the models follow the policies I want to prescribe? All that stuff. Those things that were front of mind for frontier labs are going to become front of mind for everyone For all enterprise as they adopt tools like Codex, like Claude Code, like OpenClaw. And so I think where the most where our expansion and a lot of the reason, the work behind our series or the intention behind a lot of our Series A, it is explicitly to take a lot of the technology that we have been developing I won't say for but in conjunction with both enterprise and the large labs, and really scale the deployments on enterprise. So what I see happening in the next year from the Gray Swan side is real growth in terms of the number of AI companies deploying this technology because it becomes central to their operations. Research-wise, I think I've already talked about some, right? The science, the agentification of all science. Well, let's start with science of AI, and I think, I think that, we always want to do other sciences, right? Let's, let's, let's, let's do AI for physics.Matt [00:56:06]: Introspective.Zico [00:56:07]: Let's just, let's just start with AI science. That needs a lot of work right now, right?Matt [00:56:11]: Put your own mask on before helping others.Zico [00:56:12]: Exactly. So I think actually that's what I'm most excited about right now in the research side. And as it applies to this, I think it's, it's in things like understanding models better, but doing it through the power of agents.Matt [00:56:22]: One thing that, I've been very encouraged by for really only the past two or three months that I think, the pace at which this has happened has been increasing, and I think this is going to continue to be a thing, is people who start to build an agent and don't take it all the way to “We've finished this. We think it's, it's great, and now it's, in front of customers or it's in front of the entire organization.” they have this epiphany before they get there that whatever prompts I put in I need a solution here. I understand that there are real risks, right? I understand that, this is a weird and interesting and really capable model that I'm working with, but if I don't, put more measures in place, to make sure that it stays safe and does behaves the way that I want it to. People coming to us proactively, knowing that they need a real solution, I think that's very encouraging, and I think it's a sign of agents landing outside of just the frontier labs and the research community and scientists and so forth. people are starting to get it, and I think that's great. Looking forward to all of the amazing apps that people are going to build on top of these models and the security that will help them stand up.Private Arenas, Red Teaming Markets, and AI InsuranceSwyx [00:57:39]: Is there a future where your customers are part of the arena? ‘cause I think these are, basically these are Right? these are, these are, independent entities. They're There's a guy in Australia who's, your number one. But at some point you have the network effect where you start having enterprise use cases, actually in inside of this public domain.Matt [00:57:59]: Oh, I see. You mean testing enterprise, deployments inside the arena. So we have had, the situation where people join the arena. They're maybe cybersecurity professionals. They get interested in AI security. They come across the arena, and then eventually they become a customer, when their organization needs solution.Swyx [00:58:17]: How often does that happen?Matt [00:58:17]: Not a huge number of times. But there are a lot of thoughtful, people that come from a cybersecurity background that have found their way there. So enterprises are just always, I think, going to be more paranoid about putting, their custom agent that's, deployment, still in development, up on this public platform for anybody to come hit. What we have done is worked to make private arenas where some subset of the contestants, who we've, We know well, theySwyx [00:58:54]: And what do they work on?Matt [00:58:55]: What do they work on?Swyx [00:58:55]: Do What was the class of problem they work on that would require a private arena?Matt [00:59:00]: Oh, pretty much any enterprise application. That's the point. Yeah. enterprises are not willing to put up their deployment agentsSwyx [00:59:07]: Oh, that's greatMatt [00:59:07]: On the arena for For the general public to come hit. They're fine if it's, 20 people that we've handpicked from the arena.Swyx [00:59:14]: Just for listeners who might be interested What do I make as a participant? What's on the table here?Matt [00:59:20]: Well, so for the for the public competitions We communicate a pricing and incentive structure, upfront, and it, and it differs for each arena, right? ‘Cause designing, the right set of incentives to get people focused on finding useful vulnerabilities and problems without reward hacking and just finding, de minimis things is,Swyx [00:59:47]: Are you human judging the reward hacks if it happens?Matt [00:59:50]: Sometimes, yes.Swyx [00:59:51]: Oh, that's messy.Zico [00:59:53]: Well, so we have a lot of automated graders, right? A lot of automated graders. But ultimately, if they can beat all those graders, there is a humanMatt [00:59:59]: There in the YeahZico [01:00:00]: That can, that can take a look at the at theMatt [01:00:01]: Oh, okay. Yep. And we work with the UKEC and Casey and so forth. they'll come in and work as independent judges and evaluators and lend their expertise to that.Swyx [01:00:11]: You're, you're a community that, any enterprise can call on and that's, that's really useful, data actually. It's almost McCore for red teaming.Matt [01:00:22]: For red teaming.Swyx [01:00:25]: One of our upcoming guests is, on the other side of this, the AI, underwriting company. I don't know if you've come across that.Matt [01:00:30]: Oh, yeah. Absolutely.Zico [01:00:31]: Oh, wait. They're, they're one of the logos there. I know that we have the other one.Swyx [01:00:34]: What do you yeah, what do you what do you think of that market?Zico [01:00:36]: Oh, I think it's great.Swyx [01:00:37]: Because it's such an interestingZico [01:00:38]: And and I think it pairs extremely well with our model, right? Because how do you assess the risk of a company's AI deployment? Well, use a tool like Shade, or use Arena, right? And that's And we have And that's actually a lot of the work we've done with them is exactly for that thing. And then if a company finds this level of risk, but wants, so they can't be insured because they're too risky, wants to reduce their risk, what do you do there? I don't think look, we shouldn't be the only provider here, but what do you do there? Well, you put safety systems around your model, right? Including things like Cygnal. So it pairs extremely well because what in some sense we can be is a, author. I don't We're not getting there yet, so I don't this is hypothetical. I want, I wanted to emphasize. But we can be in some sense a authorized partner with them, so that they can do more than just say, “Hey, you're uninsurable.” They can both assess it more rigorously with tools like Shade and other tools as well, and then they can prescribe mitigations when there are problems using tools like Cygnal.AI Insurance, Compliance, and the Gray Swan EventZico [01:01:44]: So it's incredibly goodMatt [01:01:46]: These two models fit together incredibly well. They also bring us customers. Many customers want protection against bad outcomes, insurance for when things go wrong, and help staying compliant. Being out of compliance is also a risk.Swyx [01:02:10]: I think AUC is fantastic and got on this early. The parallel to cyber insurance is clear. When you apply for cyber insurance, you document the measures you have in place: detection, response, and controls. Structurally, they need an arm's-length third party.

What's the most underrated tool in the motion design workflow? The Creative Brief.In today's episode, Justin and Audrey Havey of Sword and Shield sit down with us to break down the creative process behind their launch ident: a hand-drawn, frame-by-frame battle sequence built on intention, world-building, and one very special Easter egg of a Favorite Frame™. We go deep on utilizing the creative brief as the north star of any project, what it really means to build an artist-first studio, and why the best work happens when you let go of control and trust the people you've hired.If you're someone who's obsessed with both the process and the craft of motion design — this one's for you!TIMESTAMPS:0:00 – Intro0:43 – Audrey & Justin's Origin Stories8:10 – The Brand Idea Born on Daily Walks11:22 – Introducing Audrey & Justin's Favorite Frame™14:24 – The Easter Egg: When an Artist Signs Her Work23:34 – The Brief Is the Golden Goose in Motion Design27:44 – World Building as a Brand Animation Strategy39:54 – How Story Arc Shapes the Motion Design Process45:47 – Challenges, Rewards & Pivots53:01 – Their Favorite Frame™ Because…CONNECT & FOLLOW:Spotify → https://spoti.fi/3K8UDd7Apple Podcasts → https://podcasts.apple.com/us/podcast/styleframe-saturdays/id1607658120Amazon Music → https://amzn.in/d/0cziMYRNGUEST LINKS/RESOURCES:Sword & Shield: https://swordandshield.tv/Columbus College of Art & Design: https://www.ccad.edu/Riot Games: https://www.riotgames.com/enCarvana: https://www.instagram.com/vandylgaming/Vandyl Gaming: https://www.instagram.com/vandylgaming/Jessica Rowden: https://jessicarowdenart.com/Kody Orris: https://www.kodyorris.com/Ghost of Tsushima: https://www.ghostof-tsushima.com/Discovering the ‘Why' Behind Your Styleframes with Ryan Summers: https://youtu.be/ThJIz9esa4MNickelodeon: https://www.nick.com/Procreate: https://procreate.com/Maxon Cinema 4D: https://www.maxon.net/en/cinema-4dAdobe Photoshop: https://photoshop.adobe.com/?promoid=HHJ4XB3V&mv=other&mv2=ahome&lang=enAdobe After Effects: https://www.adobe.com/products/aftereffects.html*Riverside: https://riverside.fm/?utm_campaign=campaign_1&utm_medium=affiliate&utm_source=rewardful&via=styleframesatLofi Cassette by Harrison Amer (theme music licensed by Premiumbeat.com, https://www.premiumbeat.com/home)Permissions granted by the artist(s).Our podcast celebrates Motion Ideation — the raw brainstorming, early-stage thinking and lightbulb moments that shape everything before a single design or keyframe exists. Because we believe great motion design starts with one Favorite Frame™ and the fresh ideas behind it.Styleframe Saturdays is a Formerle-branded podcast, and part of the Formerle brand family.By making a purchase through one of our affiliate links we will get a small commission at no additional cost to you. Rest assured that we would recommend these products regardless of their commission-based opportunities.

How do you build AI that actually understands you and the work you do? It all starts with having the right context.  We talk with Dropbox staff product manager Noorain Noorani and principal engineer Sean-Michael Lewis about the art of context engineering and how Dropbox connects to all the tools your team needs for work—so you get AI that works wherever you do.  ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

Modern work can be frustrating and chaotic—if you don't have the right tools. From context engineering to multimodal search, go behind the scenes and hear how Dropbox engineers are building AI that actually understands you, so you can focus on the work that matters most. If you're new to Working Smarter, we've travelled from the F1 track to the bottom of a lake, and heard real stories from chefs, doctors, lawyers, and founders about how AI is helping them do more of what they love about their jobs. But in our third season, we're talking to the people behind the tools—the engineers and product leaders building helpful, time-saving AI features into the Dropbox experience you already know and trust. You'll hear all about their work on agents, inference, security, and, of course, how the people building AI use AI themselves. ~ ~ ~  Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck.  Our theme song was composed by Doug Stuart.  Working Smarter is hosted by Matthew Braga. Thanks for listening!

OLD MODELS OF FILMMAKING HAVE CRASHED?From Kane Parsons and Backrooms to creators like Markiplier and Curry Barker, the path to becoming a filmmaker is changing.The question is no longer who will give you permission.The question is: what story are you going to tell?Follow @the.artistspodcast for #arts #culture #cinema#ArtisticRants13 #Filmmaking #CreatorEconomy #Backrooms #KaneParsons #TheArtistsPodcast

This is the Everyday AI episode we probably shoulda done a while ago....

Episode 176: In this episode of Critical Thinking - Bug Bounty Podcast we're joined by top Adobe hacker Jim Green to deep-dive AEM. We talk through Sling selectors, Permissions, and how to spot AEM Red Flags.Follow us on twitter at: https://x.com/ctbbpodcastGot any ideas and suggestions? Feel free to send us any feedback here: info@criticalthinkingpodcast.ioShoutout to YTCracker for the awesome intro music!====== Links ======Follow your hosts Rhynorater, rez0 and gr3pme on X: https://x.com/Rhynoraterhttps://x.com/rez0__https://x.com/gr3pmeCritical Research Lab:https://lab.ctbb.show/ Need a Pentest? We just launched CTBB Pentests!https://pentest.ctbb.show/Hack full time? Check out the Full-Time Hunter's Guild!https://ctbb.show/fthg====== Ways to Support CTBBPodcast ======Hop on the CTBB Discord at https://ctbb.show/discord!We also do Discord subs at $25, $10, and $5 - premium subscribers get access to private masterclasses, exploits, tools, scripts, un-redacted bug reports, etc.You can also find some hacker swag at https://ctbb.show/merch!Today's Sponsor: Adobe. Earn more for AI bugs with Adobe's new AI Tier! https://blog.adobe.com/security/adobe-expands-bug-bounty-program-to-incentivize-ai-security-researchAlso don't forget to also grab a 10% bonus for valid AI vulnerabilities in Adobe Stock and Lightroom Web. Use code: CTBB063026 in your report.Expires June 30, 2026. ====== This Week in Bug Bounty ======Scaling Bug Bounty triage in the AI era(https://www.yeswehack.com/security-best-practices/scaling-bug-bounty-triage-ai)The AI impact: a triager's perspectivehttps://www.intigriti.com/blog/business-insights/the-ai-impact-a-triagers-perspective====== Resources ======Sling Selectors - The Key to Unlocking AEM's Attack Surfacehttps://greenjam.co.uk/blog/sling-selectors/Just a Moment CTFhttps://poc.greenjam.co.uk/just-a-moment.htmlGeneral XSS jquery .text()https://poc.greenjam.co.uk/text-xss.htmlURL XXS Challengehttps://poc.greenjam.co.uk/url-xss.html====== Timestamps ======(00:00:00) Introduction(00:04:35) Background and AEM Bug(00:17:40) Sling Selectors & the Tech Stack(00:38:14) Permissions & Apache Sling Resolution(01:01:37) The Bugs & AEM Red Flags(01:31:55) Moment in Time CTF(01:40:38) General XSS jquery .text()(01:45:45) URL XXS Challenge

Ever wonder how top motion designers create title sequences that actually win major pitches? Or how they make their work feel truly cinematic and full of emotion instead of flat and generic?In today's episode, Toros Kose—title designer for Blade Runner 2049 and Top Gun: Maverick —breaks down his full creative process with everything from ideation and visual referencing to color theory and composition. And bonus, he also reveals what makes his frames feel so cinematic too!We'd also like to dedicate this episode to Toros's dear friend and industry legend, Danny Yount. May his legacy live on forever ❤️TIMESTAMPS:0:00 – Intro1:10 - Toros's Journey Into Motion Design4:37 - Blade Runner 2049 Styleframe Reveal, Early Ideation & Project Overview16:42 - How to Make Motion Design Feel More Human22:00 - Why Motion Designers Should Always Design With Animation in Mind25:47 - Toros Kose's Cinematic Design Fundamentals33:41 - Toros Kose's Design Philosophy: "Pay Attention To What You Pay Attention To"36:41 - How to Level Up in Motion Design: Study (and Copy) the Greats39:43 - How Milestone Moments Shape Your Motion Design Identity & Career43:57 - Challenges & Rewards of the Blade Runner 2049 Project46:00 - This is Toros Kose's Favorite Frame™ Because…CONNECT & FOLLOW:Instagram → https://www.instagram.com/styleframesat/Twitter → https://twitter.com/styleframesatFacebook → https://www.facebook.com/styleframesatLinkedIn → https://www.linkedin.com/showcase/styleframe-saturdays-podcastTODAY'S GUESTS & RESOURCESToros Kose's website: https://www.toroskose.com/OFF Festival: https://www.offf.barcelona/Sony Vegas: https://www.vegascreativesoftware.com/Hyper Island: https://hyperisland.com/en/Nick Campbell: https://www.instagram.com/nickvegas/Greyscale Gorilla: https://greyscalegorilla.com/Video Copilot: https://www.videocopilot.net/Blade Runner: https://www.imdb.com/title/tt0083658Blade Runner 2049: https://www.imdb.com/title/tt1856101/Prodigal Pictures: https://prodigalpictures.com/Danny Yount: https://www.dannyyount.com/Warner Brothers Pictures: https://www.warnerbros.com/Toros's Tenets: https://www.toroskose.com/010834858921Roger Deakins: https://www.imdb.com/name/nm0005683/Pinterest: https://www.pinterest.com/Insydium X-Particles: https://insydium.ltd/products/x-particles/Maxon Redshift: https://www.maxon.net/en/redshiftMaxon Cinema 4D: https://www.maxon.net/en/cinema-4dAdobe Photoshop: https://photoshop.adobe.com/?promoid=HHJ4XB3V&mv=other&mv2=ahome&lang=enAdobe After Effects: https://www.adobe.com/products/aftereffects.html*Riverside: https://riverside.fm/?utm_campaign=campaign_1&utm_medium=affiliate&utm_source=rewardful&via=styleframesatLofi Cassette by Harrison Amer (theme music licensed by Premiumbeat.com, https://www.premiumbeat.com/home)Permissions granted by the artist(s).Our podcast celebrates Motion Ideation — the raw brainstorming, early-stage thinking and lightbulb moments that shape everything before a single design or keyframe exists. Because we believe great motion design starts with one Favorite Frame™ and the fresh ideas behind it.Styleframe Saturdays is a Formerle-branded podcast, and part of the Formerle brand family.*By making a purchase through one of our affiliate links we will get a small commission at no additional cost to you. Rest assured that we would recommend these products regardless of their commission-based opportunities.

OpenAI's Codex is the best AI system on the planet.

After a 3 Month Sabbatical, the SE Crew is back to catch up on all the craziness in the community, and Baker talks about cocaine hippos!PLEASE LIKE, SUBSCRIBE, RATE, AND REVIEW ON ALL PLATFORMS: YouTube, Facebook, Apple Podcasts, Spotify, Spreaker, or wherever you listen!GET YOUR SASQUATCH EXPERIENCE GEAR FROM THE SQUATCH PRO STORE!Sean Forker hosts SASQUATCH EXPERIENCE, which also features Matt Arner, James Baker, Vance Nesbitt, and Henry May.Creative Consultants: Matt Knapp (Bigfoot Crossroads) & Les Sincavage (Xplorers: Seekers of the Truth). Show Executive Producer: Brian CorbinSpecial Thanks to all our Patreons:The Experiencers: Jeffreylee Matthis, Got Knockers!, Larry Sharpe, Scott Dieterele, and Tom MihokTrackcasters: Cindy BrewerThe Hollers: Gail Frederick, David Hickernell, Matt Arner, Laurie Nelson, and Lori WorthingtonWithout their support, this show would not be possible. For as little as $2 per month, please consider becoming one of our supporters on PATREON.Our show intro music, “It Comes At Night” by Adam Dib, is licensed to us for commercial use. “9-11 Bigfoot Call” is also used under Fair Use. Sean Forker and Gabriel Forker are credited with the intro and exit voiceover work. Sasquatch Experience Trailer music, “It's in the Fog” by Darren Curtis, is used with permission and attribution. If you'd like to hear a particular topic or guest, EMAIL US! Become a supporter of this podcast: https://www.spreaker.com/podcast/sasquatch-experience--4208641/support.Sasquatch Experience by Anomalis Entertainment, LLC  is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Based on a work at https://www.spreaker.com/show/sasquatch-experience.Permissions beyond the scope of this license may be available at https://www.sasquatchexperience.com/permission.

If you have any sort of connection to former congressman Barney Frank, please reach out to Graham!Graham Neray is CEO of Oso. Oso provides authorization, governance, and security for AI agents to help customers confidently control their agent footprint. The company was founded in 2019 for authorization-as-a-service more generally, and they have since found traction using their technology to secure AI adoption. The team has raised from some of the top investors in the world including Sequoia, Felicis, and Harpoon. Before Oso, Graham was at MongoDB where he started in product marketing before taking over as Chief of Staff in 2016. Over 7 years he helped the company grow revenue 250x and headcount 30x. In the episode we discuss the transformation of MongoDB over his tenure, the lessons that transferred (and the ones that didn't), the evolution of Oso, controversial takes on building in stealth and creating an open-core company, and a lot more.  https://www.osohq.com/

Join the 3-Day Clarity Experience, May 5–7. A live space for women in the long middle who are ready to stop doing it alone — not to get a fix, but to sit with the questions alongside a community of women in exactly the same place. Standard admission is $47, or $87 for VIP, which includes a private 45-minute call with Anne-Marie. https://annemariezanzal.com/3-day-clarity-experience/The fantasy is that one day you wake up and everything snaps into place — the marriage, the friendships, the way you dress, the way you pray. What nobody tells us is that for most of us, becoming happens at the speed of a glacier, not a lightning bolt.In this month's conversation, Anne-Marie Zanzal sits down with returning guest Anna Empey to explore the long middle — the space between knowing and acting, between the question and the certainty. They talk about why coming out is the end of the beginning, not the end of the story; why "I don't know yet" is a complete and honest answer; and why the grand reinvention is really a thousand small permissions stacked on top of each other.The conversation moves into the nervous system response that comes with this kind of change — the sleep that won't come, the body that won't settle — and the practices that help women stay with themselves while everything is moving. Anne-Marie and Anna also get into shame versus guilt, the cultural script that says coming out is only for the young, and why no one has to blow up her life to live an honest one.Whether a listener is four months into claiming a new identity or has been sitting with the question for years, this conversation is a reminder that she is not behind. She is already becoming.Coming Out & Beyond is available on Apple Podcasts and Spotify, with full video episodes on YouTube: https://youtu.be/g2AGyBj8JXUFor listeners who find today's conversation landing somewhere tender, Authentically Us offers an online community for women navigating identity questions in midlife and beyond — a place to belong while still figuring out what they're becoming. More information is available at https://community.annemariezanzal.com/users/onboarding/plans#ComingOutLaterInLife #LateBloomerLesbian #LGBTQPodcast #MidlifeAwakening #SacredBelonging

Join the 3-Day Clarity Experience, May 5–7. A live space for women in the long middle who are ready to stop doing it alone — not to get a fix, but to sit with the questions alongside a community of women in exactly the same place. Standard admission is $47, or $87 for VIP, which includes a private 45-minute call with Anne-Marie. https://annemariezanzal.com/3-day-clarity-experience/The fantasy is that one day you wake up and everything snaps into place — the marriage, the friendships, the way you dress, the way you pray. What nobody tells us is that for most of us, becoming happens at the speed of a glacier, not a lightning bolt.In this month's conversation, Anne-Marie Zanzal sits down with returning guest Anna Empey to explore the long middle — the space between knowing and acting, between the question and the certainty. They talk about why coming out is the end of the beginning, not the end of the story; why "I don't know yet" is a complete and honest answer; and why the grand reinvention is really a thousand small permissions stacked on top of each other.The conversation moves into the nervous system response that comes with this kind of change — the sleep that won't come, the body that won't settle — and the practices that help women stay with themselves while everything is moving. Anne-Marie and Anna also get into shame versus guilt, the cultural script that says coming out is only for the young, and why no one has to blow up her life to live an honest one.Whether a listener is four months into claiming a new identity or has been sitting with the question for years, this conversation is a reminder that she is not behind. She is already becoming.Coming Out & Beyond is available on Apple Podcasts and Spotify, with full video episodes on YouTube: https://youtu.be/g2AGyBj8JXUFor listeners who find today's conversation landing somewhere tender, Authentically Us offers an online community for women navigating identity questions in midlife and beyond — a place to belong while still figuring out what they're becoming. More information is available at https://community.annemariezanzal.com/users/onboarding/plans#ComingOutLaterInLife #LateBloomerLesbian #LGBTQPodcast #MidlifeAwakening #SacredBelonging

Nobody wakes up wanting an average life. We all want remarkable marriages, careers, and relationships. But how do you actually build that? After 15 years of helping over a million people and testing hundreds of ideas, I discovered it comes down to four permissions: permission to dream, permission to plan, permission to do, and permission to review. In this episode, I'm breaking down the DPDR system from my new book "Procrastination Proof" and showing you exactly how to use it for three hours, three months, or three years. You'll discover why planning is just visiting the future and taking notes, why you shouldn't quit your day job until you answer one critical question, and how to use this success loop to finally retire from procrastination. Plus, I'll tell you about the free quiz that reveals which of the four procrastination traps you're most likely to fall into. Whether you're a dreamer, perfectionist, hustler, or analyst, find out at jonacuff.com/quizIn This Episode:Order Procrastination Proof!You can grab a copy of my new book Procrastination Proof from your favorite bookstore or at my website!Make sure to follow me on Instagram and share with your friends!Sign up for my newsletter, Try This!Book me to speak at your event or to your team!Sign up for the Remarkable You Community today!Keep up with my book list on GoodReads! Have me speak at your next event!

A few Novembers ago, I set out for a hang-and-hunt on my favorite piece of public land in North Carolina. After over an hour of wandering, I stumbled across a hot white oak that was surrounded by fresh deer sign. Shortly after I set up, a young buck limped up to the acorns and stood perfectly for a shot. I couldn't have been more excited as I walked up to that scrappy six-point. But reality started tugging on my sleeve as I field dressed him. My...

We talk President Lai Ching-te's nixed state visit to Eswatini, the central government's general budget plan moving forward after more than six months in limbo and more. -- Hosting provided by SoundOn

Alexander Embiricos is the Head of Codex at OpenAI, leading the development of the company's flagship AI coding systems that power automated software generation, debugging and developer workflows. Under his leadership, Codex has become one of the most widely adopted AI developer platforms.  AGENDA: 05:13 Will Coding Be Automated? Why AI Could Create More Engineers, Not Fewer 07:17 Do We Need PMs? The "Undefined" Product Role and When It Matters 08:06 The Real AGI Bottleneck: Human Prompting, Validation, and "Too Much Effort" 13:04 Three Phases of Agents: Coding → Computer Use → Productized Workflows 13:52 Enterprise Reality Check: Security, Permissions, and Safe Agentic Browsing 17:57 Is Inference the New Sales and Marketing?  18:49 What % of Codex Was Written by AI? 21:33 Do OpenAI Use AI for Code Review? 23:31 Is there any stickiness to AI coding tools? 28:22 What Does "Winning" Mean at OpenAI? Mission, Competition, and Moats 32:04 The Future UI: Chat or Voice 34:10 Agent-to-Agent Workflows: Designing for Approvals, Compliance, and Automation 35:39 Do Coding Models Have a Data Moat? 36:50 How does Codex View Data: Will They Build Their Own Mercor and Turing? 37:27 How Does Codex View Consumer: Will They Compete with Lovable? 41:56 Benchmarks vs "Vibes": How People Actually Judge Models 42:43 Cursor's Edge and the Case for Building Your Own Models 47:37 Is SaaS Dead? What Still Defends Value (Humans + Systems of Record) 51:28 Talent Wars and Career Advice for New Engineers in the AI Era 01:01:03 Guardrails, the Fully AI-Managed Stack, and a 10-Year Vision for Everyone