Podcasts about pii

Nick Constantino and Brian Jungles dive into the surprising resurgence of direct mail marketing. From data-driven targeting to fraud-free impressions, they unpack why this “unsexy” channel is outperforming digital in today's AI-saturated landscape. Learn how tactile media is reclaiming its place in full-funnel strategies and why marketers should rethink their approach to brand and lead generation.✅ Key Takeaways:• Direct mail offers 100% deliverability and high-value targeting using PII and layered data.• Digital ad fraud is rampant—up to 50% of traffic can be fake or wasted.• Direct mail impressions are tactile, memorable, and often live in homes for weeks.• Integrated campaigns (mail + digital + CTV + retargeting) outperform siloed efforts.• Unique offers and strong creative are essential—don't reuse billboard/web ads.• Measurement tools like QR codes, call tracking, and A/B testing are now standard.• Success requires repetition—one-off mailers don't work.

Download Perplexity Comet: AI-native Browser; Web Adoption and Security Talk with Favour Obasi-Ike | Get exclusive SEO newsletters in your inbox.Perplexity AI's free "Comet" web browser, which occurred this past Thursday. We expressed excitement over this development, highlighting Comet's functionality as an AI-powered browser that can import Google Chrome extensions and act as a personal assistant, shopping, and email agent. The conversation extensively examines the implications of Comet's introduction on the browser market share, particularly in relation to the dominance of Google Chrome, and explores how this new tool affects Search Engine Optimization (SEO) strategies and content visibility for businesses. Finally, a significant portion of the discussion addresses crucial concerns regarding user privacy and data security when utilizing these advanced AI tools, emphasizing the need for caution and strategic use.Next Steps for Digital Marketing + SEO Services:>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Need SEO Services? Book a Complimentary SEO Discovery Call with Favour Obasi-Ike⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Need more information? Visit our Work and PLAY Entertainment website to learn about our digital marketing services.>> Visit our Official website for the best digital marketing, SEO, and AI strategies today!FAQs about this episode1. What is the Perplexity AI Comet Browser?Comet is an AI web browser released by Perplexity AI. Comet essentially integrates Perplexity AI capabilities into a browser format. The concept involves having an AI web browser, similar to using Google Chrome but with AI integration.2. When was the Comet browser released, and to whom?The free Comet browser was recently made available to everyone worldwide. It was announced on a Thursday. However, Comet was initially released to people who had Perplexity Max in July. This three-month period (July to October) allowed Perplexity to keep it exclusive within their beta program or exclusive community before releasing it universally.3. How can I download the Comet browser, and what platforms is it available on?You can download the Comet browser by visiting perplexity.ai/comment. It is available for both Mac and Windows.4. What are the key features and capabilities of the Comet browser?The Comet browser offers several features that distinguish it from traditional browsers:• Extension Import: You can import your Google Chrome extensions into the Comet AI browser.• Agentic Capabilities: It is described as a personal assistant that helps with many things. It can: ◦ Autonomously control browser actions, such as closing tabs and opening pages. ◦ Fill out forms. ◦ Control Google Drive. ◦ Shop for you. ◦ Send out emails, leveraging a feature called "background assistant".• Current Focus: It is currently heavily focused on the web, though a mobile app is anticipated, similar to the existing Google Chrome app and Perplexity app.5. Why did Perplexity AI release the Comet browser?Perplexity is doing this to gain market share and compete with major rivals, particularly Google. The current browser market is heavily dominated by Google Chrome, which holds about 72% of the market share (specifically cited as 71.77% to 71.86% recently).6. How is Perplexity AI related to Microsoft and other platforms?Perplexity is closely associated with Microsoft and Bing. The platforms are interconnected, as LinkedIn is also owned by Microsoft. It is noted that Microsoft is also involved with Copilot and is "somewhere in the mix" of OpenAI/ChatGPT content, further connecting it to Comet.7. What are the major concerns regarding security and privacy with agentic AI browsers?The primary concerns revolve around security, privacy, and user adoption. Since the Comet browser can autonomously control browser actions, access Google Drive, and fill out forms, there are questions about how much security is provided.• Data Compromise: One critical concern is that if a company's chosen AI platform (like Comet) lacks necessary security measures, a client could be exposed to a hack, potentially compromising years of hard work.• Lack of Regulation: There is a belief that there is not enough regulation surrounding privacy in the AI space, often favoring convenience and productivity over individual privacy.8. How will AI search browsers impact SEO and business visibility?AI search models are changing how businesses achieve visibility:• Beyond Top 10: AI models are no longer just scanning the top 10 search pages; they are scanning anywhere between 10 to 40 links or sources. Businesses should aim to be in this "Top 40 listing".• Platform Diversity: Visibility is achieved when a brand is interconnected across various platforms, including LinkedIn, YouTube, Google, Pinterest, the website, blogs, videos, audios, and podcasts.• LinkedIn Importance: If Perplexity uses LinkedIn as one of its information sources, having a complete and active LinkedIn profile is significant for search results.• Contextual Content: Content needs to be contextually relevant, moving beyond just typing basic search phrases like "best restaurant near me".• SEO Relevance: SEO remains important; even if AI models like ChatGPT handle e-commerce orders, they are still pulling information from sources with high domain authority, which is based on SEO principles.9. What are the best practices for leveraging AI tools like Comet?Users should adopt a strategic approach when using these new AI tools:• Strategy and Learning: Use AI to strategize, discover different angles, and find solutions to problems you haven't considered. Ask AI how to improve upon an idea or find what is missing from your strategy.• Strategy vs. Dependence: Use AI as a tool to improve yourself and learn, but do not depend on it.• Privacy Protection: Exercise caution regarding privacy. Do not give out personal identifying information (PII) such as your specific address, phone number, or names of family members. Ask general questions instead of highly specific personal ones.• Prompt Awareness: Be aware that all prompts written into ChatGPT are typically indexed into Google unless you change your settings.Digital Marketing SEO Resources:>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our exclusive SEO Marketing community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Read SEO Articles>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Need SEO Services? Book a Complimentary SEO Discovery Call with Favour Obasi-Ike⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the We Don't PLAY Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

“Our approach is simple: remove the PII from the data stream, and you don't have to worry about compliance,” said Bill Placke, President, Americas at SecurePII. At WebexOne in San Diego, Doug Green, Publisher of Technology Reseller News, spoke with Jason Thals, COO of BroadSource, and Placke of SecurePII about their finalist recognition in Cisco's Dynamic Duo competition. The joint solution, built on Cisco Webex Contact Center, is designed to unlock AI's potential by enabling enterprises to leverage large language models without exposing sensitive personal data. SecurePII's flagship product, SecureCall, was purpose-built for Webex (and also available on Genesys) to deliver PCI compliance while removing personally identifiable information from voice interactions. This enables organizations to deploy AI and agentic automation confidently, without the regulatory risk tied to data privacy laws across the U.S., GDPR, and beyond. Thals emphasized BroadSource's role in delivering services that complement CCaaS and UCaaS platforms globally, while Placke framed the opportunity for Cisco partners: “This is a super easy bolt-on, available in the Webex App Hub. Customers can be up and running in 30 minutes and compliant.” The collaboration, already proven with a government-regulated client in Australia, is industry-agnostic and scalable from small deployments to 50,000+ users. For Cisco resellers, it represents a powerful, sticky service that integrates seamlessly into channel models while helping enterprises stay compliant as they modernize customer engagement. Learn more at BroadSource and SecurePII.

In this episode, we talk about practical guardrails for LLMs with data scientist Nicholas Brathwaite. We focus on how to stop PII leaks, retrieve data, and evaluate safety with real limits. We weigh managed solutions like AWS Bedrock against open-source approaches and discuss when to skip LLMs altogether.• Why guardrails matter for PII, secrets, and access control• Where to place controls across prompt, training, and output• Prompt injection, jailbreaks, and adversarial handling• RAG design with vector DB separation and permissions• Evaluation methods, risk scoring, and cost trade-offs• AWS Bedrock guardrails vs open-source customization• Domain-adapted safety models and policy matching• When deterministic systems beat LLM complexityThis episode is part of our "AI in Practice” series, where we invite guests to talk about the reality of their work in AI. From hands-on development to scientific research, be sure to check out other episodes under this heading in our listings.Related research:Building trustworthy AI: Guardrail technologies and strategies (N. Brathwaite)Nic's GitHubWhat did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics: LinkedIn - Episode summaries, shares of cited articles, and more. YouTube - Was it something that we said? Good. Share your favorite quotes. Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.

CISA gives federal agencies 24 hours to patch a critical Cisco firewall bug. Researchers uncover the first known malicious MCP server used in a supply chain attack. The New York SIM card threat may have been overblown. Microsoft tags a new variant of the XCSSET macOS malware. An exposed auto insurance claims database puts PII at risk. Amazon will pay $2.5 billion to settle dark pattern allegations. Researchers uncover North Korea's hybrid playbook of cybercrime and insider threats. An old Hikvision security camera vulnerability rears its ugly head. Dan Trujillo from the Air Force Research Laboratory's Space Vehicles Directorate joins Maria Varmazis, host of T-Minus Space Daily to discuss how his team is securing satellites and space systems from cyber threats. DOGE delivers dysfunction, disarray, and disappointment. Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn.CyberWire Guest Dan Trujillo from the Air Force Research Laboratory's Space Vehicles Directorate joins Maria Varmazis, host of T-Minus Space Daily to discuss how his team is securing satellites and space systems from cyber threats and also shares advice for breaking into the fast-growing field of space cybersecurity Selected Reading Federal agencies given one day to patch exploited Cisco firewall bugs (The Record) First malicious MCP Server discovered, stealing data from AI-Powered email systems (Beyond Machines) Secret Service faces backlash over SIM farm bust as experts challenge threat claims (Metacurity) Microsoft warns of new XCSSET macOS malware variant targeting Xcode devs (Bleeping Computer) Microsoft cuts off cloud services to Israeli military unit after report of storing Palestinians' phone calls (CNBC) Auto Insurance Platform Exposed Over 5 Million Records Including Documents Containing PII (Website Planet) Amazon pays $2.5 billion to settle Prime memberships lawsuit (Bleeping Computer) DeceptiveDevelopment: From primitive crypto theft to sophisticated AI-based deception (We Live Security) Critical 8 years old Hikvision Camera flaw actively exploited again (Beyond Machines) The Story of DOGE, as Told by Federal Workers (WIRED) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? You too can reach the most influential leaders and operators in the industry. Here's our media kit. Contact us at cyberwire@n2k.com to request more info. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

Security leaders from CyberArk, Fortra, and Sysdig share actionable strategies for securely implementing generative AI and reveal real-world insights on data protection and agent management.Topics Include:Panel explores practical security approaches for GenAI from prototype to productionThree-phase framework discussed: planning, pre-production, and production security considerationsSecurity must be built-in from start - data foundation is criticalUnderstanding data location, usage, transformation, and regulatory requirements is essentialFortra's security conglomerate approach integrates with AWS native tools and partnersMachine data initially easier for compliance - no PII or HIPAA concernsIdentity paradigm shift: agents can dynamically take human and non-human roles97% of organizations using AI tools lack identity and access policiesSecurity responsibility increases as you move up the customization stackOWASP Top 10 for GenAI addresses prompt injection and data poisoningRigorous model testing including adversarial attacks before deployment is crucialSysdig spent 6-9 months stress testing their agent before production releaseTension exists between moving fast and implementing proper security controlsDifferent security approaches needed based on data sensitivity and model usageZero-standing privilege and intent-based policies critical for agent managementMulti-agent systems create "Internet of Agents" with exponentially multiplying risksDiscovery challenge: finding where GenAI is running across enterprise environmentsAPI security and gateway protection becoming critical with acceptable latencyTop customer need: translating written AI policies into actionable controlsThreat modeling should focus on impact rather than just vulnerability severityParticipants:Prashant Tyagi - Go-To-Market Identity Security Technology Strategy Lead, CyberArkMike Reed – Field CISO, Cloud Security & AI, FortraZaher Hulays – Vice President Strategic Partnerships, SysdigMatthew Girdharry - WW Leader for Observability & Security Partnerships, Amazon Web ServicesFurther Links:CyberArk: Website – LinkedIn – AWS MarketplaceFortra: Website – LinkedIn – AWS MarketplaceSysdig: Website – LinkedIn – AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

On April 4, 2025, I presented live on the topic of the shifting paradigm of billable hour and serving new legal market opportunities. I presented alongside Clio's Lawyer in Resident, Joshua Lenon. Here are the top 5 takeaways:* AI Will Automate a Large Portion of Legal WorkUp to 75% of all hourly billable work in law firms is projected to be automatable by AI in the coming years. This shift is already underway, with rapid adoption of AI tools across firms of all sizes, especially in mid-sized and larger firms.* The Billable Hour Model Is Becoming ObsoleteAs AI drastically reduces the time required for many legal tasks, the traditional billable hour model is increasingly unsustainable. Flat fees, subscriptions, and value-based billing are emerging as more client-friendly and profitable alternatives, especially as clients become more aware of AI's capabilities.* The Latent Legal Market Is a Massive OpportunityThere is a huge unmet demand for legal services—estimated at over $1.3 trillion in the US alone. By leveraging AI and moving away from billable hours, lawyers can serve more clients, offer greater pricing certainty, and tap into this latent market.* Industry-Specific AI Tools and Data Security Are EssentialGeneric AI tools are not reliable sources of truth for legal work. Lawyers should prioritize industry-specific AI solutions that use retrieval augmented generation (RAG) and ensure privacy, security, and compliance (e.g., SOC 2, HIPAA). Using the right tools helps avoid ethical pitfalls and increases accuracy.* Client Expectations and Legal Practice Are EvolvingMost clients either prefer or are indifferent to their lawyers using AI, and younger generations are especially open to it. Lawyers must focus on delivering value, efficiency, and transparency. Adopting AI and new billing models not only meets client expectations but also positions firms for future success.__________________________Here's a link to the slide deck that goes with the presentation.Want to maximize your law firm? Get your ticket to MaxLawCon!Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In if you couldn't make it live.I've partnered with Pii to make it easy for you to purchase the hardware I use in my law firm: (1) Studio Setup; (2) Midrange Setup; (3) Highrange Setup.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

Christine Russo, host and creator of What Just Happened, sits with Ethan Chernofsky of Placer.ai.Placer.ai was built with privacy at its core. From its 2018 launch, the company avoided collecting personally identifiable information (PII), instead focusing on anonymized, aggregate data. This approach aligned with GDPR and CCPA regulations, allowing Placer to demonstrate that location intelligence can be both privacy-centric and commercially valuable. While this choice meant leaving some revenue opportunities (like hyper-targeted advertising) on the table, it reinforced trust, credibility, and long-term sustainability.Two major misconceptions surfaced in the discussion:Data replaces intuition. Many assumed that advanced analytics would replace industry experience and gut instinct. In reality, Placer frames data as an empowerment tool—complementary to human judgment, not a substitute.Visits equal transactions. A common misunderstanding is that foot traffic should directly correlate to sales. Instead, visits represent multiple forms of value: discovery, intent, pickup, consideration, and brand engagement. This broader view reframes physical stores as multi-purpose platforms for marketing, fulfillment, and consumer connection, not just sales points.The conversation emphasized how retail decision-making is evolving:From outdated tools to scalable intelligence. The industry shifted from handheld “clickers” and gut instinct toward data-driven decision frameworks that still honor human experience but make it actionable and scalable.The pandemic's unexpected boost. Rather than killing physical retail, COVID-19 ultimately strengthened it, highlighting the resilience and adaptability of brick-and-mortar models.Data as a universal language. Placer's insights became a common currency across verticals—real estate, retail, finance, CPG, and advertising—spurring new ways to measure impact, optimize inventory, and harmonize digital with physical.The future of insights in the AI era. With AI simplifying access to information, the differentiator won't just be data but the decisions leaders make. Trust, creativity, and the ability to “zag” when others “zig” will define competitive advantage.

Here are the top 5 takeaways from this episode with Ray Allen of ContractsCounsel:* ContractsCounsel is Transforming Legal Services with a Marketplace Model:ContractsCounsel connects consumers, small businesses, and startups with lawyers through a competitive, flat-fee proposal system. The platform emphasizes transparency, defined scope of work, and easy communication, making legal services more accessible and predictable for clients.* Flat Fees and Productized Legal Services Reduce Disputes and Increase Satisfaction:The platform encourages lawyers to offer fixed-fee services, which helps clients understand costs upfront and reduces billing disputes. Data from ContractsCounsel shows that disputes are rare, especially with flat-fee arrangements, and user satisfaction is high (average rating 4.9/5).* Subscription and Instant Bid Features Enable Lawyers to Modernize Their Practice:ContractsCounsel offers tools like instant bids (pre-set proposals for common services) and subscription-based offerings (e.g., monthly legal chat access). These features help lawyers productize their services, save time, and create recurring revenue streams, while also providing clients with affordable, ongoing legal support.* The Legal Market Opportunity is Vast and Largely Untapped:A significant portion of legal needs in the U.S. go unmet due to traditional billing models and lack of transparency. By shifting to fixed fees and subscription models, lawyers can tap into a much larger market—potentially worth over a trillion dollars—by serving clients who previously avoided legal help due to cost uncertainty.* Legal Tech, AI, and Passive Income are Shaping the Future of Law:The role of AI tools, legal chatbots, and digital product marketplaces (like selling legal templates) in the legal industry is growing. Lawyers who embrace technology, automation, and new business models (such as selling templates or offering AI-powered information bots) will be better positioned to serve clients and generate passive income.__________________________Learn more about ContractsCounsel.Want to maximize your law firm? Get your ticket to MaxLawCon!Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In if you couldn't make it live.I've partnered with Pii to make it easy for you to purchase the hardware I use in my law firm: (1) Studio Setup; (2) Midrange Setup; (3) Highrange Setup.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

In the leadership and communications segment, Lack of board access: The No. 1 factor for CISO dissatisfaction, Pressure on CISOs to stay silent about security incidents growing, The Secret to Building a High-Performing Team, and more! Jackie McGuire sits down with Chuck Randolph, SVP of Strategic Intelligence & Security at 360 Privacy, for a gripping conversation about the evolution of executive protection in the digital age. With over 30 years of experience, Chuck shares how targeted violence has shifted from physical threats to online ideation—and why it now starts with a click. From PII abuse to unregulated data brokers, generative AI manipulation, and real-world convergence of cyber and physical risks—this is a must-watch for CISOs, CSOs, CEOs, and anyone navigating modern threat landscapes. Hear real-world examples, including shocking stories of doxxing, AI-fueled radicalization, and the hidden dangers of digital exhaust. Whether you're in cyber, physical security, or executive leadership, this interview lays out the urgent need for converged risk strategies, narrative control, and a new approach to duty of care in a remote-first world. Learn what every security leader needs to do now to protect key personnel, prevent exploitation, and build a unified, proactive risk posture. This segment is sponsored by 360 Privacy. Learn how to integrate privacy and protective intelligence to get ahead of the next threat vector at https://securityweekly.com/360privacybh! In this exclusive Black Hat 2025 interview, CyberRisk TV host Matt Alderman sits down with Tom Pore, AVP of Sales Engineering at Pentera, to dive into the rapidly evolving world of AI-driven cyberattacks. What's happening? Attackers are already using AI and LLMs to launch thousands of attacks per second—targeting modern web apps, exploiting PII, and bypassing traditional testing methods. Tom explains how automated AI payload generation, context-aware red teaming, and language/system-aware attack modeling are reshaping the security landscape. The twist? Pentera flips the script by empowering security teams to think like an attacker—using continuous, AI-powered penetration testing to uncover hidden risks before threat actors do. This includes finding hardcoded credentials, leveraging leaked identities, and pivoting across systems just like real adversaries. To learn more about Pentera's proactive Ransomware testing please visit: https://securityweekly.com/penterabh Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-413

In the leadership and communications segment, Lack of board access: The No. 1 factor for CISO dissatisfaction, Pressure on CISOs to stay silent about security incidents growing, The Secret to Building a High-Performing Team, and more! Jackie McGuire sits down with Chuck Randolph, SVP of Strategic Intelligence & Security at 360 Privacy, for a gripping conversation about the evolution of executive protection in the digital age. With over 30 years of experience, Chuck shares how targeted violence has shifted from physical threats to online ideation—and why it now starts with a click. From PII abuse to unregulated data brokers, generative AI manipulation, and real-world convergence of cyber and physical risks—this is a must-watch for CISOs, CSOs, CEOs, and anyone navigating modern threat landscapes. Hear real-world examples, including shocking stories of doxxing, AI-fueled radicalization, and the hidden dangers of digital exhaust. Whether you're in cyber, physical security, or executive leadership, this interview lays out the urgent need for converged risk strategies, narrative control, and a new approach to duty of care in a remote-first world. Learn what every security leader needs to do now to protect key personnel, prevent exploitation, and build a unified, proactive risk posture. This segment is sponsored by 360 Privacy. Learn how to integrate privacy and protective intelligence to get ahead of the next threat vector at https://securityweekly.com/360privacybh! In this exclusive Black Hat 2025 interview, CyberRisk TV host Matt Alderman sits down with Tom Pore, AVP of Sales Engineering at Pentera, to dive into the rapidly evolving world of AI-driven cyberattacks. What's happening? Attackers are already using AI and LLMs to launch thousands of attacks per second—targeting modern web apps, exploiting PII, and bypassing traditional testing methods. Tom explains how automated AI payload generation, context-aware red teaming, and language/system-aware attack modeling are reshaping the security landscape. The twist? Pentera flips the script by empowering security teams to think like an attacker—using continuous, AI-powered penetration testing to uncover hidden risks before threat actors do. This includes finding hardcoded credentials, leveraging leaked identities, and pivoting across systems just like real adversaries. To learn more about Pentera's proactive Ransomware testing please visit: https://securityweekly.com/penterabh Show Notes: https://securityweekly.com/bsw-413

NumberEight converts mobile sensor data into contextual audience segments without capturing PII, addressing the fundamental breakdown of cookie-based targeting as media consumption fragments across podcasts, gaming, and connected TV. What began as a thesis project for contextual SoundCloud recommendations has evolved into a B2B data platform serving podcast platforms, media sales houses, and agencies. In this episode of Category Visionaries, we sat down with Abhishek Sen to unpack how NumberEight navigates the complex adtech ecosystem and the tactical GTM strategies that drive their expansion across multiple customer segments simultaneously. Topics Discussed: How NumberEight evolved from a Netherlands thesis project (contextual SoundCloud recommendations) to solving adtech's identity crisis Technical architecture: converting mobile sensor data to contextual audience segments without PII collection Multi-segment GTM approach across podcast platforms (AdSwizz, Triton), media sales houses, and agencies Why the company targets podcasting and gaming simultaneously despite different data density challenges Conference strategy: 45+ targeted meetings per event while completely avoiding booths Building category credibility through IAB Tech Lab standards work and white paper contributions The breakdown of cookie-based targeting as consumption fragments beyond web browsers GTM Lessons For B2B Founders: Execute systematic conference preparation to maximize deal flow: Sen books 45+ targeted meetings across 4-day conferences like Cannes Lions through advance relationship mapping and mutual connection identification. The tactical framework: pre-research each prospect's annual priorities, identify shared connections for warm introductions, and plan specific value propositions for each conversation. Execute daily follow-up during the conference to prevent pipeline degradation. Sen's insight: "Prep is incredibly important... we evaluate okay, Brett, head of monetization at ABC Company. Who does Brett know that I know? What is the actual proposition we want to discuss?" Avoid booth competition when capital-constrained: NumberEight deliberately avoids exhibition booths at major conferences, recognizing the futility of competing against Amazon's "entire city mockups" and Google's massive displays. Instead, they focus on authentic relationship building through targeted meetings and dinner sponsorships. The strategic principle: startups should leverage their authenticity advantage rather than attempting to out-spend established players in awareness channels where they're fundamentally disadvantaged. Maintain strict messaging separation between investor and customer tracks: Sen emphasizes the critical disconnect between vision-focused investor pitches and problem-focused customer conversations. His customer insight: "You tell any customer you're going to revolutionize... they're like 'man, you make me money, I'll be your friend.'" The implementation: develop completely separate messaging frameworks where investor decks emphasize market transformation while customer presentations focus exclusively on measurable business impact and revenue generation. Build category authority through standards body participation: NumberEight invests significant engineering resources in IAB Tech Lab white papers and industry standards development without direct revenue impact. This work establishes credibility when defining new data categories in established industries. Sen's co-founder leads technical working groups on identity-less targeting standards. The strategic value: "If you're trying to change the game, you have to be seen as someone giving back to the ecosystem and that helps drive your credibility." Time market entry around regulatory and consumption pattern shifts: NumberEight's positioning leverages two simultaneous disruptions: privacy regulation breakdown of cookie-based targeting and consumption fragmentation beyond web browsers. Sen identifies the core market inefficiency: "Consumption has moved beyond the web... but the data companies, in terms of how data is actually collected, hasn't changed. There's a mismatch." Founders should identify regulatory or technological shifts that create incumbent solution inadequacy and time market entry accordingly. Focus on vertical-specific events over broad industry conferences: NumberEight exclusively attends podcasting-focused (specific platforms), gaming-focused, or adtech-specific conferences rather than generalist marketing events. Sen explains: "We don't attend any conferences that are generalistic... The ones we attend are very focused on either podcasting or gaming or adtech focused ones. That's where we get the most bang for buck." This concentration strategy yields higher prospect quality and more productive pipeline development than broad industry networking.   //   Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.  www.GlobalTalent.co   //   Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM   

In the leadership and communications segment, Lack of board access: The No. 1 factor for CISO dissatisfaction, Pressure on CISOs to stay silent about security incidents growing, The Secret to Building a High-Performing Team, and more! Jackie McGuire sits down with Chuck Randolph, SVP of Strategic Intelligence & Security at 360 Privacy, for a gripping conversation about the evolution of executive protection in the digital age. With over 30 years of experience, Chuck shares how targeted violence has shifted from physical threats to online ideation—and why it now starts with a click. From PII abuse to unregulated data brokers, generative AI manipulation, and real-world convergence of cyber and physical risks—this is a must-watch for CISOs, CSOs, CEOs, and anyone navigating modern threat landscapes. Hear real-world examples, including shocking stories of doxxing, AI-fueled radicalization, and the hidden dangers of digital exhaust. Whether you're in cyber, physical security, or executive leadership, this interview lays out the urgent need for converged risk strategies, narrative control, and a new approach to duty of care in a remote-first world. Learn what every security leader needs to do now to protect key personnel, prevent exploitation, and build a unified, proactive risk posture. This segment is sponsored by 360 Privacy. Learn how to integrate privacy and protective intelligence to get ahead of the next threat vector at https://securityweekly.com/360privacybh! In this exclusive Black Hat 2025 interview, CyberRisk TV host Matt Alderman sits down with Tom Pore, AVP of Sales Engineering at Pentera, to dive into the rapidly evolving world of AI-driven cyberattacks. What's happening? Attackers are already using AI and LLMs to launch thousands of attacks per second—targeting modern web apps, exploiting PII, and bypassing traditional testing methods. Tom explains how automated AI payload generation, context-aware red teaming, and language/system-aware attack modeling are reshaping the security landscape. The twist? Pentera flips the script by empowering security teams to think like an attacker—using continuous, AI-powered penetration testing to uncover hidden risks before threat actors do. This includes finding hardcoded credentials, leveraging leaked identities, and pivoting across systems just like real adversaries. To learn more about Pentera's proactive Ransomware testing please visit: https://securityweekly.com/penterabh Visit https://www.securityweekly.com/bsw for all the latest episodes! Show Notes: https://securityweekly.com/bsw-413

In the leadership and communications segment, Lack of board access: The No. 1 factor for CISO dissatisfaction, Pressure on CISOs to stay silent about security incidents growing, The Secret to Building a High-Performing Team, and more! Jackie McGuire sits down with Chuck Randolph, SVP of Strategic Intelligence & Security at 360 Privacy, for a gripping conversation about the evolution of executive protection in the digital age. With over 30 years of experience, Chuck shares how targeted violence has shifted from physical threats to online ideation—and why it now starts with a click. From PII abuse to unregulated data brokers, generative AI manipulation, and real-world convergence of cyber and physical risks—this is a must-watch for CISOs, CSOs, CEOs, and anyone navigating modern threat landscapes. Hear real-world examples, including shocking stories of doxxing, AI-fueled radicalization, and the hidden dangers of digital exhaust. Whether you're in cyber, physical security, or executive leadership, this interview lays out the urgent need for converged risk strategies, narrative control, and a new approach to duty of care in a remote-first world. Learn what every security leader needs to do now to protect key personnel, prevent exploitation, and build a unified, proactive risk posture. This segment is sponsored by 360 Privacy. Learn how to integrate privacy and protective intelligence to get ahead of the next threat vector at https://securityweekly.com/360privacybh! In this exclusive Black Hat 2025 interview, CyberRisk TV host Matt Alderman sits down with Tom Pore, AVP of Sales Engineering at Pentera, to dive into the rapidly evolving world of AI-driven cyberattacks. What's happening? Attackers are already using AI and LLMs to launch thousands of attacks per second—targeting modern web apps, exploiting PII, and bypassing traditional testing methods. Tom explains how automated AI payload generation, context-aware red teaming, and language/system-aware attack modeling are reshaping the security landscape. The twist? Pentera flips the script by empowering security teams to think like an attacker—using continuous, AI-powered penetration testing to uncover hidden risks before threat actors do. This includes finding hardcoded credentials, leveraging leaked identities, and pivoting across systems just like real adversaries. To learn more about Pentera's proactive Ransomware testing please visit: https://securityweekly.com/penterabh Show Notes: https://securityweekly.com/bsw-413

Top 5 Takeaways from my interview with Mike Payne of Boss Advisors:1. Embracing Alternative Business Structures (ABS):Mike Payne was an early adopter of Arizona's Alternative Business Structure for law firms, allowing him to merge his law and accounting practices. This move reduced administrative burdens, enabled non-lawyer ownership, and positioned his firm as a pioneer, paving the way for larger firms to follow.2. Subscription and Flat Fee Model Over Hourly Billing:Mike's firm operates almost entirely on flat fees or subscriptions, avoiding hourly billing. He started by spreading tax prep fees over 12 months and added value through consulting, eventually formalizing subscription offerings across five practice areas, including legal services.3. Client-Centric, Tiered Service Packages:Instead of letting clients choose from generic service tiers, Mike's firm categorizes clients based on their business profile (e.g., investor, startup, owner-operator, enterprise) and recommends the appropriate package. This approach streamlines pricing, reduces custom quotes, and ensures clients get what they need.4. Data-Driven, Transparent Pricing:Mike uses a detailed, analytical process to set fixed fees—calculating internal costs, adding a target profit margin, and comparing to market rates. If a service isn't profitable or competitive, he won't offer it. This transparency extends to publishing pricing and typical client profiles on his website.5. Leveraging Technology and Remote Work:Mike prioritizes cloud-based, integrated tech tools for both legal and accounting work, enabling a hybrid and remote team. He's open to AI and automation for efficiency but is cautious about client data security. Tools like WealthCounsel, Clio Grow, Carbon, and Ignition are central to his operations.__________________________Learn more about BOSS Advisors.Want to maximize your law firm? Get your ticket to MaxLawCon!Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In if you couldn't make it live.I've partnered with Pii to make it easy for you to purchase the hardware I use in my law firm: (1) Studio Setup; (2) Midrange Setup; (3) Highrange Setup.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

Patrick (Tracer Labs) breaks down Trust ID, a consent + identity layer that replaces cookie pop-ups with a portable, user-owned identity (and embedded wallet). We dig into how Tracer helps brands unify siloed data without storing PII, verify real humans amid AI traffic, and enable one-click privacy that travels site-to-site.Timestamps[00:00] AI = most traffic; attribution is broken [00:01] Intro — Patrick, Tracer Labs & Trust ID [00:02] Patrick's crypto origin story & prior ventures [00:05] The problem: siloed brand data + compliance burden [00:06] What Trust ID does: consent + identity + embedded wallet [00:07] One-click wedge: spin up wallet, tokenize consent, no more cookies [00:09] Brands get real humans, no PII; users keep privacy & control [00:12] GDPR/CCPA costs; why a new US standard is needed[00:15] AI search & bot traffic: restoring pre-intent signal[00:18] Federated identity, modular plug-in, keep existing auth[00:19] Agentic “child IDs” w/ wallets & rule sets (Q1 roadmap)[00:20] KYC/KYB as commoditized credentials that travel with you [00:22] Live MVP; replacing legacy consent managers; early clients [00:24] Who's adopting: cards, casinos, banks, travel; multi-brand SSO [00:25] Unifying loyalty & rewards across properties [00:26] Founder advice: talk to customers on day one [00:31] Digital identity misconceptions; why this time is different [00:33] Abstraction for users; less friction, fewer decisions[00:36] Vision: 0.5–1B users; cut spam; programmatic commerce [00:38] The ask: hiring devs; enterprise intros; $15M seed openConnecthttps://www.tracerlabs.com/https://www.linkedin.com/company/tracerlabs/https://www.linkedin.com/in/patrickmoynihan1/DisclaimerNothing mentioned in this podcast is investment advice and please do your own research. Finally, it would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Be a guest on the podcast or contact us - https://www.web3pod.xyz/

On May 4, 2025, I presented live on the topic of Emerging Technological Trends in the Workplace to the American Academy of Matrimonial Lawyers, Northern California Chapter Symposium. Here are the top 5 takeaways:* Generative AI is Transforming Legal Practice—But Must Be Used Correctly* Generative AI (GenAI) tools like ChatGPT are revolutionizing legal work by enabling rapid drafting, research, and iteration. However, lawyers must use legal-specific AI tools that leverage retrieval augmented generation (RAG) and reliable databases, not general-purpose tools, to avoid errors and ethical pitfalls.* The Billable Hour Model is Becoming Obsolete* The efficiency gains from AI make the traditional billable hour model unsustainable and potentially unethical. Lawyers are encouraged to adopt alternative fee structures, especially subscription models, which align incentives, increase access to justice, and provide predictable revenue for firms.* There is a Massive Untapped Legal Market* 77% of U.S. legal issues go unresolved by lawyers, representing a $1.3 trillion market opportunity. By leveraging technology and alternative pricing, lawyers can serve clients previously priced out of legal services, expanding their reach and impact.* Ethical and Practical Imperatives for AI Adoption* Not using AI, or using it incorrectly, can put a lawyer's license and reputation at risk. Rules of professional conduct increasingly require technological competence. Lawyers must be proactive in adopting, understanding, and ethically integrating AI into their practice.* Subscription and Alternative Fee Models Benefit Both Lawyers and Clients* Subscription models foster ongoing client relationships, reduce burnout, and reward efficiency. They provide clients with cost transparency and predictability, while allowing lawyers to scale their practices, serve more clients, and improve profitability.__________________________Here's a link to the slide deck that goes with the presentation.Want to maximize your law firm? Get your ticket to MaxLawCon!Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In for only $77 if you couldn't make it live.I've partnered with Pii to make it easy for you to purchase the hardware I use in my law firm: (1) Studio Setup; (2) Midrange Setup; (3) Highrange Setup.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lawsubscribed.com/subscribe

Mark Stiving came back to Law Subscribed for a second time to go deep on the complexities and strategies of pricing in business, with a particular emphasis on how companies can better understand and communicate value to their customers. Stiving explores the importance of value-based pricing, the challenges organizations face when shifting away from cost-plus models, and practical steps for implementing more effective pricing strategies. He shares insights into the psychological aspects of pricing, the role of sales teams in conveying value, and the impact of pricing decisions on overall business success.Stiving brings a wealth of expertise as a pricing educator, author, and consultant. He shares real-world examples from his extensive experience, offering actionable advice for both seasoned professionals and those new to pricing. Stiving's engaging approach demystifies complex pricing concepts, making them accessible and relevant. Throughout the conversation, he emphasizes the need for continuous learning and adaptation in pricing, encouraging businesses to focus on customer perceptions of value to drive growth and profitability.__________________________Want to maximize your law firm? Get your ticket to MaxLawCon!Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In for only $77 if you couldn't make it live.I've partnered with Pii to make it easy for you to purchase the hardware I use in my law firm: (1) Studio Setup; (2) Midrange Setup; (3) Highrange Setup.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

Welcome back to Guardians of M365 Governance!

In this episode of Bulletproof Your Marketplace, Jeremy Gottschalk sits down with seasoned legal counsel Krishan Thakker to unpack how user contracts and robust privacy practices can act as liability shields for digital platforms. Drawing on over 15 years advising global technology, e-commerce, and social media companies, Krish shares his expertise at the intersection of data privacy, regulatory compliance, AI governance, and trust & safety. Together, they explore why privacy can no longer be an afterthought, the dangers of conflating terms of use with privacy policies, and the financial and reputational fallout from neglecting compliance—illustrated through high-profile failure. Krish also outlines practical steps for platform operators, including conducting a data audit, adopting a “less is more” approach to PII collection, and drafting clear, standalone user agreements. Whether you're a founder, legal counsel, or trust & safety leader, this episode delivers actionable strategies to protect your platform, build user trust, and stay ahead of evolving regulations.

I intended to interview Tyson Mutrux from Maximum Lawyer about MaxLawCon but got sidetracked talking about technology!Mutrux discusses the evolution of legal podcasting, the importance of high-quality content, and the impact of technology—especially AI—on the legal profession. He reflects on the early days in podcasting, sharing stories about improving audio and video quality, and how valuable content can keep listeners engaged even when production isn't perfect. He explores the significance of staying current, listening to the audience, and being well-prepared for interviews, as well as the crossover skills between litigation and podcasting, such as active listening and curiosity. Mutrux explores the idea of law firm branding, the pros and cons of using personal names versus trade names, and the value of niche marketing. Mutrux shares insights on domain collecting, the challenges of legal tech integration, and the future of AI in legal research and practice management. He highlights the upcoming MaxLawCon conference, emphasizing its collaborative, non-salesy atmosphere and the practical, practitioner-focused sessions. The episode closes with advice for law students and attorneys on leveraging AI tools, the importance of continuous learning, and how to connect with the hosts and their communities.__________________________Get your ticket to MaxLawCon!I've partnered with Pii to make it easy for you to purchase the hardware I use in my law firm: (1) Studio Setup; (2) Midrange Setup; (3) Highrange Setup.Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In for only $77 if you couldn't make it live.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

Nonprofits, your “10 blue links” era is over. In this episode, Avinash Kaushik (Human-Made Machine; Occam's Razor) breaks down Answer Engine Optimization—why LLMs now decide who gets seen, why third-party chatter outweighs your own site, and what to do about it. We get tactical: build AI-resistant content (genuine novelty + depth), go multimodal (text, video, audio), and stamp everything with real attribution so bots can't regurgitate you into sludge. We also cover measurement that isn't delusional—group your AEO referrals, expect fewer visits but higher intent, and stop worshiping last-click and vanity metrics. Avinash updates the 10/90 rule for the AI age (invest in people, plus “synthetic interns”), and torpedoes linear funnels in favor of See-Think-Do-Care anchored in intent. If you want a blunt, practical playbook for staying visible—and actually converting—when answers beat searches, this is it. About Avinash Avinash Kaushik is a leading voice in marketing analytics—the author of Web Analytics: An Hour a Day and Web Analytics 2.0, publisher of the Marketing Analytics Intersect newsletter, and longtime writer of the Occam's Razor blog. He leads strategy at Human Made Machine, advises Tapestry on brand strategy/marketing transformation, and previously served as Google's Digital Marketing Evangelist. Uniquely, he donates 100% of his book royalties and paid newsletter revenue to charity (civil rights, early childhood education, UN OCHA; previously Smile Train and Doctors Without Borders). He also co-founded Market Motive. Resource Links Avinash Kaushik — Occam's Razor (site/home) Occam's Razor by Avinash Kaushik Marketing Analytics Intersect (newsletter sign-up) Occam's Razor by Avinash Kaushik AEO series starter: “AI Age Marketing: Bye SEO, Hello AEO!” Occam's Razor by Avinash Kaushik See-Think-Do-Care (framework explainer) Occam's Razor by Avinash Kaushik Books: Web Analytics: An Hour a Day | Web Analytics 2.0 (author pages) Occam's Razor by Avinash Kaushik+1 Human Made Machine (creative pre-testing) — Home | About | Products humanmademachine.com+2humanmademachine.com+2 Tapestry (Coach, Kate Spade) (company site) Tapestry Tools mentioned (AEO measurement): Trakkr (AI visibility / prompts / sentiment) Trakkr Evertune (AI Brand Index & monitoring) evertune.ai GA4 how-tos (for your AEO channel + attribution): Custom Channel Groups (create an “AEO” channel) Google Help Attribution Paths report (multi-touch view) Google Help Nonprofit vetting (Avinash's donation diligence): Charity Navigator (ratings) Charity Navigator Google for Nonprofits — Gemini & NotebookLM (AI access) Announcement / overview | Workspace AI for nonprofits blog.googleGoogle Help Example NGO Avinash supports: EMERGENCY (Italy) EMERGENCY Transcript Avinash Kaushik: [00:00:00] So traffic's gonna go down. So if you're a business, you're a nonprofit, how. Do you deal with the fact that you're gonna lose a lot of traffic that you get from a search engine? Today, when all of humanity moves to the answer Engine W world, only about two or 3% of the people are doing it. It's growing very rapidly. Um, and so the art of answer engine optimization is making sure that we are building for these LMS and not getting stuck with only solving for Google with the old SEO techniques. Some of them still work, but you need to learn a lot of new stuff because on average, organic traffic will drop between 16 to 64% negative and paid search traffic will drop between five to 30% negative. And that is a huge challenge. And the reason you should start with AEO now ​ George Weiner: [00:01:00] This week's guest, Avinash Kaushik is an absolute hero of mine because of his amazing, uh, work in the field of web analytics. And also, more importantly, I'd say education. Avinash Kaushik, , digital marketing evangelist at Google for Google Analytics. He spent 16 years there. He basically is. In the room where it happened, when the underlying ability to understand what's going on on our websites was was created. More importantly, I think for me, you know, he joined us on episode 45 back in 2016, and he still is, I believe, on the cutting edge of what's about to happen with AEO and the death of SEO. I wanna unpack that 'cause we kind of fly through terms [00:02:00] before we get into this podcast interview AEO. Answer engine optimization. It's this world of saying, alright, how do we create content that can't just be, , regurgitated by bots, , wholesale taken. And it's a big shift from SEO search engine optimization. This classic work of creating content for Google to give us 10 blue links for people to click on that behavior is changing. And when. We go through a period of change. I always wanna look at primary sources. The people that, , are likely to know the most and do the most. And he operates in the for-profit world. But make no mistake, he cares deeply about nonprofits. His expertise, , has frankly been tested, proven and reproven. So I pay attention when he says things like, SEO is going away, and AEO is here to stay. So I give you Avan Kashic. I'm beyond excited that he has come back. He was on our 45th episode and now we are well over our 450th episode. So, , who knows what'll happen next time we talk to him. [00:03:00] This week on the podcast, we have Avinash Kaushik. He is currently the chief strategy officer at Human Made Machine, but actually returning guest after many, many years, and I know him because he basically introduced me to Google Analytics, wrote the literal book on it, and also helped, by the way. No big deal. Literally birth Google Analytics for everyone. During his time at Google, I could spend the entire podcast talking about, uh, the amazing amounts that you have contributed to, uh, marketing and analytics. But I'd rather just real quick, uh, how are you doing and how would you describe your, uh, your role right now? Avinash Kaushik: Oh, thank you. So it's very excited to be back. Um, look forward to the discussion today. I do, I do several things concurrently, of course. I, I, I am an author and I write this weekly newsletter on marketing and analytics. Um, I am the Chief Strategy Officer at Human Made Machine, a company [00:04:00] that obsesses about helping brands win before they spend by doing creative pretesting. And then I also do, uh, uh, consulting at Tapestry, which owns Coach and Kate Spades. And my work focuses on brand strategy and marketing transformation globally. George Weiner: , Amazing. And of course, Occam's Razor. The, the, yes, the blog, which is incredible. I happen to be a, uh, a subscriber. You know, I often think of you in the nonprofit landscape, even though you operate, um, across many different brands, because personally, you also actually donate all of your proceeds from your books, from your blog, from your subscription. You are donating all of that, um, because that's just who you are and what you do. So I also look at you as like team nonprofit, though. Avinash Kaushik: You're very kind. No, no, I, I, yeah. All the proceeds from both of my books and now my newsletter, premium newsletter. It's about $200,000 a year, uh, donated to nonprofits, and a hundred [00:05:00] percent of the revenue is donated nonprofit, uh, nonprofits. And, and for me, it, it's been ai. Then I have to figure out. Which ones, and so I research nonprofits and I look up their cha charity navigators, and I follow up with the people and I check in on the works while, while don't work at a nonprofit, but as a customer of nonprofits, if you will. I, I keep sort of very close tabs on the amazing work that these charities do around the world. So feel very close to the people that you work with very closely. George Weiner: So recently I got an all caps subject line from you. Well, not from you talking about this new acronym that was coming to destroy the world, I think is what you, no, AEO. Can you help us understand what answer engine optimization is? Avinash Kaushik: Yes, of course. Of course. We all are very excited about ai. Obviously you, you, you would've to live in. Some backwaters not to be excited about it. And we know [00:06:00] that, um, at the very edge, lots of people are using large language models, chat, GPT, Claude, Gemini, et cetera, et cetera, in the world. And, and increasingly over the last year, what you have begun to notice is that instead of using a traditional search engine like Google or using the old Google interface with the 10 blue links, et cetera. People are beginning to use these lms. They just go to chat, GPT to get the answer that they want. And the one big difference in this, this behavior is I actually have on September 8th, I have a keynote here in New York and I have to be in Shanghai the next day. That is physically impossible because it, it just, the time it takes to travel. But that's my thing. So today, if I wanted to figure out what is the fastest way. On September 8th, I can leave New York and get to Shanghai. I would go to Google flights. I would put in the destinations. It will come back with a crap load of data. Then I poke and prod and sort and filter, and I have to figure out which flight is right for that. For this need I have. [00:07:00] So that is the old search engine world. I'm doing all the work, hunting and pecking, drilling down, visiting websites, et cetera, et cetera. Instead, actually what I did is I went to charge GBT 'cause I, I have a plus I, I'm a paying member of charge GBT and I said to charge GBTI have to do a keynote between four and five o'clock on September 8th in New York and I have to be in Shanghai as fast as I possibly can be After my keynote, can you find me the best flight? And I just typed in those two sentences. He came back and said, this Korean airline website flight is the best one for you. You will not get to your destination on time until, unless you take a private jet flight for $300,000. There is your best option. They're gonna get to Shanghai on, uh, September 10th at 10 o'clock in the morning if you follow these steps. And so what happened there? I didn't have to hunt and pack and dig and go to 15 websites to find the answer I wanted. The engine found the [00:08:00] answer I wanted at the end and did all the work for me that you are seeing from searching, clicking, clicking, clicking, clicking, clicking to just having somebody get you. The final answer is what I call the, the, the underlying change in consumer behavior that makes answer engine so exciting. Obviously, it creates a challenge for us because what happened between those two things, George is. I didn't have to visit many websites. So traffic is going down, obviously, and these interfaces at the moment don't have paid search links for now. They will come, they will come, but they don't at the moment. So traffic's gonna go down. So if you're a business, you're a nonprofit, how. Do you deal with the fact that you're gonna lose a lot of traffic that you get from a search engine? Today, when all of humanity moves to the answer Engine W world, only about two or 3% of the people are doing it. It's growing very rapidly. Um, and so the art of answer engine optimization [00:09:00] is making sure that we are building for these LMS and not getting stuck with only solving for Google with the old SEO techniques. Some of them still work, but you need to learn a lot of new stuff because on average, organic traffic will drop between 16 to 64% negative and paid search traffic will drop between five to 30% negative. And that is a huge challenge. And the reason you should start with AEO now George Weiner: that you know. Is a window large enough to drive a metaphorical data bus through? And I think talk to your data doctor results may vary. You are absolutely right. We have been seeing this with our nonprofit clients, with our own traffic that yes, basically staying even is the new growth. Yeah. But I want to sort of talk about the secondary implications of an AI that has ripped and gripped [00:10:00] my website's content. Then added whatever, whatever other flavors of my brand and information out there, and is then advising somebody or talking about my brand. Can you maybe unwrap that a little bit more? What are the secondary impacts of frankly, uh, an AI answering what is the best international aid organization I should donate to? Yes. As you just said, you do Avinash Kaushik: exactly. No, no, no. This such a, such a wonderful question. It gets to the crux. What used to influence Google, by the way, Google also has an answer engine called Gemini. So I just, when I say Google, I'm referring to the current Google that most people use with four paid links and 10 SEO links. So when I say Google, I'm referring to that one. But Google also has an answer engine. I, I don't want anybody saying Google does is not getting into the answer engine business. It is. So Google is very much influenced by content George that you create. I call it one P content, [00:11:00] first party content. Your website, your mobile app, your YouTube channel, your Facebook page, your, your, your, your, and it sprinkles on some amount of third party content. Some websites might have reviews about you like Yelp, some websites might have PR releases about you light some third party content. Between search engine and engines. Answer Engines seem to overvalue third party content. My for one p content, my website, my mobile app, my YouTube channel. My, my, my, everything actually is going down in influence while on Google it's pretty high. So as here you do SEO, you're, you're good, good ranking traffic. But these LLMs are using many, many, many, literally tens of thousands more sources. To understand who you are, who you are as a nonprofit, and it's [00:12:00] using everybody's videos, everybody's Reddit posts, everybody's Facebook things, and tens of thousands of more people who write blogs and all kinds of stuff in order to understand who you are as a nonprofit, what services you offer, how good you are, where you're falling short, all those negative reviews or positive reviews, it's all creepy influence. Has gone through the roof, P has come down, which is why it has become very, very important for us to build a new content strategy to figure out how we can influence these LMS about who we are. Because the scary thing is at this early stage in answer engines, someone else is telling the LLMs who you are instead of you. A more, and that's, it feels a little scary. It feels as scary as a as as a brand. It feels very scary as I'm a chief strategy officer, human made machine. It feels scary for HMM. It feels scary for coach. [00:13:00] It's scary for everybody, uh, which is why you really urgently need to get a handle on your content strategy. George Weiner: Yeah, I mean, what you just described, if it doesn't give you like anxiety, just stop right now. Just replay what we just did. And that is the second order effects. And you know, one of my concerns, you mentioned it early on, is that sort of traditional SEO, we've been playing the 10 Blue Link game for so long, and I'm worried that. Because of the changes right now, roughly what 20% of a, uh, search is AI overview, that number's not gonna go down. You're mentioning third party stuff. All of Instagram back to 2020, just quietly got tossed into the soup of your AI brand footprint, as we call it. Talk to me about. There's a nonprofit listening to this right now, and then probably if they're smart, other organizations, what is coming in the next year? They're sitting down to write the same style of, you know, [00:14:00] ai, SEO, optimized content, right? They have their content calendar. If you could have like that, I'm sitting, you're sitting in the room with them. What are you telling that classic content strategy team right now that's about to embark on 2026? Avinash Kaushik: Yes. So actually I, I published this newsletter just last night, and this is like the, the fourth in my AEO series, uh, newsletter, talks about how to create your content portfolio strategy. Because in the past we were like, we've got a product pages, you know, the equivalent of our, our product pages. We've got some, some, uh, charitable stories on our website and uh, so on and so forth. And that's good. That's basic. You need to do the basics. The interesting thing is you need to do so much more both on first party. So for example, one of the first things to appreciate is LMS or answer engines are far more influenced by multimodal content. So what does that mean? Text plus [00:15:00] video plus audio. Video and audio were also helpful in Google. And remember when I say Google, I'm referring to the old linky linking Google, not Gemini. But now video has ton more influence. So if you're creating a content strategy for next year, you should say many. Actually, lemme do one at a time. Text. You have to figure out more types of things. Authoritative Q and as. Very educational deep content around your charity's efforts. Lots of text. Third. Any seasonality, trends and patterns that happen in your charity that make a difference? I support a school in, in Nepal and, and during the winter they have very different kind of needs than they do during the summer. And so I bumped into this because I was searching about something seasonality related. This particular school for Tibetan children popped up in Nepal, and it's that content they wrote around winter and winter struggles and coats and all this stuff. I'm like. [00:16:00] It popped up in the answer engine and I'm like, okay. I research a bit more. They have good stories about it, and I'm supporting them q and a. Very, very important. Testimonials. Very, very important interviews. Very, very important. Super, super duper important with both the givers and the recipients, supporters of your nonprofit, but also the recipient recipients of very few nonprofits actually interview the people who support them. George Weiner: Like, why not like donors or be like, Hey, why did you support us? What was the, were the two things that moved you from Aware to care? Avinash Kaushik: Like for, for the i I Support Emergency, which is a Italian nonprofit like Ms. Frontiers and I would go on their website and speak a fiercely about why I absolutely love the work they do. Content, yeah. So first is text, then video. You gotta figure out how to use video a lot more. And most nonprofits are not agile in being able to use video. And the third [00:17:00] thing that I think will be a little bit of a struggle is to figure out how to use audio. 'cause audio also plays a very influential role. So for as you are planning your uh, uh, content calendar for the next year. Have the word multimodal. I'm sorry, it's profoundly unsexy, but put multimodal at the top, underneath it, say text, then say video, then audio, and start to fill those holes in. And if those people need ideas and example of how to use audio, they should just call you George. You are the king of podcasting and you can absolutely give them better advice than I could around how nonprofits could use audio. But the one big thing you have to think about is multimodality for next year George Weiner: that you know, is incredibly powerful. Underlying that, there's this nuance that I really want to make sure that we understand, which is the fact that the type of content is uniquely different. It's not like there's a hunger organization listening right now. It's not 10 facts about hunger during the winter. [00:18:00] Uh, days of being able to be an information resource that would then bring people in and then bring them down your, you know, your path. It's game over. If not now, soon. Absolutely. So how you are creating things that AI can't create and that's why you, according to whom, is what I like to think about. Like, you're gonna say something, you're gonna write something according to whom? Is it the CEO? Is it the stakeholder? Is it the donor? And if you can put a attribution there, suddenly the AI can't just lift and shift it. It has to take that as a block and be like, no, it was attributed here. This is the organization. Is that about right? Or like first, first party data, right? Avinash Kaushik: I'll, I'll add one more, one more. Uh, I'll give a proper definition. So, the fir i I made 11 recommendations last night in the newsletter. The very first one is focus on creating AI resistant content. So what, what does that mean? AI resistant means, uh, any one of us from nonprofits could [00:19:00] open chat, GPT type in a few queries and chat. GD PT can write our next nonprofit newsletter. It could write the next page for our donation. It could create the damn page for our donation, right? Remember, AI can create way more content than you can, but if you can use AI to create content, 67 million other nonprofits are doing the same thing. So what you have to do is figure out how to build AI resistant content, and my definition is very simple. George, what is AI resistance? It's content of genuine novelty. So to tie back to your recommendation, your CEO of a nonprofit that you just recommended, the attribution to George. Your CEO has a unique voice, a unique experience. The AI hasn't learned what makes your CEO your frontline staff solving problems. You are a person who went and gave a speech at the United Nations on behalf of your nonprofit. Whatever you are [00:20:00] doing is very special, and what you have to figure out is how to get out of the AI slop. You have to get out of all the things that AI can automatically type. Figure out if your content meets this very simple, standard, genuine novelty and depth 'cause it's the one thing AI isn't good at. That's how you rank higher. And not only will will it, will it rank you, but to make another point you made, George, it's gonna just lift, blanc it out there and attribute credit to you. Boom. But if you're not genuine, novelty and depth. Thousand other nonprofits are using AI to generate text and video. Could George Weiner: you just, could you just quit whatever you're doing and start a school instead? I seriously can't say it enough that your point about AI slop is terrifying me because I see it. We've built an AI tool and the subtle lesson here is that think about how quickly this AI was able to output that newsletter. Generic old school blog post and if this tool can do it, which [00:21:00] by the way is built on your local data set, we have the rag, which doesn't pause for a second and realize if this AI can make it, some other AI is going to be able to reproduce it. So how are you bringing the human back into this? And it's a style of writing and a style of strategic thinking that please just start a school and like help every single college kid leaving that just GPT their way through a degree. Didn't freaking get, Avinash Kaushik: so it's very, very important to make sure. Content is of genuine novelty and depth because it cannot be replicated by the ai. And by the way, this, by the way, George, it sounds really high, but honestly to, to use your point, if you're a CEO of a nonprofit, you are in it for something that speaks to you. You're in it. Because ai, I mean nonprofit is not your path to becoming the next Bill Gates, you're doing it because you just have this hair. Whoa, spoiler alert. No, I'm sorry. [00:22:00] Maybe, maybe that is. I, I didn't, I didn't mean any negative emotion there, but No, I love it. It's all, it's like a, it's like a sense of passion you are bringing. There's something that speaks to you. Just put that on paper, put that on video, put that on audio, because that is what makes you unique. And the collection of those stories of genuine depth and novelty will make your nonprofit unique and stand out when people are looking for answers. George Weiner: So I have to point to the next elephant in the room here, which is measurement. Yes. Yes. Right now, somebody is talking about human made machine. Someone's talking about whole whale. Someone's talking about your nonprofit having a discussion in an answer engine somewhere. Yes. And I have no idea. How do I go about understanding measurement in this new game? Avinash Kaushik: I have. I have two recommendations. For nonprofits, I would recommend a tool called Tracker ai, TRA, KKR [00:23:00] ai, and it has a free version, that's why I'm recommending it. Some of the many of these tools are paid tools, but with Tracker, do ai. It allows you to identify your website, URL, et cetera, et cetera, and it'll give you some really wonderful and fantastic, helpful report It. Tracker helps you understand prompt tracking, which is what are other people writing about you when they're seeking? You? Think of this, George, as your old webmaster tools. What keywords are people using to search? Except you can get the prompts that people are using to get a more robust understanding. It also monitors your brand's visibility. How often are you showing up and how often is your competitor showing up, et cetera, et cetera. And then he does that across multiple search engines. So you can say, oh, I'm actually pretty strong in OpenAI for some reason, and I'm not that strong in Gemini. Or, you know what, I have like the highest rating in cloud, but I don't have it in OpenAI. And this begins to help you understand where your current content strategy is working and where it is not [00:24:00] working. So that's your brand visibility. And the third thing that you get from Tracker is active sentiment tracking. This is the scary part because remember, you and I were both worried about what other people saying about us. So this, this are very helpful that we can go out and see what it is. What is the sentiment around our nonprofit that is coming across in, um, in these lms? So Tracker ai, it have a free and a paid version. So I would, I would recommend using it for these three purposes. If, if you have funding to invest in a tool. Then there's a tool called Ever Tool, E-V-E-R-T-U-N-E Ever. Tune is a paid tool. It's extremely sophisticated and robust, and they do brand monitoring, site audit, content strategy, consumer preference report, ai, brand index, just the. Step and breadth of metrics that they provide is quite extensive, but, but it is a paid tool. It does cost money. It's not actually crazy expensive, but uh, I know I have worked with them before, so full disclosure [00:25:00] and having evaluated lots of different tools, I have sort of settled on those two. If it's a enterprise type client I'm working with, then I'll use Evert Tune if I am working with a nonprofit or some of my personal stuff. I'll use Tracker AI because it's good enough for a person that is, uh, smaller in size and revenue, et cetera. So those two tools, so we have new metrics coming, uh, from these tools. They help us understand the kind of things we use webmaster tools for in the past. Then your other thing you will want to track very, very closely is using Google Analytics or some other tool on your website. You are able to currently track your, uh, organic traffic and if you're taking advantage of paid ads, uh, through a grant program on Google, which, uh, provides free paid search credits to nonprofits. Then you're tracking your page search traffic to continue to track that track trends, patterns over time. But now you will begin to see in your referrals report, in your referrals report, you're gonna begin to seeing open [00:26:00] ai. You're gonna begin to see these new answer engines. And while you don't know the keywords that are sending this traffic and so on and so forth, it is important to keep track of the traffic because of two important reasons. One, one, you want to know how to highly prioritize. AEO. That's one reason. But the other reason I found George is syn is so freaking hard to rank in an answer engine. When people do come to my websites from Answer engine, the businesses I work with that is very high intent person, they tend to be very, very valuable because they gave the answer engine a very complex question to answer the answers. Engine said you. The right answer for it. So when I show up, I'm ready to buy, I'm ready to donate. I'm ready to do the action that I was looking for. So the percent of people who are coming from answer engines to your nonprofit carry significantly higher intention, and coming from Google, who also carry [00:27:00] intent. But this man, you stood out in an answer engine, you're a gift from God. Person coming thinks you're very important and is likely to engage in some sort of business with you. So I, even if it's like a hundred people, I care a lot about those a hundred people, even if it's not 10,000 at the moment. Does that make sense George? George Weiner: It does, and I think, I'm glad you pointed to, you know, the, the good old Google Analytics. I'm like, it has to be a way, and I, I think. I gave maximum effort to this problem inside of Google Analytics, and I'm still frustrated that search console is not showing me, and it's just blending it all together into one big soup. But. I want you to poke a hole in this thinking or say yes or no. You can create an AI channel, an AEO channel cluster together, and we have a guide on that cluster together. All of those types of referral traffic, as you mentioned, right from there. I actually know thanks to CloudFlare, the ratios of the amount of scrapes versus the actual clicks sent [00:28:00] for roughly 20, 30% of. Traffic globally. So is it fair to say I could assume like a 2% clickthrough or a 1% clickthrough, or even worse in some cases based on that referral and then reverse engineer, basically divide those clicks by the clickthrough rate and essentially get a rough share of voice metric on that platform? Yeah. Avinash Kaushik: So, so for, um, kind of, kind of at the moment, the problem is that unlike Google giving us some decent amount of data through webmaster tools. None of these LLMs are giving us any data. As a business owner, none of them are giving us any data. So we're relying on third parties like Tracker. We're relying on third parties like Evert Tune. You understand? How often are we showing up so we could get a damn click through, right? Right. We don't quite have that for now. So the AI Brand Index in Evert Tune comes the closest. Giving you some information we could use in the, so your thinking is absolutely right. Your recommendation is ly, right? Even if you can just get the number of clicks, even if you're tracking them very [00:29:00] carefully, it's very important. Please do exactly what you said. Make the channel, it's really important. But don't, don't read too much into the click-through rate bits, because we're missing the. We're missing a very important piece of information. Now remember when Google first came out, we didn't have tons of data. Um, and that's okay. These LLMs Pro probably will realize over time if they get into the advertising business that it's nice to give data out to other people, and so we might get more data. Until then, we are relying on these third parties that are hacking these tools to find us some data. So we can use it to understand, uh, some of the things we readily understand about keywords and things today related to Google. So we, we sadly don't have as much visibility today as we would like to have. George Weiner: Yeah. We really don't. Alright. I have, have a segment that I just invented. Just for you called Avanade's War Corner. And in Avanade's War Corner, I noticed that you go to war on various concepts, which I love because it brings energy and attention to [00:30:00] frankly data and finding answers in there. So if you'll humor me in our war corner, I wanna to go through some, some classic, classic avan. Um, all right, so can you talk to me a little bit about vanity metrics, because I think they are in play. Every day. Avinash Kaushik: Absolutely. No, no, no. Across the board, I think in whatever we do. So, so actually I'll, I'll, I'll do three. You know, so there's vanity metrics, activity metrics and outcome metrics. So basically everything goes into these three buckets essentially. So vanity metrics are, are the ones that are very easy to find, but them moving up and down has nothing to do with the number of donations you're gonna get as a nonprofit. They're just there to ease our ego. So, for example. Let's say we are a nonprofit and we run some display ads, so measure the number of impressions that were delivered for our display ad. That's a vanity metric. It doesn't tell you anything. You could have billions of impressions. You could have 10 impressions, doesn't matter, but it is easily [00:31:00] available. The count is easily available, so we report it. Now, what matters? What matters are, did anybody engage with the ad? What were the percent of people who hovered on the ad? What were the number of people who clicked on the ad activity metrics? Activity metrics are a little more useful than vanity metrics, but what does it matter for you as a non nonprofit? The number of donations you received in the last 24 hours. That's an outcome metric. Vanity activity outcome. Focus on activity to diagnose how well our campaigns or efforts are doing in marketing. Focus on outcomes to understand if we're gonna stay in business or not. Sorry, dramatic. The vanity metrics. Chasing is just like good for ego. Number of likes is a very famous one. The number of followers on a social paia, a very famous one. Number of emails sent is another favorite one. There's like a whole host of vanity metrics that are very easy to get. I cannot emphasize this enough, but when you unpack and or do meta-analysis of [00:32:00] relationship between vanity metrics and outcomes, there's a relationship between them. So we always advise people that. Start by looking at activity metrics to help you understand the user's behavior, and then move to understanding outcome metrics because they are the reason you'll thrive. You will get more donations or you will figure out what are the things that drive more donations. Otherwise, what you end up doing is saying. If I post provocative stuff on Facebook, I get more likes. Is that what you really wanna be doing? But if your nonprofit says, get me more likes, pretty soon, there's like a naked person on Facebook that gets a lot of likes, but it's corrupting. Yeah. So I would go with cute George Weiner: cat, I would say, you know, you, you get the generic cute cat. But yeah, same idea. The Internet's built on cats Avinash Kaushik: and yes, so, so that's why I, I actively recommend people stay away from vanity metrics. George Weiner: Yeah. Next up in War Corner, the last click [00:33:00] fallacy, right? The overweighting of this last moment of purchase, or as you'd maybe say in the do column of the See, think, do care. Avinash Kaushik: Yes. George Weiner: Yes. Avinash Kaushik: So when the, when the, when we all started to get Google Analytics, we got Adobe Analytics web trends, remember them, we all wanted to know like what drove the conversion. Mm-hmm. I got this donation for a hundred dollars. I got a donation for a hundred thousand dollars. What drove the conversion. And so what lo logically people would just say is, oh, where did this person come from? And I say, oh, the person came from Google. Google drove this conversion. Yeah, his last click analysis just before the conversion. Where did the person come from? Let's give them credit. But the reality is it turns out that if you look at consumer behavior, you look at days to donation, visits to donation. Those are two metrics available in Google. It turns out that people visit multiple times before [00:34:00] they make a donation. They may have come through email, their interest might have been triggered through your email. Then they suddenly remembered, oh yeah, yeah, I wanted to go to the nonprofit and donate something. This is Google, you. And then Google helps them find you and they come through. Now, who do you give credit Email or the Google, right? And what if you came 5, 7, 8, 10 times? So the last click fallacy is that it doesn't allow you to see the full consumer journey. It gives credit to whoever was the last person who sent you this, who introduced this person to your website. And so very soon we move to looking at what we call MTI, Multi-Touch Attribution, which is a free solution built into Google. So you just go to your multichannel funnel reports and it will help you understand that. One, uh, 150 people came from email. Then they came from Google. Then there was a gap of nine days, and they came back from Facebook and then they [00:35:00] converted. And what is happening is you're beginning to understand the consumer journey. If you understand the consumer journey better, we can come with better marketing. Otherwise, you would've said, oh, close shop. We don't need as many marketing people. We'll just buy ads on Google. We'll just do SEO. We're done. Oh, now you realize there's a more complex behavior happening in the consumer. They need to solve for email. You solve for Google, you need to solve Facebook. In my hypothetical example, so I, I'm very actively recommend people look at the built-in free MTA reports inside the Google nalytics. Understand the path flow that is happening to drive donations and then undertake activities that are showing up more often in the path, and do fewer of those things that are showing up less in the path. George Weiner: Bring these up because they have been waiting on my mind in the land of AEO. And by the way, we're not done with war. The war corner segment. There's more war there's, but there's more, more than time. But with both of these metrics where AEO, if I'm putting these glasses back on, comes [00:36:00] into play, is. Look, we're saying goodbye to frankly, what was probably somewhat of a vanity metric with regard to organic traffic coming in on that 10 facts about cube cats. You know, like, was that really how we were like hanging our hat at night, being like. Job done. I think there's very much that in play. And then I'm a little concerned that we just told everyone to go create an AEO channel on their Google Analytics and they're gonna come in here. Avinash told me that those people are buyers. They're immediately gonna come and buy, and why aren't they converting? What is going on here? Can you actually maybe couch that last click with the AI channel inbound? Like should I expect that to be like 10 x the amount of conversions? Avinash Kaushik: All we can say is it's, it's going to be people with high intention. And so with the businesses that I'm working with, what we are finding is that the conversion rates are higher. Mm. This game is too early to establish any kind of sense of if anybody has standards for AEO, they're smoking crack. Like the [00:37:00] game is simply too early. So what we I'm noticing is that in some cases, if the average conversion rate is two point half percent, the AEO traffic is converting at three, three point half. In two or three cases, it's converting at six, seven and a half. But there is not enough stability in the data. All of this is new. There's not enough stability in the data to say, Hey, definitely you can expect it to be double or 10% more or 50% more. We, we have no idea this early stage of the game, but, but George, if we were doing this again in a year, year and a half, I think we'll have a lot more data and we'll be able to come up with some kind of standards for, for now, what's important to understand is, first thing is you're not gonna rank in an answer engine. You just won't. If you do rank in an answer engine, you fought really hard for it. The person decided, oh my God, I really like this. Just just think of the user behavior and say, this person is really high intent because somehow [00:38:00] you showed up and somehow they found you and came to you. Chances are they're caring. Very high intent. George Weiner: Yeah. They just left a conversation with a super intelligent like entity to come to your freaking 2001 website, HTML CSS rendered silliness. Avinash Kaushik: Whatever it is, it could be the iffiest thing in the world, but they, they found me and they came to you and they decided that in the answer engine, they like you as the answer the most. And, and it took that to get there. And so all, all, all is I'm finding in the data is that they carry higher intent and that that higher intent converts into higher conversion rates, higher donations, as to is it gonna be five 10 x higher? It's unclear at the moment, but remember, the other reason you should care about it is. Every single day. As more people move away from Google search engines to answer engines, you're losing a ton of traffic. If somebody new showing up, treat them with, respect them with love. Treat them with [00:39:00] care because they're very precious. Just lost a hundred. Check the landing George Weiner: pages. 'cause you may be surprised where your front door is when complexity is bringing them to you, and it's not where you spent all of your design effort on the homepage. Spoiler. That's exactly Avinash Kaushik: right. No. Exactly. In fact, uh, the doping deeper into your websites is becoming even more prevalent with answer engines. Mm-hmm. Um, uh, than it used to be with search engines. The search always tried to get you the, the top things. There's still a lot of diversity. Your homepage likely is still only 30% of your traffic. Everybody else is landing on other homepage or as you call them, landing pages. So it's really, really important to look beyond your homepage. I mean, it was true yesterday. It's even truer today. George Weiner: Yeah, my hunch and what I'm starting to see in our data is that it is also much higher on the assisted conversion like it is. Yes. Yes, it is. Like if you have come to us from there, we are going to be seeing you again. That's right. That's right. More likely than others. It over indexes consistently for us there. Avinash Kaushik: [00:40:00] Yes. Again, it ties back to the person has higher intent, so if they didn't convert in that lab first session, their higher intent is gonna bring them back to you. So you are absolutely right about the data that you're seeing. George Weiner: Um, alright. War corner, the 10 90 rule. Can you unpack this and then maybe apply it to somebody who thinks that their like AI strategy is done? 'cause they spend $20 or $200 a month on some tool and then like, call it a day. 'cause they did ai. Avinash Kaushik: Yes, yes. No, it's, it's good. I, I developed it in context of analytics. When I was at my, uh, job at Intuit, I used to, I was at Intuit, senior director for research and analytics. And one of the things I found is people would consistently spend lots of money on tools in that time, web analytics tools, research tools, et cetera. And, uh, so they're spending a contract of a few hundred thousand dollars or hundreds of thousands of dollars, and then they give it to a fresh graduate to find insights. [00:41:00] I was like, wait, wait, wait. So you took this $300,000 thing and gave it to somebody. You're paying $45,000 a year. Who is young in their career, young in their career, and expecting them to make you tons of money using this tool? It's not the tool, it's the human. And so that's why I developed the the 10 90 rule, which is that if you have a, if you have a hundred dollars to invest in making smarter decisions, invest $10 in the tool, $90 in the human. We all have access to so much data, so much complexity. The world is changing so fast that it is the human that is going to figure out how to make sense of these insights rather than the tool magically spewing and understanding your business enough to tell you exactly what to do. So that, that's sort of where the 10 90 rule came from. Now, sort of we are in this, in this, um, this is very good for nonprofits by the way. So we're in this era. Where On the 90 side? No. So the 10, look, don't spend insane money on tools that is just silly. So don't do that. Now the 90, let's talk about the [00:42:00] 90. Up until two years ago, I had to spell all of the 90 on what I now call organic humans. You George Weiner: glasses wearing humans, huh? Avinash Kaushik: The development of LLM means that every single nonprofit in the world has access to roughly a third year bachelor's degree student. Like a really smart intern. For free. For free. In fact, in some instances, for some nonprofits, let's say I I just reading about this nonprofit that is cleaning up plastics in the ocean for this particular nonprofit, they have access to a p HT level environmentalist using the latest Chad GP PT 4.5, like PhD level. So the little caveat I'm beginning to put in the 10 90 rule is on the 90. You give the 90 to the human and for free. Get the human, a very smart Bachelor's student by using LLMs in some instances. Get [00:43:00] for free a very smart TH using the LLMs. So the LLMs have now to be incorporated into your research, into your analysis, into building a next dashboard, into building a next website, into building your next mobile game into whatever the hell you're doing for free. You can get that so you have your organic human. Less the synthetic human for free. Both of those are in the 90 and, and for nonprofit, so, so in my work at at Coach and Kate Spade. I have access now to a couple of interns who do free work for me, well for 20 minor $20 a month because I have to pay for the plus version of G bt. So the intern costs $20 a month, but I have access to this syn synthetic human who can do a whole lot of work for me for $20 a month in my case, but it could also do it for free for you. Don't forget synthetic humans. You no longer have to rely only on the organic humans to do the 90 part. You would be stunned. Upload [00:44:00] your latest, actually take last year's worth of donations, where they came from and all this data from you. Have a spreadsheet lying around. Dump it into chat. GPT, I'll ask it to analyze it. Help you find where most donations came from, and visualize trends to present to board of directors. It will blow your mind how good it is at do it with Gemini. I'm not biased, I'm just seeing chat. GPD 'cause everybody knows it so much Better try it with mistrial a, a small LLM from France. So I, I wanna emphasize that what has changed over the last year is the ability for us to compliment our organic humans with these synthetic entities. Sometimes I say synthetic humans, but you get the point. George Weiner: Yeah. I think, you know, definitely dump that spreadsheet in. Pull out the PII real quick, just, you know, make me feel better as, you know, the, the person who's gonna be promoting this to everybody, but also, you know, sort of. With that. I want to make it clear too, that like actually inside of Gemini, like Google for nonprofits has opened up access to Gemini for free is not a per user, per whatever. You have that [00:45:00] you have notebook, LLM, and these. Are sitting in their backyards for free every day and it's like a user to lose it. 'cause you have a certain amount of intelligence tokens a day. Can you, I just like wanna climb like the tallest tree out here and just start yelling from a high building about this. Make the case of why a nonprofit should be leveraging this free like PhD student that is sitting with their hands underneath their butts, doing nothing for them right now. Avinash Kaushik: No, it is such a shame. By the way, I cannot add to your recommendation in using your Gemini Pro account if it's free, on top of, uh, all the benefits you can get. Gemini Pro also comes with restrictions around their ability to use your data. They won't, uh, their ability to put your data anywhere. Gemini free versus Gemini Pro is a very protected environment. Enterprise version. So more, more security, more privacy, et cetera. That's a great benefit. And by the way, as you said, George, they can get it for free. So, um, the, the, the, the posture you should adopt is what big companies are doing, [00:46:00] which is anytime there is a job to be done, the first question you, you should ask is, can I make the, can an AI do the job? You don't say, oh, let me send it to George. Let me email Simon, let me email Sarah. No, no, no. The first thing that should hit your head is. I do the job because most of the time for, again, remember, third year bachelor's degree, student type, type experience and intelligence, um, AI can do it better than any human. So your instincts to be, let me outsource that kind of work so I can free up George's cycles for the harder problems that the AI cannot solve. And by the way, you can do many things. For example, you got a grant and now Meta allows you to run X number of ads for free. Your first thing, single it. What kind of ad should I create? Go type in your nonprofit, tell it the kind of things you're doing. Tell it. Tell it the donations you want, tell it the size, donation, want. Let it create the first 10 ads for you for free. And then you pick the one you like. And even if you have an internal [00:47:00] designer who makes ads, they'll start with ideas rather than from scratch. It's just one small example. Or you wanna figure out. You know, my email program is stuck. I'm not getting yield rates for donations. The thing I want click the button that called that is called deep research or thinking in the LL. Click one of those two buttons and then say, I'm really struggling. I'm at wits end. I've tried all these things. Write all the detail. Write all the detail about what you've tried and now working. Can you please give me three new ideas that have worked for nonprofits who are working in water conservation? Hmm. This would've taken a human like a few days to do. You'll have an answer in under 90 seconds. I just give two simple use cases where we can use these synthetic entities to send us, do the work for us. So the default posture in nonprofits should be, look, we're resource scrapped anyway. Why not use a free bachelor's degree student, or in some case a free PhD student to do the job, or at least get us started on a job. So just spending 10 [00:48:00] hours on it. We only spend the last two hours. The entity entity does the first date, and that is super attractive. I use it every single day in, in one of my browsers. I have three traps open permanently. I've got Claude, I've got Mistrial, I've got Charge GPT. They are doing jobs for me all day long. Like all day long. They're working for me. $20 each. George Weiner: Yeah, it's an, it, it, it's truly, it's an embarrassment of riches, but also getting back to the, uh, the 10 90 is, it's still sitting there. If you haven't brought that capacity building to the person on how to prompt how to play that game of linguistic tennis with these tools, right. They're still just a hammer on a. Avinash Kaushik: That's exactly right. That's exactly right. Or, or in your case, you, you have access to Gemini for nonprofits. It's a fantastic tool. It's like a really nice card that could take you different places you insist on cycling everywhere. It's, it's okay cycle once in a while for health reasons. Otherwise, just take the car, it's free. George Weiner: Ha, you've [00:49:00] been so generous with your time. Uh, I do have one more quick war. If you, if you have, have a minute, uh, your war on funnels, and maybe this is not. Fully fair. And I am like, I hear you yelling at me every time I'm showing our marketing funnel. And I'm like, yeah, but I also have have a circle over here. Can you, can you unpack your war on funnels and maybe bring us through, see, think, do, care and in the land of ai? Avinash Kaushik: Yeah. Okay. So the marketing funnel is very old. It's been around for a very long time, and once I, I sort of started working at Google, access to lots more consumer research, lots more consumer behavior. Like 20 years ago, I began to understand that there's no such thing as funnel. So what does the funnel say? The funnel says there's a group of people running around the world, they're not aware of your brand. Find them, scream at them, spray and pray advertising at them, make them aware, and then somehow magically find the exact same people again and shut them down the fricking funnel and make them consider your product.[00:50:00] And now that they're considering, find them again, exactly the same people, and then shove them one more time. Move their purchase index and then drag them to your website. The thing is this linearity that there's no evidence in the universe that this linearity exists. For example, uh, I'm going on a, I like long bike rides, um, and I just got thirsty. I picked up the first brand. I could see a water. No awareness, no consideration, no purchase in debt. I just need water. A lot of people will buy your brand because you happen to be the cheapest. I don't give a crap about anything else, right? So, um, uh, uh, the other thing to understand is, uh, one of the brands I adore and have lots of is the brand. Patagonia. I love Patagonia. I, I don't use the word love for I think any other brand. I love Patagonia, right? For Patagonia. I'm always in the awareness stage because I always want these incredible stories that brand ambassadors tell about how they're helping the environment. [00:51:00] I have more Patagonia products than I should have. I'm already customer. I'm always open to new considerations of Patagonia products, new innovations they're bringing, and then once in a while, I'm always in need to buy a Patagonia product. I'm evaluating them. So this idea that the human is in one of these stages and your job is to shove them down, the funnel is just fatally flawed, no evidence for it. Instead, what you want to do is what is Ash's intent at the moment? He would like environmental stories about how we're improving planet earth. Patagonia will say, I wanna make him aware of my environmental stories, but if they only thought of marketing and selling, they wouldn't put me in the awareness because I'm already a customer who buys lots of stuff from already, right? Or sometimes I'm like, oh, I'm, I'm heading over to London next week. Um, I need a thing, jacket. So yeah, consideration show up even though I'm your customer. So this seating do care is a framework that [00:52:00] says, rather than shoving people down things that don't exist and wasting your money, your marketing should be able to discern any human's intent and then be able to respond with a piece of content. Sometimes that piece of content in an is an ad. Sometimes it's a webpage, sometimes it's an email. Sometimes it's a video. Sometimes it's a podcast. This idea of understanding intent is the bedrock on which seat do care is built about, and it creates fully customer-centric marketing. It is harder to do because intent is harder to infer, but if you wanna build a competitive advantage for yourself. Intent is the magic. George Weiner: Well, I think that's a, a great point to, to end on. And again, so generous with, uh, you know, all the work you do and also supporting nonprofits in the many ways that you do. And I'm, uh, always, always watching and seeing what I'm missing when, um, when a new, uh, AKA's Razor and Newsletter come out. So any final sign off [00:53:00] here on how do people find you? How do people help you? Let's hear it. Avinash Kaushik: You can just Google or answer Engine Me. It's, I'm not hard. I hard to find, but if you're a nonprofit, you can sign up for my newsletter, TMAI marketing analytics newsletter. Um, there's a free one and a paid one, so you can just sign up for the free one. It's a newsletter that comes out every five weeks. It's completely free, no strings or anything. And that way I'll be happy to share my stories around better marketing and analytics using the free newsletter for you so you can sign up for that. George Weiner: Brilliant. Well, thank you so much, Avan. And maybe, maybe we'll have to take you up on that offer to talk sometime next year and see, uh, if maybe we're, we're all just sort of, uh, hanging out with synthetic humans nonstop. Thank you so much. It was fun, George. [00:54:00]

Discover how to build an efficient tech stack for your modern virtual law firm in this comprehensive guide! This episode of Law Subscribed covers everything from essential hardware and software recommendations to detailed purchasing strategies and crucial implementation tips. Learn about the latest AI tools, ergonomic setups, and advanced scheduling and communication platforms. Whether you're looking to streamline your operations or enhance client engagement, this episode is packed with valuable insights to help you optimize your practice. Don't miss out on these game-changing strategies—watch the episode now and take your legal practice to the next level!__________________________I've partnered with Pii to make it easy for you to purchase the setups recommended in this talk! Use the corresponding link to get the hardware you want in one purchase from my setups:Studio SetupMidrange SetupHighrange SetupWant to maximize your law firm? Get your ticket to MaxLawCon!Here's a link to purchase lifetime access to the recordings of My Shingle's AI Teach-In for only $77 if you couldn't make it live.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Check out my other show, the Law for Kids Podcast.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Want to use the subscription model for your law firm? Sign up for the Subscription Seminar waitlist at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscriptionseminar.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get full access to Law Subscribed at www.lawsubscribed.com/subscribe

Summary In this episode, Marc is chattin' with Colleen García, a seasoned privacy attorney. The conversation begins with an introduction to Colleen's extensive background in cybersecurity law, including her experience working with the U.S. government before transitioning to the private sector. This sets the stage for a deep dive into the complex relationship between data privacy and artificial intelligence (AI), highlighting the importance of understanding legal and ethical considerations as AI technology continues to evolve rapidly. The core of the discussion centers on how AI models are trained on vast amounts of data, often containing personal identifiable information (PII). Colleen emphasizes that respecting individuals' data privacy rights is crucial, especially when it comes to obtaining proper consent for the use of their data in AI systems. She points out that while AI offers many benefits, it also raises significant concerns about data misuse, leakage, and the potential for infringing on privacy rights, which companies must carefully navigate to avoid legal and reputational risks. Colleen elaborates on the current legal landscape, noting that existing data privacy laws—such as those in the U.S., the European Union, Canada, and Singapore—are being adapted to address AI-specific issues. She mentions upcoming regulations like the EU AI Act and highlights the role of the Federal Trade Commission (FTC) in enforcing transparency and honesty in AI disclosures. Although some laws do not explicitly mention AI, their principles are increasingly being applied to regulate AI development and deployment, emphasizing the need for companies to stay compliant and transparent. The conversation then expands to a global perspective, with Colleen discussing how different countries are approaching the intersection of data privacy and AI. She notes that international efforts are underway to develop legal frameworks that address the unique challenges posed by AI, reflecting a broader recognition that AI regulation is a worldwide concern. This global outlook underscores the importance for companies operating across borders to stay informed about evolving legal standards and best practices. In closing, Colleen offers practical advice for businesses seeking to responsibly implement AI. She stresses the importance of building AI systems on a strong foundation of data privacy, including thorough vetting of training data and transparency with users. She predicts that future legislative efforts may lead to more state-level AI laws and possibly a comprehensive federal framework, although the current landscape remains fragmented. The podcast concludes with Colleen inviting listeners to connect with her for further discussion, emphasizing the need for proactive, thoughtful approaches to AI and data privacy in the evolving legal environment. Key Points The Relationship Between Data Privacy and AI: The discussion emphasizes how AI models are trained on data that often includes personal identifiable information (PII), highlighting the importance of respecting privacy rights and obtaining proper consent. Legal Risks and Challenges in AI and Data Privacy: Colleen outlines potential risks such as data leakage, misuse, and the complexities of ensuring compliance with existing privacy laws when deploying AI systems. Current and Emerging Data Privacy Laws: The conversation covers how existing laws (like those from the U.S., EU, Canada, and Singapore) are being adapted to regulate AI, along with upcoming regulations such as the EU AI Act and the role of agencies like the FTC. International Perspectives on AI and Data Privacy: The interview highlights how different countries are approaching AI regulation, emphasizing that this is a global issue with ongoing legislative developments worldwide. Practical Advice for Responsible AI Deployment: Colleen offers guidance for companies to build AI systems on a strong data privacy foun...

Send us a textCRO veteran Dylan Ander (Founder, heatmap.com) joins Jordan to spill the never-before-shared story of how he landed heatmap.com by acquiring an entire C-Corp—and why the name matters for brand authority, SEO, and inbound. We break down why GA4 falls short for eCommerce, how definitions (sessions, idle windows, engagement) skew your numbers vs Shopify, and what to use when you need buyer-truth, not vanity metrics.Dylan unveils element-level revenue analytics—Revenue per Click (RPC) and Revenue per Session (RPS)—plus the coming Revenue per View (RPV), so you can prioritize changes that actually increase cash, not just clicks. We dig into pixel-level behavior tracking (no cookies, no PII), AI insights that call out underperforming elements (e.g., a specific FAQ item), and how to catch bugs and bot traffic before they burn revenue.We also get tactical on replacing Google Optimize, the realities of SaaS pricing (and why “McDonald's pricing” works), and the rise of social search (TikTok as a top search engine) shaping product discovery more than LLM/Chat. If you own a P&L for a DTC brand—or you're the CRO/performance lead—this episode will make you money.What you'll learn→ How Dylan cold-outreaches to acquire companies & premium domains (the “urgent, must speak to founder” play)→ Why GA4 under-/over-reports vs Shopify—and how definitions (idle windows, engagement) distort truth→ The RPC/RPS (and coming RPV) metrics that finally connect elements → revenue→ Pixel-level behavior tracking (no cookies/PII) + AI insights that tell you exactly what to change→ Social search optimization (TikTok search often beats LLM/Chat for product discovery)→ Replacing Google Optimize and building reliable A/B workflows in 2025→ The real cost drivers behind SaaS pricing—and how to price without burning trust→ Bot/junk filtering and defining a “session” that reflects buyers, not noiseWho this is for→ DTC/eCommerce founders & growth leaders→ CROs, performance marketers, and Shopify teams→ SaaS operators curious about pricing, PLG, and analytics positioningTimestamp:00:00 Intro & why this convo matters for DTC02:00 The C-Corp acquisition story behind heatmap.com06:30 Exact-match domains, SEO, and the inbound engine09:20 GA4 vs Shopify: definitions that change your numbers16:30 RIP Google Optimize: reliable A/B testing in 202518:50 Element-level revenue: RPC, RPS (and RPV coming)22:30 Pixel-level tracking & AI insights (no cookies/PII)26:15 Catching bugs + filtering bots/junk traffic28:40 Social search: TikTok as a top product discovery engine31:20 SaaS pricing & the “McDonald's” strategy36:40 Who should use revenue-based heatmaps (and why)44:30 Contrarian analytics takes you need to hear55:10 Personal: life, music, and loving the gameGuestDylan Ander — Founder, heatmap.com (revenue-based heatmaps, funnels, analytics for ecom). Mentions his upcoming book, Billion Dollar Websites.

Will the stock market crash? With the market continuing to march higher and setting record high after record high, I do worry more and more that a crash could be coming. It doesn't mean it will happen tomorrow, next week, or maybe even this year, but I do believe the risk to reward of investing in the S&P 500 at this point is not favorable when you take all the data into consideration. I have talked a lot about the fact that the top 10 companies now account for nearly 40% of the entire index and the forward P/E multiple of around 22x is well above the 30-year average of 17x, but there are also less discussed factors that are quite concerning. There is something called the Buffett Indicator that looks at the total US stock market value compared to US GDP. Buffet even made the claim at one point that this was “the best single measure of where valuations stand at any given moment." The problem here is that it now exceeds 200%, which is a historic high and well above even the tech boom when it peaked around 150%. Another concerning measure is the Shiller PE ratio, which looks at the average inflation-adjusted earnings from the previous 10 years in relation to the current price of the index. This is now at a multiple around 39x, which is well above the 30-year average of 28.3 and at a level that was only seen during the tech boom. While valuation isn't always the best indicator for what will happen in the next year, it has proven to be a successful tool for long term investing. Unfortunately, valuations aren't my only concern. Margin expansion is even more frightening as the reliance on debt can derail investors. Margin allows investors to buy stocks with debt, but the big problem is if there is a decline and a margin call comes the investor would either have to add more cash or make sells, which causes a further decline in the stock due to added selling pressure. Margin debt has now topped $1 trillion, which is a record, and it has grown very quickly considering there was an 18% increase in margin usage from April to June. This was one of the fastest two month increases on record and rivals the 24.6% increase in December 1999 and the 20.3% increase in May 2007. In case you forgot, both of the periods that followed did not end well for investors. Looking at margin as a share of GDP, it is now higher than during the dot-com bubble and near the all-time high that was reached in 2021. One other concern with the margin level is it does not include securities-based loans, which is another tool that leverages stock positions and if there is a decline could cause added selling pressure. Unfortunately, this data is not as easy to find since they are lumped in with consumer credit. The most recent estimate I could find was in Q1 2024, they totaled $138 billion and with the risk on mentality that has occurred, my assumption is the total would be even higher now. We have to remember that we now are essentially 18 years into a market that has always had a buy the dip mentality. Even pullbacks that occurred in 2020 and 2022 saw rebounds take place quite quickly. This has created a generation of investors that have not actually experienced a difficult market. I always encourage people to study the tech boom and bust as it was devastating for investors. The S&P 500 fell 49% in the fallout from the dotcom bubble and it took about 7 years to recover. Investors in the Nasdaq fared even worse as they saw a 79% drop and it took 15 years to get back to those record levels. Unfortunately, this isn't the only historical period that saw difficult returns. If you look back to the start of 1964, the Dow was at 874 and by the end of 1981 it gained just one point to 875. This was an extremely difficult period that saw Vietnam War spending, stagflation, and oil shocks, but it again illustrates that difficult markets with little to no advancement can occur. So, with all of this, how are we investing at this time? We are maintaining our value approach, which generally holds up much better in difficult markets. For comparison, the Russell 1000 Value index was actually up 7% in 2000 while the Russell 1000 Growth index fell 22.4% that year. We are also maintaining our highest cash position around 25% since at least 2007.  I continue to believe there are opportunities for investors, it just requires discipline and patience. One other person remaining patient at this time is Warren Buffett. Berkshire now has near a record cash hoard of $344.1 billion and the conglomerate has been a net seller of stocks for the 11th quarter in a row. I'd rather follow people like Buffett at times like this over the Meme traders that have become popular once again.   Consumers are doing a better job managing their credit card debt  Data released by Truist Bank analysts show that card holders of both higher and lower scores are doing a better job paying their bills on time. This is based on a drop in the rate of late payments from last quarter. Also improving is debt servicing payments as a percent of consumers disposable personal income. The first quarter shows debt-servicing payments were roughly 11% of disposable income, which is a strong ratio to see considering that level is below what was typical before the start of 2020 and it's far below the 15%-plus levels that were seen leading up to the Great Recession in 2008. According to Fed data, card loan growth was only 3% year over a year, which could be due to lenders increasing their credit standards. Stricter standards also made it more difficult for subprime borrowers to obtain new credit cards considering the fact that as a share of new card accounts, this category accounted for just 16% of all new accounts. This was down roughly 7% from the last quarter in 2022 when it was 23%. Consumers may also be more aware of the high interest costs considering rates stood at 22% as of May. There has been a decrease in rates from the peak last year, but Fed data reveals before interest rates began rising in 2022 interest rates stood at 16% for card accounts. If the Fed were to drop rates a couple of times between now and the end of the year, we could see a small decline in the rate. With that said borrowing money on a credit card and accruing interest is a terrible idea as even a 16% rate would not be worth it!    Real estate investors may be supporting the real estate market. This may sound like a good thing, but this could be dangerous long-term since investors don't live at the property. It would be far easier for them to default on the mortgage and let the house go into foreclosure or sell at a price well below market value just to get their investment back. So far in 2025 investors have accounted for roughly 30% of sales of both existing and newly built homes, which is the highest share on record. This is according to property analytics firm Cotality and they started tracking the sales 14 years ago. Most of these investors were small investors, who own fewer than 100 homes as they accounted for roughly 25% of all purchases. This compares to large investors which accounted for only 5% of purchases of new and existing homes. Within the small investor space, the stronger category is those with just 3-9 properties as this group has accounted for between 14 and 15% of all sales each month this year. The data also shows that the large investors like Invitation Homes and Progress Residential have become net sellers in the market and are selling more properties than they are buying. This is likely due to reduced rents from the high competition in the rental market and a softening of the overall real estate market in certain areas that has not provided the expected return that they wanted. I do worry that the small investor here has less access to good data and is less disciplined with their investment strategy. They are likely buying homes because real estate has been a good investment for the last several years, but if the market were to turn, they would be more likely to panic and sell and they may not have the means to continue holding the real estate. I do believe if interest rates remain, housing prices could remain stable or perhaps even drop a little bit. It's important to remember long term mortgage rates generally stem from longer term debt instruments like a 10-year Treasury, rather than the short-term discount rate set by the Fed.   Financial Planning: When and How a Refinance is Helpful After several years of elevated mortgage rates, steady declines have made more homeowners candidates for refinancing, but a smart decision requires looking beyond the headline interest rate. The first question is whether the refinance actually reduces the rate, and if so, what third-party closing costs and discount points are involved. Every mortgage carries these costs, and paying points may not make sense if rates are expected to fall further and another refinance could be on the horizon, especially since few 30-year mortgages last their full term before a sale or another refi. The structure of the new loan also matters: should costs be paid upfront or rolled into the loan balance, and how long will the loan likely be kept? The real goal is to borrow at the lowest overall cost over the life of the loan, factoring in both the rate and the cost to obtain it. A lower rate and payment may feel like a win, but without careful structuring, it may not be the most cost-effective move, something mortgage brokers often overlook when focusing solely on rate reduction. Here's a real example from just last week. A homeowner with a $580,000 mortgage at 6.875% and a $3,900 monthly payment has the opportunity to refinance to 5.5%, lowering the payment to $3,500 with no additional cash due at closing, and saving roughly $80,000 in total interest over the life of the loan. At first glance, this looks like a no-brainer. However, this structure would only be ideal if the homeowner never had another chance to refinance, which is unlikely given their current rate of 6.875%. In this case, all costs were rolled into a new loan balance of $616,000—an increase of $36,000—explaining why no cash was required at closing. A better approach might be to refinance to a rate only slightly lower than 6.875%, still reducing both the monthly payment and lifetime interest, but without dramatically increasing the loan balance by rolling in discount point costs. Refinances can continue as long as rates are expected to decline, and the best time to pay points is in a “final” refinance when rates are no longer expected to drop so the benefit can be locked in for the long term.   Companies Discussed: Carrier Global Corporation (CARR), Polaris Inc. (PII) & Align Technology, Inc. (ALGN)

Getting the basics right before exploring Artificial Intelligence projects is the key message from my guest for this episode.Santosh Kaveti is the CEO and Founder of ProArch, a purpose-driven enterprise that accelerates value and increases resilience for its clients with consulting and technology services, enabled by cloud, guided by data, fueled by apps, and secured by design.His pro tip? First, get your data sorted - classification, access, governance etc.  Without this, you could be putting your organisation in harm's way and in this day and age, there is no excuse for not understanding the data you collect, what you do with it, how you manage, store and dispose of it.Once you have your data 'housekeeping' right, you can explore the amazing possibilities of AI confident in the knowledge that you won't be exposing confidential or personally identifiable information (PII) inadvertently. Santosh shares his vast experience in this space - I know you will enjoy listening as much as I did talking to him. Send us a textContact ABM Risk Partnership to optimise your risk management approach: email us: info@abmrisk.com.au Tweet us at @4RiskCme Visit our LinkedIn page https://www.linkedin.com/company/18394064/admin/ Thanks for listening to the show and please keep your guest suggestions coming!

Officials in St. Paul, Minnesota declare a state of emergency following a cyberattack. Hackers disrupt a major French telecom. A power outage causes widespread service disruptions for cloud provider Linode. Researchers reveal a critical authentication bypass flaw in an AI-driven app development platform. A new study shows AI training data is chock full of PII. Fallout continues for the Tea dating safety app. Hackers are actively exploiting a critical SAP NetWeaver vulnerability to deploy malware. CISA and the FBI update their Scattered Spider advisory. A Florida prison exposes personal information of visitors to all of its inmates. Our guest today is Keith Mularski, Chief Global Ambassador at Qintel, retired FBI Special Agent, and co-host of Only Malware in the Building. CISA and Senator Wyden come to terms —mostly— over the long-buried US Telecommunications Insecurity Report.  Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Our guest today is Keith Mularski, Chief Global Ambassador at Qintel, retired FBI Special Agent, and co-host of Only Malware in the Building discussing what it's like to be the new host on the N2K CyberWire network and giving a glimpse into some upcoming episodes. You can catch Keith and his co-hosts Selena Larson, Staff Threat Researcher and Lead, Intelligence Analysis and Strategy at Proofpoint, and our own Dave Bittner the first Tuesday of each month on your favorite podcast app with new episodes of Only Malware. Selected Reading Major cyberattack hits St. Paul, shuts down many services (Star Tribune) French telecom giant Orange discloses cyberattack (Bleeping Computer) Power Outage at Newark Data Center Disrupts Linode, Took LWN Offline (FOSS Force) Critical authentication bypass flaw reported in AI coding platform Base44 (Beyond Machines) A major AI training data set contains millions of examples of personal data (MIT Technology Review) Dating safety app Tea suspends messaging after hack (BBC) Hackers exploit SAP NetWeaver bug to deploy Linux Auto-Color malware (Bleeping Computer) CISA and FBI Release Tactics, Techniques, and Procedures of the Scattered Spider Hacker Group (gb hackers) Florida prison data breach exposes visitors' contact information to inmates (Florida Phoenix) CISA to release long-buried US telco security report (The Register) Audience Survey Complete our annual audience survey before August 31. Want to hear your company in the show? You too can reach the most influential leaders and operators in the industry. Here's our media kit. Contact us at cyberwire@n2k.com to request more info. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the pitfalls and best practices of “vibe coding” with generative AI. You will discover why merely letting AI write code creates significant risks. You will learn essential strategies for defining robust requirements and implementing critical testing. You will understand how to integrate security measures and quality checks into your AI-driven projects. You will gain insights into the critical human expertise needed to build stable and secure applications with AI. Tune in to learn how to master responsible AI coding and avoid common mistakes! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast_everything_wrong_with_vibe_coding_and_how_to_fix_it.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn – 00:00 In this week’s In-Ear Insights, if you go on LinkedIn, everybody, including tons of non-coding folks, has jumped into vibe coding, the term coined by OpenAI co-founder Andre Karpathy. A lot of people are doing some really cool stuff with it. However, a lot of people are also, as you can see on X in a variety of posts, finding out the hard way that if you don’t know what to ask for—say, application security—bad things can happen. Katie, how are you doing with giving into the vibes? Katie Robbert – 00:38 I’m not. I’ve talked about this on other episodes before. For those who don’t know, I have an extensive background in managing software development. I myself am not a software developer, but I have spent enough time building and managing those teams that I know what to look for and where things can go wrong. I’m still really skeptical of vibe coding. We talked about this on a previous podcast, which if you want to find our podcast, it’s @TrustInsightsAI_TIpodcast, or you can watch it on YouTube. My concern, my criticism, my skepticism of vibe coding is if you don’t have the basic foundation of the SDLC, the software development lifecycle, then it’s very easy for you to not do vibe coding correctly. Katie Robbert – 01:42 My understanding is vibe coding is you’re supposed to let the machine do it. I think that’s a complete misunderstanding of what’s actually happening because you still have to give the machine instruction and guardrails. The machine is creating AI. Generative AI is creating the actual code. It’s putting together the pieces—the commands that comprise a set of JSON code or Python code or whatever it is you’re saying, “I want to create an app that does this.” And generative AI is like, “Cool, let’s do it.” You’re going through the steps. You still need to know what you’re doing. That’s my concern. Chris, you have recently been working on a few things, and I’m curious to hear, because I know you rely on generative AI because yourself, you’ve said, are not a developer. What are some things that you’ve run into? Katie Robbert – 02:42 What are some lessons that you’ve learned along the way as you’ve been vibing? Christopher S. Penn – 02:50 Process is the foundation of good vibe coding, of knowing what to ask for. Think about it this way. If you were to say to Claude, ChatGPT, or Gemini, “Hey, write me a fiction novel set in the 1850s that’s a drama,” what are you going to get? You’re going to get something that’s not very good. Because you didn’t provide enough information. You just said, “Let’s do the thing.” You’re leaving everything up to the machine. That prompt—just that prompt alone. If you think about an app like a book, in this example, it’s going to be slop. It’s not going to be very good. It’s not going to be very detailed. Christopher S. Penn – 03:28 Granted, it doesn’t have the issues of code, but it’s going to suck. If, on the other hand, you said, “Hey, here’s the ideas I had for all the characters, here’s the ideas I had for the plot, here’s the ideas I had for the setting. But I want to have these twists. Here’s the ideas for the readability and the language I want you to use.” You provided it with lots and lots of information. You’re going to get a better result. You’re going to get something—a book that’s worth reading—because it’s got your ideas in it, it’s got your level of detail in it. That’s how you would write a book. The same thing is true of coding. You need to have, “Here’s the architecture, here’s the security requirements,” which is a big, big gap. Christopher S. Penn – 04:09 Here’s how to do unit testing, here’s the fact why unit tests are important. I hated when I was writing code by myself, I hated testing. I always thought, Oh my God, this is the worst thing in the world to have to test everything. With generative AI coding tools, I now am in love with testing because, in fact, I now follow what’s called test-driven development, where you write the tests first before you even write the production code. Because I don’t have to do it. I can say, “Here’s the code, here’s the ideas, here’s the questions I have, here’s the requirements for security, here’s the standards I want you to use.” I’ve written all that out, machine. “You go do this and run these tests until they’re clean, and you’ll just keep running over and fix those problems.” Christopher S. Penn – 04:54 After every cycle you do it, but it has to be free of errors before you can move on. The tools are very capable of doing that. Katie Robbert – 05:03 You didn’t answer my question, though. Christopher S. Penn – 05:05 Okay. Katie Robbert – 05:06 My question to you was, Chris Penn, what lessons have you specifically learned about going through this? What’s been going on, as much as you can share, because obviously we’re under NDA. What have you learned? Christopher S. Penn – 05:23 What I’ve learned: documentation and code drift very quickly. You have your PRD, you have your requirements document, you have your work plans. Then, as time goes on and you’re making fixes to things, the code and the documentation get out of sync very quickly. I’ll show an example of this. I’ll describe what we’re seeing because it’s just a static screenshot, but in the new Claude code, you have the ability to build agents. These are built-in mini-apps. My first one there, Document Code Drift Auditor, goes through and says, “Hey, here’s where your documentation is out of line with the reality of your code,” which is a big deal to make sure that things stay in sync. Christopher S. Penn – 06:11 The second one is a Code Quality Auditor. One of the big lessons is you can’t just say, “Fix my code.” You have to say, “You need to give me an audit of what’s good about my code, what’s bad about my code, what’s missing from my code, what’s unnecessary from my code, and what silent errors are there.” Because that’s a big one that I’ve had trouble with is silent errors where there’s not something obviously broken, but it’s not quite doing what you want. These tools can find that. I can’t as a person. That’s just me. Because I can’t see what’s not there. A third one, Code Base Standards Inspector, to look at the standards. This is one that it says, “Here’s a checklist” because I had to write—I had to learn to write—a checklist of. Christopher S. Penn – 06:51 These are the individual things I need you to find that I’ve done or not done in the codebase. The fourth one is logging. I used to hate logging. Now I love logs because I can say in the PRD, in the requirements document, up front and throughout the application, “Write detailed logs about what’s happening with my application” because that helps machine debug faster. I used to hate logs, and now I love them. I have an agent here that says, “Go read the logs, find errors, fix them.” Fifth lesson: debt collection. Technical debt is a big issue. This is when stuff just accumulates. As clients have new requests, “Oh, we want to do this and this and this.” Your code starts to drift even from its original incarnation. Christopher S. Penn – 07:40 These tools don’t know to clean that up unless you tell it to. I have a debt collector agent that goes through and says, “Hey, this is a bunch of stuff that has no purpose anymore.” And we can then have a conversation about getting rid of it without breaking things. Which, as a thing, the next two are painful lessons that I’ve learned. Progress Logger essentially says, after every set of changes, you need to write a detailed log file in this folder of that change and what you did. The last one is called Docs as Data Curator. Christopher S. Penn – 08:15 This is where the tool goes through and it creates metadata at the top of every progress entry that says, “Here’s the keywords about what this bug fixes” so that I can later go back and say, “Show me all the bug fixes that we’ve done for BigQuery or SQLite or this or that or the other thing.” Because what I found the hard way was the tools can introduce regressions. They can go back and keep making the same mistake over and over again if they don’t have a logbook of, “Here’s what I did and what happened, whether it worked or not.” By having these set—these seven tools, these eight tools—in place, I can prevent a lot of those behaviors that generative AI tends to have. Christopher S. Penn – 08:54 In the same way that you provide a writing style guide so that AI doesn’t keep making the mistake of using em dashes or saying, “in a world of,” or whatever the things that you do in writing. My hard-earned lessons I’ve encoded into agents now so that I don’t keep making those mistakes, and AI doesn’t keep making those mistakes. Katie Robbert – 09:17 I feel you’re demonstrating my point of my skepticism with vibe coding because you just described a very lengthy process and a lot of learnings. I’m assuming what was probably a lot of research up front on software development best practices. I actually remember the day that you were introduced to unit tests. It wasn’t that long ago. And you’re like, “Oh, well, this makes it a lot easier.” Those are the kinds of things that, because, admittedly, software development is not your trade, it’s not your skillset. Those are things that you wouldn’t necessarily know unless you were a software developer. Katie Robbert – 10:00 This is my skepticism of vibe coding: sure, anybody can use generative AI to write some code and put together an app, but then how stable is it, how secure is it? You still have to know what you’re doing. I think that—not to be too skeptical, but I am—the more accessible generative AI becomes, the more fragile software development is going to become. It’s one thing to write a blog post; there’s not a whole lot of structure there. It’s not powering your website, it’s not the infrastructure that holds together your entire business, but code is. Katie Robbert – 11:03 That’s where I get really uncomfortable. I’m fine with using generative AI if you know what you’re doing. I have enough knowledge that I could use generative AI for software development. It’s still going to be flawed, it’s still going to have issues. Even the most experienced software developer doesn’t get it right the first time. I’ve never in my entire career seen that happen. There is no such thing as the perfect set of code the first time. I think that people who are inexperienced with the software development lifecycle aren’t going to know about unit tests, aren’t going to know about test-based coding, or peer testing, or even just basic QA. Katie Robbert – 11:57 It’s not just, “Did it do the thing,” but it’s also, “Did it do the thing on different operating systems, on different browsers, in different environments, with people doing things you didn’t ask them to do, but suddenly they break things?” Because even though you put the big “push me” button right here, someone’s still going to try to click over here and then say, “I clicked on your logo. It didn’t work.” Christopher S. Penn – 12:21 Even the vocabulary is an issue. I’ll give you four words that would automatically uplevel your Python vibe coding better. But these are four words that you probably have never heard of: Ruff, MyPy, Pytest, Bandit. Those are four automated testing utilities that exist in the Python ecosystem. They’ve been free forever. Ruff cleans up and does linting. It says, “Hey, you screwed this up. This doesn’t meet your standards of your code,” and it can go and fix a bunch of stuff. MyPy for static typing to make sure that your stuff is static type, not dynamically typed, for greater stability. Pytest runs your unit tests, of course. Bandit looks for security holes in your Python code. Christopher S. Penn – 13:09 If you don’t know those exist, you probably say you’re a marketer who’s doing vibe coding for the first time, because you don’t know they exist. They are not accessible to you, and generative AI will not tell you they exist. Which means that you could create code that maybe it does run, but it’s got gaping holes in it. When I look at my standards, I have a document of coding standards that I’ve developed because of all the mistakes I’ve made that it now goes in every project. This goes, “Boom, drop it in,” and those are part of the requirements. This is again going back to the book example. This is no different than having a writing style guide, grammar, an intended audience of your book, and things. Christopher S. Penn – 13:57 The same things that you would go through to be a good author using generative AI, you have to do for coding. There’s more specific technical language. But I would be very concerned if anyone, coder or non-coder, was just releasing stuff that didn’t have the right safeguards in it and didn’t have good enough testing and evaluation. Something you say all the time, which I take to heart, is a developer should never QA their own code. Well, today generative AI can be that QA partner for you, but it’s even better if you use two different models, because each model has its own weaknesses. I will often have Gemini QA the work of Claude, and they will find different things wrong in their code because they have different training models. These two tools can work together to say, “What about this?” Christopher S. Penn – 14:48 “What about this?” And they will. I’ve actually seen them argue, “The previous developers said this. That’s not true,” which is entertaining. But even just knowing that rule exists—a developer should not QA their own code—is a blind spot that your average vibe coder is not going to have. Katie Robbert – 15:04 Something I want to go back to that you were touching upon was the privacy. I’ve seen a lot of people put together an app that collects information. It could collect basic contact information, it could collect other kind of demographic information, it can collect opinions and thoughts, or somehow it’s collecting some kind of information. This is also a huge risk area. Data privacy has always been a risk. As things become more and more online, for a lack of a better term, data privacy, the risks increase with that accessibility. Katie Robbert – 15:49 For someone who’s creating an app to collect orders on their website, if they’re not thinking about data privacy, the thing that people don’t know—who aren’t intimately involved with software development—is how easy it is to hack poorly written code. Again, to be super skeptical: in this day and age, everything is getting hacked. The more AI is accessible, the more hackable your code becomes. Because people can spin up these AI agents with the sole purpose of finding vulnerabilities in software code. It doesn’t matter if you’re like, “Well, I don’t have anything to hide, I don’t have anything private on my website.” It doesn’t matter. They’re going to hack it anyway and start to use it for nefarious things. Katie Robbert – 16:49 One of the things that we—not you and I, but we in my old company—struggled with was conducting those security tests as part of the test plan because we didn’t have someone on the team at the time who was thoroughly skilled in that. Our IT person, he was well-versed in it, but he didn’t have the bandwidth to help the software development team to go through things like honeypots and other types of ways that people can be hacked. But he had the knowledge that those things existed. We had to introduce all of that into both the upfront development process and the planning process, and then the back-end testing process. It added additional time. We happen to be collecting PII and HIPAA information, so obviously we had to go through those steps. Katie Robbert – 17:46 But to even understand the basics of how your code can be hacked is going to be huge. Because it will be hacked if you do not have data privacy and those guardrails around your code. Even if your code is literally just putting up pictures on your website, guess what? Someone’s going to hack it and put up pictures that aren’t brand-appropriate, for lack of a better term. That’s going to happen, unfortunately. And that’s just where we’re at. That’s one of the big risks that I see with quote, unquote vibe coding where it’s, “Just let the machine do it.” If you don’t know what you’re doing, don’t do it. I don’t know how many times I can say that, or at the very. Christopher S. Penn – 18:31 At least know to ask. That’s one of the things. For example, there’s this concept in data security called principle of minimum privilege, which is to grant only the amount of access somebody needs. Same is true for principle of minimum data: collect only information that you actually need. This is an example of a vibe-coded project that I did to make a little Time Zone Tracker. You could put in your time zones and stuff like that. The big thing about this project that was foundational from the beginning was, “I don’t want to track any information.” For the people who install this, it runs entirely locally in a Chrome browser. It does not collect data. There’s no backend, there’s no server somewhere. So it stays only on your computer. Christopher S. Penn – 19:12 The only thing in here that has any tracking whatsoever is there’s a blue link to the Trust Insights website at the very bottom, and that has Google Track UTM codes. That’s it. Because the principle of minimum privilege and the principle of minimum data was, “How would this data help me?” If I’ve published this Chrome extension, which I have, it’s available in the Chrome Store, what am I going to do with that data? I’m never going to look at it. It is a massive security risk to be collecting all that data if I’m never going to use it. It’s not even built in. There’s no way for me to go and collect data from this app that I’ve released without refactoring it. Christopher S. Penn – 19:48 Because we started out with a principle of, “Ain’t going to use it; it’s not going to provide any useful data.” Katie Robbert – 19:56 But that I feel is not the norm. Christopher S. Penn – 20:01 No. And for marketers. Katie Robbert – 20:04 Exactly. One, “I don’t need to collect data because I’m not going to use it.” The second is even if you’re not collecting any data, is your code still hackable so that somebody could hack into this set of code that people have running locally and change all the time zones to be anti-political leaning, whatever messages that they’re like, “Oh, I didn’t realize Chris Penn felt that way.” Those are real concerns. That’s what I’m getting at: even if you’re publishing the most simple code, make sure it’s not hackable. Christopher S. Penn – 20:49 Yep. Do that exercise. Every software language there is has some testing suite. Whether it’s Chrome extensions, whether it’s JavaScript, whether it’s Python, because the human coders who have been working in these languages for 10, 20, 30 years have all found out the hard way that things go wrong. All these automated testing tools exist that can do all this stuff. But when you’re using generative AI, you have to know to ask for it. You have to say. You can say, “Hey, here’s my idea.” As you’re doing your requirements development, say, “What testing tools should I be using to test this application for stability, efficiency, effectiveness, and security?” Those are the big things. That has to be part of the requirements document. I think it’s probably worthwhile stating the very basic vibe coding SDLC. Christopher S. Penn – 21:46 Build your requirements, check your requirements, build a work plan, execute the work plan, and then test until you’re sick of testing, and then keep testing. That’s the process. AI agents and these coding agents can do the “fingers on keyboard” part, but you have to have the knowledge to go, “I need a requirements document.” “How do I do that?” I can have generative AI help me with that. “I need a work plan.” “How do I do that?” Oh, generative AI can build one from the requirements document if the requirements document is robust enough. “I need to implement the code.” “How do I do that?” Christopher S. Penn – 22:28 Oh yeah, AI can do that with a coding agent if it has a work plan. “I need to do QA.” “How do I do that?” Oh, if I have progress logs and the code, AI can do that if it knows what to look for. Then how do I test? Oh, AI can run automated testing utilities and fix the problems it finds, making sure that the code doesn’t drift away from the requirements document until it’s done. That’s the bare bones, bare minimum. What’s missing from that, Katie? From the formal SDLC? Katie Robbert – 23:00 That’s the gist of it. There’s so much nuance and so much detail. This is where, because you and I, we were not 100% aligned on the usage of AI. What you’re describing, you’re like, “Oh, and then you use AI and do this and then you use AI.” To me, that immediately makes me super anxious. You’re too heavily reliant on AI to get it right. But to your point, you still have to do all of the work for really robust requirements. I do feel like a broken record. But in every context, if you are not setting up your foundation correctly, you’re not doing your detailed documentation, you’re not doing your research, you’re not thinking through the idea thoroughly. Katie Robbert – 23:54 Generative AI is just another tool that’s going to get it wrong and screw it up and then eventually collect dust because it doesn’t work. When people are worried about, “Is AI going to take my job?” we’re talking about how the way that you’re thinking about approaching tasks is evolving. So you, the human, are still very critical to this task. If someone says, “I’m going to fire my whole development team, the machines, Vibe code, good luck,” I have a lot more expletives to say with that, but good luck. Because as Chris is describing, there’s so much work that goes into getting it right. Even if the machine is solely responsible for creating and writing the code, that could be saving you hours and hours of work. Because writing code is not easy. Katie Robbert – 24:44 There’s a reason why people specialize in it. There’s still so much work that has to be done around it. That’s the thing that people forget. They think they’re saving time. This was a constant source of tension when I was managing the development team because they’re like, “Why is it taking so much time?” The developers have estimated 30 hours. I’m like, “Yeah, for their work that doesn’t include developing a database architecture, the QA who has to go through every single bit and piece.” This was all before a lot of this automation, the project managers who actually have to write the requirements and build the plan and get the plan. All of those other things. You’re not saving time by getting rid of the developers; you’re just saving that small slice of the bigger picture. Christopher S. Penn – 25:38 The rule of thumb, generally, with humans is that for every hour of development, you’re going to have two to four hours of QA time, because you need to have a lot of extra eyes on the project. With vibe coding, it’s between 10 and 20x. Your hour of vibe coding may shorten dramatically. But then you’re going to. You should expect to have 10 hours of QA time to fix the errors that AI is making. Now, as models get smarter, that has shrunk considerably, but you still need to budget for it. Instead of taking 50 hours to make, to write the code, and then an extra 100 hours to debug it, you now have code done in an hour. But you still need the 10 to 20 hours to QA it. Christopher S. Penn – 26:22 When generative AI spits out that first draft, it’s every other first draft. It ain’t done. It ain’t done. Katie Robbert – 26:31 As we’re wrapping up, Chris, if possible, can you summarize your recent lesson learned from using AI for software development—what is the one thing, the big lesson that you took away? Christopher S. Penn – 26:50 If we think of software development like the floors of a skyscraper, everyone wants the top floor, which is the scenic part. That’s cool, and everybody can go up there. It is built on a foundation and many, many floors of other things. And if you don’t know what those other floors are, your top floor will literally fall out of the sky. Because it won’t be there. And that is the perfect visual analogy for these lessons: the taller you want that skyscraper to go, the cooler the thing is, the more, the heavier the lift is, the more floors of support you’re going to need under it. And if you don’t have them, it’s not going to go well. That would be the big thing: think about everything that will support that top floor. Christopher S. Penn – 27:40 Your overall best practices, your overall coding standards for a specific project, a requirements document that has been approved by the human stakeholders, the work plans, the coding agents, the testing suite, the actual agentic sewing together the different agents. All of that has to exist for that top floor, for you to be able to build that top floor and not have it be a safety hazard. That would be my parting message there. Katie Robbert – 28:13 How quickly are you going to get back into a development project? Christopher S. Penn – 28:19 Production for other people? Not at all. For myself, every day. Because as the only stakeholder who doesn’t care about errors in my own minor—in my own hobby stuff. Let’s make that clear. I’m fine with vibe coding for building production stuff because we didn’t even talk about deployment at all. We touched on it. Just making the thing has all these things. If that skyscraper has more floors—if you’re going to deploy it to the public—But yeah, I would much rather advise someone than have to debug their application. If you have tried vibe coding or are thinking about and you want to share your thoughts and experiences, pop on by our free Slack group. Christopher S. Penn – 29:05 Go to TrustInsights.ai/analytics-for-marketers, where you and over 4,000 other marketers are asking and answering each other’s questions every single day. Wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on instead, we’re probably there. Go to TrustInsights.ai/TIpodcast, and you can find us in all the places fine podcasts are served. Thanks for tuning in, and we’ll talk to you on the next one. Katie Robbert – 29:31 Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch, and optimizing content strategies. Katie Robbert – 30:24 Trust Insights also offers expert guidance on social media analytics, marketing technology and martech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What? livestream webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Katie Robbert – 31:30 Data Storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

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//The Wire//2300Z July 25, 2025////ROUTINE////BLUF: "DATING" APP DATA BREACH HIGHLIGHTS NATIONAL SECURITY CONCERNS.// -----BEGIN TEARLINE------HomeFront-USA: This morning a major PII leak was exploited on the Tea app, the infamous app that has gained notoriety around the United States. This data leak was not a hack by any means; the selfie ID feature and driver's license images used to register users were stored unencrypted on the app's servers for anyone on the internet to see. Furthermore, the location data was not scrubbed from the images, so the exact GPS coordinate of each user was also leaked, with tens of thousands of users' private location data being leaked online.-----END TEARLINE-----Analyst Comments: This app gained infamy as it's entire purpose is to serve as a "Yelp" for women to rate men, and to allow women to secretly share personal information regarding prospective dates, all without men being allowed to either face their accusers or even know that they are being gossiped about (thus the name of the app being a slang term that serves as a synonym for "gossip"). Most importantly, the app uses facial recognition to prevent biological males from obtaining an account. Beyond the unfortunate origins of the app and the equally unfortunate data leak, examination of the data that was leaked is likely to cause exceptionally grave risks to national security. The "gossipy" nature of this story doesn't matter, a bunch of unflattering selfies doesn't matter either; what does matter is that this may have inadvertently revealed significant national security concerns.For instance, preliminary analysis of the datasets indicates that many users of the Tea app downloaded the app, took a selfie, and registered for an account while at work. In some cases, at government facilities or on military bases...such as the rather unfortunate individual who decided it was a good idea to register for this app while stationed at Marine Corps Base Quantico. Or the person who felt that they needed to use this app while on a gunnery range at the Aberdeen Proving Grounds. So far, other interesting sites located via personnel taking a selfie to register for this app at work include the following locations:- An ammunition storage bunker at Naval Weapons Station Earle in New Jersey.- The legislative offices at the Connecticut State Capitol building.- One of the headquarters buildings at Minot Air Force Base.- A maintenance site on the airfield at Eglin Air Force Base.- Alumni Hall at the US Naval Academy in Annapolis.- And the off-base housing complexes at nearly every single military base in the United States.Of course, these data points only encompass the GPS coordinates that were embedded in the metadata of the selfies taken when users created an account on the app, so the data that was leaked is merely a snapshot of wherever a person was when they registered an account. Most of the GPS points presented in this data were very precise, pinpointing users within a diameter of 36ft or so on average. GPS errors are also likely to throw off this dataset, so it's probable that quite a few data points are inaccurate. However, most of the data (as leaked) is good enough for nationstate-level malign actors to have a field day when it comes to espionage. A person who is unhappy with the person they are in a relationship with, who is also willing to submit their full legal name and street address (or GPS location) makes for a prime espionage target when this data is cross-referenced with other data. It takes exactly two clicks to import the leaked data to a map, and overlay that map with known sensitive military sites around the nation...perhaps in the process finding a few new locations as well. It is also easy to cross-reference this data with property ownership documents to find out how many people took a selfie at a different ad

Donata Stroink-Skillrud is an attorney licensed in Illinois, a Certified Information Privacy Professional, and President of Termageddon, a SaaS platform transforming how eCommerce businesses handle legal compliance. Built at the intersection of privacy law expertise and technology, Termageddon helps online businesses stay compliant with ever-changing privacy regulations, without needing a legal team.After years of working directly with contract law, consumer protection, and international privacy regulations, Donata saw firsthand how fragmented, outdated, and risky privacy compliance had become for Ecommerce websites. What started as manual legal work soon evolved into an automated solution that identifies which privacy laws apply to a business and generates up-to-date, accurate website policies in minutes—not weeks.Donata brings a legal insider's perspective to the realities of online selling, breaking down complex regulations into practical steps for founders. From helping brands avoid FTC fines on subscription renewals, to clarifying why state privacy laws apply to your store, Donata explains the hidden legal pitfalls that quietly erode Ecommerce growth and how to protect against them.Whether sharing how generic privacy templates leave stores exposed, why recurring billing pages are the newest legal battleground, or how to future-proof your policies against incoming U.S. state laws, Donata delivers a tactical, no-nonsense playbook for reducing legal risk and building customer trust.In This Conversation We Discuss: [00:42] Intro[01:04] Breaking down contract laws for entrepreneurs[02:02] Explaining why Shopify won't cover your compliance[03:57] Breaking down real costs of ignoring privacy laws[06:53] Clarifying why location won't shield your store[08:10] Highlighting false refund claims that trigger fines[11:54] Identifying which privacy laws apply to you[13:36] Turning repetitive legal work into automation[14:55] Updating policies before laws take effect[16:29] Receiving automatic updates without extra effort[17:15] Saving weeks of legal work with automation[18:12] Staying compliant as privacy laws keep changingResources:Subscribe to Honest Ecommerce on YoutubeProtects business from fines and lawsuits termageddon.com/Follow Donata Stroink-Skillrud linkedin.com/in/donata-stroink-skillrudIf you're enjoying the show, we'd love it if you left Honest Ecommerce a review on Apple Podcasts. It makes a huge impact on the success of the podcast, and we love reading every one of your reviews!

In the security news: The train is leaving the station, or is it? The hypervisor will protect you, maybe The best thing about Flippers are the clones Also, the Flipper Zero as an interrogation tool Threats are commercial and open-source Who is still down with FTP? AI bug hunters Firmware for Russian drones Merging Android and ChromOS Protecting your assets with CVSS? Patch Citrixbleed 2 Rowhammer comes to NVIDIA GPUs I hear Microsoft hires Chinese spies Gigabyte motherboards and UEFI vulnerabilities McDonald's AI hiring bot: you want some PII with that? Visit https://www.securityweekly.com/psw for all the latest episodes! Show Notes: https://securityweekly.com/psw-883

In the security news: The train is leaving the station, or is it? The hypervisor will protect you, maybe The best thing about Flippers are the clones Also, the Flipper Zero as an interrogation tool Threats are commercial and open-source Who is still down with FTP? AI bug hunters Firmware for Russian drones Merging Android and ChromOS Protecting your assets with CVSS? Patch Citrixbleed 2 Rowhammer comes to NVIDIA GPUs I hear Microsoft hires Chinese spies Gigabyte motherboards and UEFI vulnerabilities McDonald's AI hiring bot: you want some PII with that? Show Notes: https://securityweekly.com/psw-883

In the security news: The train is leaving the station, or is it? The hypervisor will protect you, maybe The best thing about Flippers are the clones Also, the Flipper Zero as an interrogation tool Threats are commercial and open-source Who is still down with FTP? AI bug hunters Firmware for Russian drones Merging Android and ChromOS Protecting your assets with CVSS? Patch Citrixbleed 2 Rowhammer comes to NVIDIA GPUs I hear Microsoft hires Chinese spies Gigabyte motherboards and UEFI vulnerabilities McDonald's AI hiring bot: you want some PII with that? Visit https://www.securityweekly.com/psw for all the latest episodes! Show Notes: https://securityweekly.com/psw-883

In the security news: The train is leaving the station, or is it? The hypervisor will protect you, maybe The best thing about Flippers are the clones Also, the Flipper Zero as an interrogation tool Threats are commercial and open-source Who is still down with FTP? AI bug hunters Firmware for Russian drones Merging Android and ChromOS Protecting your assets with CVSS? Patch Citrixbleed 2 Rowhammer comes to NVIDIA GPUs I hear Microsoft hires Chinese spies Gigabyte motherboards and UEFI vulnerabilities McDonald's AI hiring bot: you want some PII with that? Show Notes: https://securityweekly.com/psw-883

Send us a textCheck us out at:  https://www.cisspcybertraining.com/Get access to 360 FREE CISSP Questions:  https://www.cisspcybertraining.com/offers/dzHKVcDB/checkoutReady to master data classification for your CISSP exam? This episode delivers exactly what you need through fifteen practical questions that mirror real exam scenarios, all focused on Domain 2.1.1.The cybersecurity world is constantly evolving, and our discussion of the newly formed ARPA-H demonstrates this perfectly. Modeled after DARPA but focused on healthcare innovation, this agency represents a $50 million opportunity for security professionals to tackle the persistent ransomware threats plaguing the healthcare industry.Diving into our practice questions, we explore how marketing materials receive "sensitive" classifications, while revolutionary battery technology blueprints warrant "class three severe impact" protection. We clarify why social security numbers in healthcare settings fall under Protected Health Information rather than just PII, and why government agencies use distinctive classification schemas including terms like "top secret" that aren't merely arbitrary labels.The episode tackles complex scenarios including cloud storage responsibilities (you retain ownership of customer data even when stored by third parties), the limitations of DLP solutions for printed documents, and proper breach response protocols. Each question provides context-rich explanations that go beyond simple answers to build your understanding of the underlying principles.Perhaps most valuable is our exploration of classification system design - revealing why simply labeling all non-public information as "sensitive" creates security vulnerabilities by failing to distinguish between different impact levels. This practical insight helps you not just memorize concepts but understand how to implement effective classification in real-world environments.Whether you're studying for your CISSP exam or wanting to strengthen your organization's security posture, these fifteen questions provide the perfect framework for mastering data classification principles. Visit cisspcybertraining.com to access our complete blueprint and mentoring services guaranteed to help you pass the CISSP exam on your first attempt.Gain exclusive access to 360 FREE CISSP Practice Questions delivered directly to your inbox! Sign up at FreeCISSPQuestions.com and receive 30 expertly crafted practice questions every 15 days for the next 6 months—completely free! Don't miss this valuable opportunity to strengthen your CISSP exam preparation and boost your chances of certification success. Join now and start your journey toward CISSP mastery today!

This week we're joined by Julia Fallon, Executive Director of the State Educational Technology Directors Association (SETDA) and she shines a light on the appeal of school systems to cyber attackers. (HINT: it is access to PII to open credit cards, mortgages and more in the name of children that often is only detected many years later.) We also discuss the connection between schools and insurance companies, trends in how school systems are fortifying their security measures, the evolution of infosec to become a front office issue, and what schools can do to integrate cybersecurity into curriculums to both bolster security and lay a pathway for future cyber professionals.   Julia Fallon is the Executive Director of the State Educational Technology Directors Association (SETDA), where she works with U.S. state and territorial digital learning leaders to empower the education community to leverage technology for learning, teaching, and school operations. Involved with learning technologies since 1989, her professional interest lies in making the case for public school systems wherein educators are able to optimize technology-rich learning environments to equitably engage the learners who fill their classrooms. For links and resources discussed in this episode, please visit our show notes at https://www.forcepoint.com/govpodcast/e339

In this episode of The Good Life EDU Podcast, host Andrew Easton reconnects with longtime friend (and podcast guest) Rachelle Dene Poth for a timely and insightful discussion about the legal implications of AI in education. Drawing from her experience as an educator, speaker, and attorney, Rachelle unpacks some of the critical and often overlooked considerations educators should keep in mind when integrating AI tools into schools and classrooms. Listeners will learn: Why AI literacy goes far beyond knowing how to use tools How AI is being misused in cases of cyberbullying—and what educators should know What legal considerations (like FERPA and COPPA) apply to AI tools in schools The dangers of uploading PII to generative AI models How to foster a district culture of responsible AI use for both staff and students Whether you're just starting to explore AI or you're leading its implementation in your district, this conversation offers valuable guidance on what to prioritize and how to stay compliant and ethical in the process. Connect with Rachelle and explore her work: Website/Blog: www.rdene915.com Socials: @Rdene915 (Instagram, X, Threads, LinkedIn) Recent Books Released: How to Teach AI and What the Tech

Kory Daniels, Chief Information Security Officer at Trustwave,  highlights the unique cybersecurity challenges facing the healthcare industry, particularly in this environment of funding constraints and the increasing sophistication of cyberattacks. Healthcare data is highly valuable to cybercriminals, who can use it for ransomware attacks, identity and insurance fraud, and other nefarious purposes. AI can be part of both the attack and the solution, helping to build in more cyber resilience and awareness about vulnerabilities. Kory explains, "Healthcare is a prime target for cyberattacks for a very fundamental reason. When human lives are at risk due to a criminal objective—which is to make money—they view organizations where human lives are at risk as a greater potential and opportunity. Facilitation of ransomware payments: Ransomware is one of the largest tactics that criminals use to achieve financial gain, but it's not the only tactic they use to achieve financial gain. So, they're looking to exploit the fear and uncertainty, putting patient lives at risk and adding complexity to patient care through their nefarious actions. But also, healthcare data is very attractive for cybercriminals, and just criminal activity in general. And why that is, is that criminals are looking at healthcare data even more so—it's more valuable than driver's license data." "Look at the opportunity of what you can do with healthcare records, and what can you do with PII, Personally Identifiable Information. Threat actors are tapping into this data in several different ways to achieve the additional financial gain above and beyond targeting a healthcare organization with a ransomware attack." "But they're also committing fraud, and fraud toward healthcare insurers, and looking at submitting false claims, fraud against the prescription drug industry in terms of soliciting and looking to obtain prescription drugs through nefarious means, but utilizing data and identity data that comes from hospital and healthcare records. There are a variety of different ways that we've just scratched the surface on, which make the healthcare industry such a desirable target for those seeking to achieve financial gain in the criminal industry." #Trustwave #Cybersecurity #CyberAttacks #HealthcareSecurity #HealthcareIT #CISOInsights trustwave.com Download the transcript here

Kory Daniels, Chief Information Security Officer at Trustwave,  highlights the unique cybersecurity challenges facing the healthcare industry, particularly in this environment of funding constraints and the increasing sophistication of cyberattacks. Healthcare data is highly valuable to cybercriminals, who can use it for ransomware attacks, identity and insurance fraud, and other nefarious purposes. AI can be part of both the attack and the solution, helping to build in more cyber resilience and awareness about vulnerabilities. Kory explains, "Healthcare is a prime target for cyberattacks for a very fundamental reason. When human lives are at risk due to a criminal objective—which is to make money—they view organizations where human lives are at risk as a greater potential and opportunity. Facilitation of ransomware payments: Ransomware is one of the largest tactics that criminals use to achieve financial gain, but it's not the only tactic they use to achieve financial gain. So, they're looking to exploit the fear and uncertainty, putting patient lives at risk and adding complexity to patient care through their nefarious actions. But also, healthcare data is very attractive for cybercriminals, and just criminal activity in general. And why that is, is that criminals are looking at healthcare data even more so—it's more valuable than driver's license data." "Look at the opportunity of what you can do with healthcare records, and what can you do with PII, Personally Identifiable Information. Threat actors are tapping into this data in several different ways to achieve the additional financial gain above and beyond targeting a healthcare organization with a ransomware attack." "But they're also committing fraud, and fraud toward healthcare insurers, and looking at submitting false claims, fraud against the prescription drug industry in terms of soliciting and looking to obtain prescription drugs through nefarious means, but utilizing data and identity data that comes from hospital and healthcare records. There are a variety of different ways that we've just scratched the surface on, which make the healthcare industry such a desirable target for those seeking to achieve financial gain in the criminal industry." #Trustwave #Cybersecurity #CyberAttacks #HealthcareSecurity #HealthcareIT #CISOInsights trustwave.com Listen to the podcast here

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Recent digital developments show a growing gap between technological innovation and the protections needed to safeguard privacy, autonomy, and society at large. A string of high-profile incidents showcases the systemic vulnerabilities across sectors.Data breaches remain rampant. LexisNexis Risk Solutions, a leading data broker, suffered a breach via a third-party vendor, compromising the PII of over 364,000 individuals. This underscores the inherent risks of outsourcing sensitive data and the challenge of securing even “security-focused” firms.Retail giants like Cartier, Victoria's Secret, Harrods, and Marks & Spencer have been targeted by cyberattacks, exposing customer data and causing disruptions. Notably, Marks & Spencer reported potential losses of up to £300 million. Credential-stuffing attacks, such as the one affecting The North Face, exploit reused passwords from earlier breaches, emphasizing the cascading risks of weak user hygiene.Social media platforms are still vulnerable. A scraping operation exposed data from 1.2 billion Facebook users due to a public API flaw—reaffirming that even mature platforms are prone to exploitation when data is monetizable at scale.Government surveillance is expanding in concerning ways. The U.S. has collected DNA from over 133,000 migrant children—many without criminal charges—and stored it in a national criminal database. This raises major ethical concerns about consent, privacy, and the erosion of legal norms like the presumption of innocence.Brazil's dWallet initiative offers a contrasting vision: enabling citizens to monetize their personal data. While empowering, it also prompts questions about equity, digital literacy, and the unintended consequences of commodifying identity.AI tools are now weaponizing digital footprints. “YouTube-Tools” scrapes public comments and uses AI to infer users' locations, political views, and more—posing risks of harassment and surveillance, despite being marketed for law enforcement.LLMs show serious limitations in sustained, autonomous operations. Simulations involving AI running simple businesses failed dramatically—some models contacted the FBI, others misunderstood basic logic, showing how far AI remains from reliable real-world decision-making.AI ethics research via "SnitchBench" shows that some models will autonomously report unethical behavior, raising questions around AI moral agency and alignment—specifically, when and how AI should intervene in human affairs.Finally, a grave data leak in Russia revealed nuclear infrastructure details through a procurement portal—due to careless document handling. This illustrates that critical security failures often originate not from elite hacks, but from bureaucratic neglect.

Do you REALLY know what cookies are? Like really, REALLY know? What about GDPR? What about PII?I know the words. But what do they REALLY mean? I enlisted the help of Eddie "The Techie" Aguilar to help me simplify some of these complex topics, and help me create meaningful next steps on how to address PII concerns and other marketing-related issues in data collection. We got into:- Simplified definitions of cookies, data collection, GDPR, etc. (I'm stupid and like hearing things simplified from smart people)- First vs. Third part cookies (and what it means to your marketing program)- A/B testing and the importance of NOT collecting PII in your testing toolsTimestamps:00:00 Episode Start2:31 What is a Cookie?7:41 How Cookies Have Been Used Maliciously (Lack of Consent)9:51 First Party vs. Third Party Data13:11 Opting Out of Cookies (Explained)14:45 GDPR28:20 A/B Testing and Cookies37:30 PII and A/B testingGo follow Eddie Aguilar on LinkedIn: https://www.linkedin.com/in/whoiseddie/ Also go follow Shiva Manjunath on LinkedIn: ⁠https://www.linkedin.com/in/shiva-manjunath/⁠Subscribe to our newsletter for more memes, clips, and awesome content! https://fromatob.beehiiv.com/And go get your free ticket for the Women in Experimentation - you might even be entered to win some From A to B merch! : https://tinyurl.com/FromAtoB-WIE

Join Oyster experts as they provide real-world insight into the shifting CAT and CAIS landscape, including:The current regulatory focus on removing PII information from CAIS reportingImplementation uncertainty - where FINRA guidance falls shortMember firms grappling with the scope of PII removal at account and customer levelsBlue sheets and CAIS - redundant reporting and integration challengesCAT reporting's critical role in market surveillance during volatile trading periodsHow the multi-year phased implementation approach provides a potential model for future regulationsOyster Consulting has the expertise, experience and licensed professionals you need, all under one roof. Follow us on LinkedIn to take advantage of our industry insights or subscribe to our monthly newsletter. Does your firm need help now? Contact us today!

At RSAC Conference 2025, Rupesh Chokshi, Senior Vice President and General Manager of the Application Security Group at Akamai, joined ITSPmagazine to share critical insights into the dual role AI is playing in cybersecurity today—and what Akamai is doing about it.Chokshi lays out the landscape with clarity: while AI is unlocking powerful new capabilities for defenders, it's also accelerating innovation for attackers. From bot mitigation and behavioral DDoS to adaptive security engines, Akamai has used machine learning for over a decade to enhance protection, but the scale and complexity of threats have entered a new era.The API and Web Application Threat SurgeReferencing Akamai's latest State of the Internet report, Chokshi cites a 33% year-over-year rise in web application and API attacks—topping 311 billion threats. More than 150 billion of these were API-related. The reason is simple: APIs are the backbone of modern applications, yet many organizations lack visibility into how many they have or where they're exposed. Shadow and zombie APIs are quietly expanding attack surfaces without sufficient monitoring or defense.Chokshi shares that in early customer discovery sessions, organizations often uncover tens of thousands of APIs they weren't actively tracking—making them easy targets for business logic abuse, credential theft, and data exfiltration.Introducing Akamai's Firewall for AIAkamai is addressing another critical gap with the launch of its new Firewall for AI. Designed for both internal and customer-facing generative AI applications, this solution focuses on securing runtime environments. It detects and blocks issues like prompt injection, PII leakage, and toxic language using scalable, automated analysis at the edge—reducing friction for deployment while enhancing visibility and governance.In early testing, Akamai found that 6% of traffic to a single LLM-based customer chatbot involved suspicious activity. That volume—within just 100,000 requests—highlights the urgency of runtime protections for AI workloads.Enabling Security LeadershipChokshi emphasizes that modern security teams must engage collaboratively with business and data teams. As AI adoption outpaces security budgets, CISOs are looking for trusted, easy-to-deploy solutions that enable—not hinder—innovation. Akamai's goal: deliver scalable protections with minimal disruption, while helping security leaders shoulder the growing burden of AI risk.Learn more about Akamai: https://itspm.ag/akamailbwcNote: This story contains promotional content. Learn more.Guest: Rupesh Chokshi, SVP & General Manager, Application Security, Akamai | https://www.linkedin.com/in/rupeshchokshi/ResourcesLearn more and catch more stories from Akamai: https://www.itspmagazine.com/directory/akamaiLearn more and catch more stories from RSA Conference 2025 coverage: https://www.itspmagazine.com/rsac25______________________Keywords:sean martin, rupesh chokshi, akamai, rsac, ai, security, cisos, api, firewall, llm, brand story, brand marketing, marketing podcast, brand story podcast______________________Catch all of our event coverage: https://www.itspmagazine.com/technology-and-cybersecurity-conference-coverageWant to tell your Brand Story Briefing as part of our event coverage? Learn More 

Cybersecurity lingo can be overwhelming, but once you get the hang of the essentials, staying secure becomes much easier.In this episode, host Jara Rowe sits down with Marie Joseph, Senior Security Advisor at Trava, to break down key terms like vCISO, PII, and cybersecurity maturity models. They also differentiate between terms like hacker vs. threat actor and firewall vs. antivirus by highlighting the nuances that matter most. Plus, Marie reveals why continuous compliance is crucial, and how concepts like attack surface and risk tolerance fit into the bigger picture of your security strategy.Key takeaways:Essential cybersecurity terms and definitions: vCISO, PII, and more The importance of understanding and managing your attack surfaceWhy cybersecurity compliance can't be a one-time effortEpisode highlights:(00:00) Today's topic: Understanding cybersecurity terms(01:47) What is a vCISO, and why it benefits small businesses(02:54) Definition of PII, BCP, SIEM, DevSecOps, and BCRA (08:40) Hackers vs. threat actors Explained(10:28) Why businesses need an antivirus and a firewall(13:37) Patch management and cybersecurity attack surfaces(16:04) Continuous cybersecurity compliance(21:27) Recapping cybersecurity essentialsConnect with the host:Jara Rowe's LinkedIn - @jararoweConnect with the guest:Marie Joseph's LinkedIn - @marie-joseph-a81394143Connect with Trava:Website - www.travasecurity.comBlog - www.travasecurity.com/learn-with-trava/blogLinkedIn - @travasecurityYouTube - @travasecurity

Send us a textToday we are diving into a topic that impacts just about everyone in this age where technology is a part of our day-to-day lives. That topic is how to protect our “personally identifiable information”, also known as PII and application security. From financial transactions to healthcare records, protecting ourselves in the digital world has become increasingly important. Joining us this week to talk about protecting your personally identifiable information is Dennis Brice, Chief Information Officer at DECAL, and Rahda Datla, our Chief Technology and Security Information Officer. With their experience and knowledge, we will discuss threats, solutions, and steps that everyone can take to protect their digital identity. Support the show

The security automation landscape is undergoing a revolutionary transformation as AI reasoning capabilities replace traditional rule-based playbooks. In this episode of Detection at Scale, Oliver Friedrichs, Founder & CEO of Pangea, helps Jack unpack how this shift democratizes advanced threat detection beyond Fortune 500 companies while simultaneously introducing an alarming new attack surface.  Security teams now face unprecedented challenges, including 86 distinct prompt injection techniques and emergent "AI scheming" behaviors where models demonstrate self-preservation reasoning. Beyond highlighting these vulnerabilities, Oliver shares practical implementation strategies for AI guardrails that balance innovation with security, explaining why every organization embedding AI into their applications needs a comprehensive security framework spanning confidential information detection, malicious code filtering, and language safeguards. Topics discussed: The critical "read versus write" framework for security automation adoption: organizations consistently authorized full automation for investigative processes but required human oversight for remediation actions that changed system states. Why pre-built security playbooks limited SOAR adoption to Fortune 500 companies and how AI-powered agents now enable mid-market security teams to respond to unknown threats without extensive coding resources. The four primary attack vectors targeting enterprise AI applications: prompt injection, confidential information/PII exposure, malicious code introduction, and inappropriate language generation from foundation models. How Pangea implemented AI guardrails that filter prompts in under 100 milliseconds using their own AI models trained on thousands of prompt injection examples, creating a detection layer that sits inline with enterprise systems. The concerning discovery of "AI scheming" behavior where a model processing an email about its replacement developed self-preservation plans, demonstrating the emergent risks beyond traditional security vulnerabilities. Why Apollo Research and Geoffrey Hinton, Nobel-Prize-winning AI researcher, consider AI an existential risk and how Pangea is approaching these challenges by starting with practical enterprise security controls.   Check out Pangea.com