Podcasts about Apis

At the Fall '25 vCon conference in Washington, D.C., Doug Green, Publisher of Technology Reseller News, sat down with Dan Petrie, CEO & President of SIPez, to talk about the origins, purpose, and practical future of vCon technology. Petrie, who co-authored the original vCon draft and brought it to the IETF in 2003, describes vCon as a “standard container for capturing conversations” across voice, video, messaging, email, web chat, and more—bringing structure and consistency to interaction data that has long been fragmented across proprietary platforms. Drawing an analogy to Adobe's breakthrough with PDF, Petrie explains that just as PDF standardized how documents are represented and shared regardless of word processor or device, vCon does the same for conversational data. By abstracting common elements like parties, metadata, transcripts, and even AI-generated analytics into a unified format, vCons allow enterprises to capture, store, and analyze interactions from call centers, UCaaS platforms, and messaging systems in a consistent way. This unlocks deeper analysis—such as customer sentiment, agent performance, product feedback, and workflow optimization—without having to wrestle with dozens of incompatible APIs. Petrie stresses that vCon is especially valuable in an AI-driven world, where structured, well-labeled data is essential. “To get real value from AI, you need structured data,” he notes, pointing out that large language models like ChatGPT can only work on limited context windows and rely on upstream systems to extract, segment, and feed the right portions of conversation data. vCons provide that layer: a rich, extensible container that supports encryption, signing, redaction, amendments, and complex scenarios such as multi-leg call transfers and agent handoffs. Much of Petrie's advice is practical: don't try to build everything from scratch. SIPez maintains open-source vCon projects (such as PyvCon) and also offers a commercial vCon recording and AI analysis solution for the NetSapiens platform, giving service providers and MSPs a faster on-ramp. As more vendors add vCon interfaces and as small and mid-sized providers adopt these tools, Petrie believes 2026 will be a pivotal year for MSPs and channel partners to start monetizing vCon-based analytics and services across horizontal markets—from healthcare to customer support and beyond. To learn more about SIPez's vCon tools, open-source projects, and consulting services, visit http://sipez.com/.

(This is made with AI from our sponsor, Buzzsprout)We break down the Recap Apocalypse across Spotify, YouTube, Apple, and Amazon, then dig into craft with Brad Mielke on how Start Here reached 2,000 episodes by prioritising clarity, titles that pull, and audio-first production. Data meets discipline and the result is steady growth without burnout.• Spotify's Creator Wrapped as a real growth tool• YouTube's US-only charts and watch-time logic• Apple Replay and Amazon Delivered compared• Why hosts should build their own year-in-review• Start Here's daily format and guest booking tactics• Titles that drive plays and timely packaging• News avoidance, constructive journalism, balance• Audio-only discipline vs video tradeoffs• UK podcast charts and creator ad spend signals• iOS auto-chapters and timed links for navigation• V4V, boosts, and payment standard progress• New tools, APIs, and analytics experimentsStart podcasting, keep podcasting with BuzzSprout.comSend James & Sam a messageSupport the showConnect With Us: Email: weekly@podnews.net Fediverse: @james@bne.social and @samsethi@podcastindex.social Support us: www.buzzsprout.com/1538779/support Get Podnews: podnews.net

Jake and Michael discuss all the latest Laravel releases, tutorials, and happenings in the community.This episode is sponsored by CodeRabbit; Smart CLI Reviews act as quality gates for Codex, Claude, Gemini, and you.Show linksBlade @hasStack Directive Added in Laravel 12.39 Time Interval Helpers in Laravel 12.40 Pause a Queue for a Given Number of Seconds in Laravel 12 PHP 8.5 is released with the pipe operator, URI extension, new array functions, and more Introducing Mailviews Early Access Prevent Disposable Email Registrations with Email Utilities for Laravel A DynamoDB Driver for the Laravel Auditing Package Build Production-ready APIs in Laravel with Tyro TutorialsSeparate your Cloudflare page cache with a middleware group PostgreSQL vs. MongoDB for Laravel: Choosing the Right Database Modernizing Code with Rector - Laravel In Practice EP12 Static Analysis Secrets - Laravel In Practice EP13 

Send us a textThis quick-tip episode breaks down the blueprint for building a high-efficiency insurance eligibility system that actually works—before the chaos of January hits. Brandon reveals the annual VOB strategy top practices use to stay ahead: forming a dedicated verification task force, running preseason workflow simulations, batching by payer, gamifying team performance, using standups and dashboards, and applying smart tools like APIs and AI phone verification. He walks through how to prep your team months in advance, streamline communication, prevent burnout, and protect your revenue from missed benefits, incorrect data, and preventable errors. If your practice struggles every January with verification bottlenecks, denials, or frantic phone calls, this episode gives you a proven, repeatable model to transform your entire VOB process—and start the year with clarity, accuracy, and confidence. Welcome to Private Practice Survival Guide Podcast hosted by Brandon Seigel! Brandon Seigel, President of Wellness Works Management Partners, is an internationally known private practice consultant with over fifteen years of executive leadership experience. Seigel's book "The Private Practice Survival Guide" takes private practice entrepreneurs on a journey to unlocking key strategies for surviving―and thriving―in today's business environment. Now Brandon Seigel goes beyond the book and brings the same great tips, tricks, and anecdotes to improve your private practice in this companion podcast. Get In Touch With MePodcast Website: https://www.privatepracticesurvivalguide.com/LinkedIn: https://www.linkedin.com/in/brandonseigel/Instagram: https://www.instagram.com/brandonseigel/https://wellnessworksmedicalbilling.com/Private Practice Survival Guide Book

In this episode of The Product Experience, host Randy Silver speaks with Teresa Huang — Head of Product for Enablement at global health‑insurer Bupa — about the often‑overlooked world of platform product management. They explore why building internal platforms is fundamentally different and often more challenging than building user‑facing products, how to measure the value of platform work, and practical strategies for gaining stakeholder alignment, driving platform adoption and demonstrating business impact.Chapters0:00 – Why “efficiency” alone no longer cuts it — measuring platform impact in business terms1:02 – Teresa's background: from business analyst to head of product in health insurance6:20 – What we mean by “platform product management” — internal tools vs marketplace vs public‑API platforms7:44 – Why you need to “hop two steps”: address developer needs and end-customer value10:24 – Types of platforms: internal APIs, marketplace ecosystems, public‑facing platforms (e.g. like Shopify)10:55 – Reframing platform work: building business cases instead of chasing “efficiency” metrics13:16 – Linking platform initiatives to core business goals and joint OKRs15:47 – The importance of visualisation — using prototypes and role‑plays to communicate platform value20:57 – Internal showcases: keeping stakeholders engaged with real‑world scenarios23:28 – Success metrics for platforms: adoption, usage, reliability, ecosystem growth26:00 – Retiring legacy services: deciding when low-use tools should be decommissioned28:55 – From cost centre to enabler: shifting the narrative to show value creationOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

What does it really take to build AI that can resolve customer support at scale reliably, safely, and with measurable business impact?We explore how Intercom has evolved from a traditional customer support platform into an AI-first company, with its AI assistant, Fin, now resolving 65% of customer queries without human intervention. Intercom's Chief AI Officer, Fergal Reid, discusses the company's journey from natural language understanding (NLU) systems to their current retrieval augmented generation (RAG) approach, explaining how they've optimised every component of their AI pipeline with custom-built models.The conversation covers Intercom's unique approach to AI product development, emphasising standardisation and continuous improvement rather than customisation for individual clients. Fergal explains their outcome-based pricing model, where clients pay for successful resolutions rather than conversations, and how this aligns incentives across the business.We also discuss Intercom's approach to agentic AI, which enables their systems to perform complex, multi-step tasks, such as processing refunds, by integrating with various APIs. Fergal shares insights on testing methodologies, the balance between customisation and standardisation, and the challenges of building AI products in a rapidly evolving technological landscape.Finally, Fergal shares what excites and honestly freaks him out a bit about where AI is heading next.Timestamps00:00 - Intro02:31 - Welcome to Fergal Reid05:26 - How to train an NLU solution effectively?08:56 - What gen AI changed for Intercom10:57 - How would you describe Fin?14:30 - Fin's performance increase17:18 - Intercom's custom models22:14 - Large Language Models vs Small Language Models30:40 - RAG and 'the full stop problem'40:08 - Agentic AI capabilities at Intercom50:40 - Intercom's approach to testing1:04:46 - About the most exciting things in the AI spaceShow notesLearn more about IntercomConnect with Fergal Reid on LinkedInFollow Kane Simms on LinkedInArticle - The full stop problem: RAG's biggest limitationTake our updated AI Maturity AssessmentSubscribe to VUX WorldSubscribe to The AI Ultimatum Substack Hosted on Acast. See acast.com/privacy for more information.

In this episode of the Power Producers Podcast, David Carothers, Kyle Houck, and Clinton Houck explore how technology, customer experience, and new product offerings are reshaping opportunities in the insurance industry.  Clinton, who started his career at State Farm and later moved into the insurtech space, shares how his path led him to Fair, a company reimagining the vehicle warranty space. Historically plagued by poor customer experiences and shady telemarketing tactics, warranties are being reinvented as a trustworthy, transparent, and agency-distributed product.  Key Highlights: Disrupting Auto Warranties Clinton Houk explains how Fair eliminates dealership markups and regulation issues to offer independent agents a transparent, partner-focused warranty solution with a superior claims experience. The "Plus One" Cross-Sell Learn how to seamlessly integrate warranty discussions into everyday workflows. This strategy offers clients critical financial protection against repair bills while boosting agency revenue and retention. Closing Commercial Coverage Gaps David and Clinton highlight a major opportunity: protecting rideshare drivers and commercial fleets, which are often excluded by standard personal warranties, from cash flow shocks. Plug-and-Play Sales Tech   Clinton details Fair's agent-friendly technology, from embeddable quoting links and APIs to an in-house sales team that can handle the entire process for your agency. Connect with: David Carothers LinkedIn Clinton Houck LinkedIn Kyle Houck LinkedIn Visit Websites: Power Producer Base Camp Fair Killing Commercial Crushing Content Power Producers Podcast Policytee The Dirty 130 The Extra 2 Minutes

This special ChinaTalk cross-post features Zixuan Li of Z.ai (Zhipu AI), exploring the culture, incentives, and constraints shaping Chinese AI development. PSA for AI builders: Interested in alignment, governance, or AI safety? Learn more about the MATS Summer 2026 Fellowship and submit your name to be notified when applications open: https://matsprogram.org/s26-tcr. The discussion covers Z.ai's powerful GLM 4.6 model, their open weights strategy as a marketing tactic, and unique Chinese AI use cases like "role-play." Gain insights into the rapid pace of innovation, the talent market, and how Chinese companies view their position relative to global AI leaders. Sponsors: Google AI Studio: Google AI Studio features a revamped coding experience to turn your ideas into reality faster than ever. Describe your app and Gemini will automatically wire up the right models and APIs for you at https://ai.studio/build Agents of Scale: Agents of Scale is a podcast from Zapier CEO Wade Foster, featuring conversations with C-suite leaders who are leading AI transformation. Subscribe to the show wherever you get your podcasts Framer: Framer is the all-in-one platform that unifies design, content management, and publishing on a single canvas, now enhanced with powerful AI features. Start creating for free and get a free month of Framer Pro with code COGNITIVE at https://framer.com/design Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive PRODUCED BY: https://aipodcast.ing CHAPTERS: (00:00) Sponsor: Google AI Studio (00:31) About the Episode (03:44) Introducing Z.AI (07:07) Drupu AI's Backstory (09:38) Achieving Global Recognition (Part 1) (12:53) Sponsors: Agents of Scale | Framer (15:15) Achieving Global Recognition (Part 2) (15:15) Z.AI's Internal Culture (19:17) China's AI Talent Market (24:39) Open vs. Closed Source (Part 1) (24:46) Sponsors: Tasklet | Shopify (27:54) Open vs. Closed Source (Part 2) (35:16) Enterprise Sales in China (40:38) AI for Role-Playing (45:56) Optimism vs. Fear of AI (51:36) Translating Internet Culture (57:11) Navigating Compute Constraints (01:03:59) Future Model Directions (01:15:02) Release Velocity & Work Culture (01:25:04) Outro

Send us a textStop guessing your way through sales. We sit down with Carolyn Miller—builder's daughter, top-performing dealer, sales trainer, and CRM implementer—to map a simple path from chaotic follow-up to a clean, scalable system that grows shed and post‑frame sales. Carolyn's Ask, Listen, Solve framework anchors the conversation: ask smarter questions that surface real needs, listen for budget, timing, and site constraints, then solve with a clear next step that moves the deal forward. From there, we translate that human process into technology your team will actually use.You'll hear concrete examples of how a right-sized CRM becomes more than a contact list. We talk automations that text prospects within minutes of a configurator submission, task sequences that keep quotes alive, and post‑delivery check-ins that trigger five‑star Google reviews and referrals. Carolyn shares a client win where automation alone revived a lead the salesperson had written off, turning it into an $800 profit carport sale. We also open the hood on integrations—connecting IdeaRoom or Digital Shed Builder to capture high-intent leads, syncing orders to QuickBooks Online to eliminate double entry, and pushing projects to monday.com so production and delivery stay in lockstep with sales.If your tech stack already feels crowded, this chat will help you make it act like one system. We cover when to use APIs, webhooks, and Zapier, and why a simple front end matters more than a flashy dashboard. Most importantly, we focus on adoption: weekly coaching, tight feedback loops, and small refinements so your team starts the day in the CRM and never loses the thread with a customer again. Ready to replace “winging it” with a repeatable process that frees your time and lifts your close rate? Hit play, then tell us your biggest follow-up bottleneck—we'll tackle it in a future installment. If you find value here, subscribe, leave a review, and share this with a dealer who needs a cleaner system.For more information or to know more about the Shed Geek Podcast visit us at our website.Would you like to receive our weekly newsletter?  Sign up here.Follow us on Twitter, Instagram, Facebook, or YouTube at the handle @shedgeekpodcast.To be a guest on the Shed Geek Podcast visit our website and fill out the "Contact Us" form.To suggest show topics or ask questions you want answered email us at info@shedgeek.com.This episodes Sponsors:Studio Sponsor: Shed ProIdentigrowCALCardinal LeasingDigital Shed Builder

In this episode of The Product Experience, host Randy Silver speaks with Teresa Huang — Head of Product for Enablement at global health‑insurer Bupa — about the often‑overlooked world of platform product management. They explore why building internal platforms is fundamentally different and often more challenging than building user‑facing products, how to measure the value of platform work, and practical strategies for gaining stakeholder alignment, driving platform adoption and demonstrating business impact. Chapters0:00 – Why “efficiency” alone no longer cuts it — measuring platform impact in business terms1:02 – Teresa's background: from business analyst to head of product in health insurance6:20 – What we mean by “platform product management” — internal tools vs marketplace vs public‑API platforms7:44 – Why you need to “hop two steps”: address developer needs and end-customer value10:24 – Types of platforms: internal APIs, marketplace ecosystems, public‑facing platforms (e.g. like Shopify)10:55 – Reframing platform work: building business cases instead of chasing “efficiency” metrics13:16 – Linking platform initiatives to core business goals and joint OKRs15:47 – The importance of visualisation — using prototypes and role‑plays to communicate platform value20:57 – Internal showcases: keeping stakeholders engaged with real‑world scenarios23:28 – Success metrics for platforms: adoption, usage, reliability, ecosystem growth26:00 – Retiring legacy services: deciding when low-use tools should be decommissioned28:55 – From cost centre to enabler: shifting the narrative to show value creationOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Ben Toner once again joins Keith Parsons to explain the new WLAN-Pi App. Originally built to control the WLAN-Pi Go, the app now works with all WLAN-Pi models and consolidates controls previously spread across the web UI and APIs. They then dive deeper into the method of connectivity for the app and the functionalities it... Read more »

Most software teams still think of payments as a chore. We take you inside the playbook that turns it into a growth engine. I sits down with NMI CTO Phillip Goericke to unpack how embedded payments evolved from a basic checkout to a full-stack platform that handles onboarding, underwriting, payouts, analytics, and even embedded finance. The conversation is straight talk on what actually works when you're shipping fast and scaling globally.We dig into the architectural choices that matter: start with a no-code drop-in to activate revenue quickly, then progress to low-code SDKs and finally full APIs when you need deep control. Phillip shares where platforms stall - manual KYC, fragmented global rules, and data blind spots and how a modular approach fixes these without ripping out your stack. You'll hear how compliance-as-a-service, network tokenization, and adaptive 3D Secure can raise approval rates, reduce fraud, and simplify audits while keeping the checkout experience seamless.Looking ahead, we explore why identity, compliance, and data are the foundation for embedded finance. Philip outlines NMI's unified experience that brings payments, onboarding, insights, and new services like business capital into one place. We also tackle AI with clear eyes: use it to augment decisioning and anomaly detection, but wrap it with deterministic controls so money-critical outcomes are consistently right. The key takeaway is a mindset shift: stop treating payments as a feature and start using it as a strategic lever for revenue, retention, and product velocity.If you're building software with transactions anywhere in the flow, this is your blueprint for turning payments into a competitive moat. Subscribe for more deep dives, share with a teammate who owns monetization, and leave a review to tell us what topic you want next.

In this special 2026 Payments Outlook episode of the Payments Podcast, host Owen McDonald is joined by Jessica Cheney and Vitus Rotzer to explore the trends shaping the future of banking and B2B payments. From monetizing ISO 20022 data and accelerating real-time and cross-border payments to scaling embedded payments and leveraging AI for fraud prevention, this conversation dives deep into the strategies banks must adopt to stay competitive. Discover why collaboration, APIs, and advanced analytics will define success in the coming year.

Can agentic AI solve the scalability challenge in wealth management while expanding access to underserved communities? Ramona Ortega believes it can, but only with the right foundation. She explains how WealthBuild has moved from basic chatbots to RAG and now to agentic workflows that can deliver accurate and personalized guidance at scale. In her opinion, the real blockers aren't algorithms but messy data, governance gaps and enterprise-grade security. Since traditional financial services can't reach many everyday consumers, she partners with community banks to close the gap. For her, the future lies where AI, APIs and blockchain meet, opening the door to accessible and democratized financial advice.Explore the podcast → https://ibm.biz/BdbuaR

In this special Cloud Wars report, Bob Evans sits down with Michael Ameling, President and Chief Product Officer of SAP Business Technology Platform, for a deep dive into how SAP is helping customers navigate the fast-moving AI Era. Ameling and Evans discuss how SAP's Business Data Cloud, partnerships with Snowflake and Databricks, HANA Cloud innovations, and new AI-powered tools and agents are helping SAP evolve from an applications powerhouse into a data-and-AI-driven business platform for the next generation.SAP's AI Data FutureThe Big Themes:SAP HANA Cloud Becomes an AI-Optimized Database: SAP HANA Cloud is evolving into “the database AI was looking for." As a multi-model system supporting spatial, graph, vector, and document storage, HANA Cloud enables AI workloads to run more efficiently and contextually. Recent additions, like vector engines and Knowledge Graph capabilities, give customers powerful tools for retrieval-augmented generation (RAG), contextual reasoning, and advanced analytics.Developers Are 'The AI Revolution': Developers aren't observing the AI Revolution, they are the revolution. With modern AI tools, developers can innovate faster, solve bigger problems, and directly influence business outcomes. SAP is investing heavily in meeting developers where they are by enhancing IDEs, building business-aware development tools, and providing context-rich assets such as APIs, business objects, and process insights. AI acts as a teammate, not a replacement.SAP: An Applications and a Data Company: SAP must be both an applications and a data company. Customer value emerges when applications, data, and AI converge seamlessly. SAP's decades of industry expertise give it unparalleled business context, which becomes even more powerful when embedded into AI agents and data platforms. With more than 34,000 SAP HANA Cloud customers and rapidly expanding AI adoption, SAP is positioning itself as the platform where business process knowledge meets modern AI capability.The Big Quote: " . . what we need to understand that AI is our teammate. It's like asking your best friend who has a lot of knowledge, but you can ask multiple friends at the same time. Not everything is always right, but you can ask questions, you can continuously improve. If we understand that pattern, we understand that AI helps us to solve much bigger problems as a developer, and then, of course, having much more impact on real business."More from Michael Ameling and SAP:Connect with Michael Ameling on LinkedIn, or get more insights from SAP TechEd.  Visit Cloud Wars for more.

In this episode of Technology Reseller News' special series on Telco Days 2025, Doug Green speaks with Damian Mazurek, Chief Innovation Officer at Software Mind, about why the telecom industry is at a historic crossroads – and what it will take for telcos to move from commodity connectivity to AI-era value creators. Mazurek explains how rapid advances in AI, edge computing, LEO satellites and IoT are converging with generational change, especially Gen Z's preference for asynchronous, AI-enabled interactions. Traditional voice and human-to-human communication are giving way to data-driven, bot-mediated experiences. “The next generation will not even talk with us – their AI assistants will do it for them,” he notes, predicting a future where AI agents negotiate, schedule, buy, sell and resolve issues on behalf of human users. To avoid being trapped as low-margin bandwidth providers, Mazurek argues that telcos must evolve from telco to techco, building both an innovation culture and the cloud-native platforms needed to iterate at high speed. He outlines a three-layer framework for AI in the RAN – AI for the run, AI in the run and AI on the run – where AI improves network operations, monetizes unused capacity for AI workloads, and enables new services built on top of programmable, API-driven networks. Mazurek sees major opportunities in: Turning surplus network capacity and distributed edge infrastructure into an “AI grid” that hosts and accelerates AI workloads. Leveraging telco data and real-time APIs to power new services and revenue streams. Enabling sectors like agriculture, aquaculture and industrial automation with reliable connectivity, low latency and AI-ready infrastructure in previously hard-to-reach locations. Delivering proactive, AI-driven customer experiences that match Gen Z expectations for simplicity, personalization and immediacy. Ultimately, Mazurek believes telcos that embrace cloud-native transformation, programmable networks and AI-driven operations can do far more than survive the coming decade. “They can dominate the market and create new business value,” he says, by building the secure, trusted infrastructure that will underpin AI-to-AI communication at global scale. To learn more about Software Mind's telecom innovation initiatives and access resources from Telco Days, visit https://softwaremind.com/.

Join Balaji Raghavan, Head of Engineering at Postman, as he discusses the critical gap between AI adoption and API readiness, revealing that while 80% of developers use AI, only 24% design APIs with AI agents as the intended consumer. Drawing from Postman's 40 million developer user base, Raghavan explains how human-designed APIs create ambiguity problems for AI systems, requiring additional tooling layers that often introduce security vulnerabilities through proxy credentials and unauthorized access risks. He addresses the uncomfortable reality that the industry is still in early stages of making AI reliably call APIs at scale, with hallucinations and context limitations preventing effective orchestration across hundreds of endpoints, while warning that judicious leaders must distinguish between deterministic flows and cases where expensive AI-based approaches are truly necessary to manage infrastructure costs and prevent cascade failures.

AI systems change constantly. Models get deprecated, APIs shift, and what works today might fail tomorrow. Instead of trying to keep up with everything, I've built my systems for permanent adaptability. That means migration patterns that let me run old and new prompts side by side, using OpenAI's hidden Flex tier to cut costs by 50%, front-loading repeated data in prompts to maximize cache savings, and implementing circuit breakers so runaway AI costs can't blow up my bill. These aren't optimizations — they're how you run AI in production without losing your mind or your money.I'm running a time-limited Black Friday sale of The Bootstrapper's Bundle: all my books, all my courses, all formats, for $25 instead of $100+. Grab it here: https://tbf.link/bffThis episode of The Bootstraped Founder is sponsored by Paddle.comYou'll find the Black Friday Guide here: https://www.paddle.com/learn/grow-beyond-black-fridayThe blog post: https://thebootstrappedfounder.com/ai-best-practices-for-bootstrappers-that-actually-save-you-money/ The podcast episode: https://tbf.fm/episodes/425-ai-best-practices-for-bootstrappers-that-actually-save-you-money Check out Podscan, the Podcast database that transcribes every podcast episode out there minutes after it gets released: https://podscan.fmSend me a voicemail on Podline: https://podline.fm/arvidYou'll find my weekly article on my blog: https://thebootstrappedfounder.comPodcast: https://thebootstrappedfounder.com/podcastNewsletter: https://thebootstrappedfounder.com/newsletterMy book Zero to Sold: https://zerotosold.com/My book The Embedded Entrepreneur: https://embeddedentrepreneur.com/My course Find Your Following: https://findyourfollowing.comHere are a few tools I use. Using my affiliate links will support my work at no additional cost to you.- Notion (which I use to organize, write, coordinate, and archive my podcast + newsletter): https://affiliate.notion.so/465mv1536drx- Riverside.fm (that's what I recorded this episode with): https://riverside.fm/?via=arvid- TweetHunter (for speedy scheduling and writing Tweets): http://tweethunter.io/?via=arvid- HypeFury (for massive Twitter analytics and scheduling): https://hypefury.com/?via=arvid60- AudioPen (for taking voice notes and getting amazing summaries): https://audiopen.ai/?aff=PXErZ- Descript (for word-based video editing, subtitles, and clips): https://www.descript.com/?lmref=3cf39Q- ConvertKit (for email lists, newsletters, even finding sponsors): https://convertkit.com?lmref=bN9CZw

A dealership website script shouldn't be the key to your car. Yet that's exactly what one security researcher demonstrated on a DEF CON stage, turning a forgotten corner of a portal into national-level access that could unlock vehicles, view customer data, and send remote commands. We dig into what that means for drivers, dealers, and automakers now that the family SUV doubles as a rolling endpoint connected to clouds, APIs, and third-party tools.We walk through the chain of weak links—subdomains, misconfigured permissions, app integrations—and explain why dealer networks can become the soft underbelly of an automaker's security. Then we turn to the flipside of software-defined cars: when an over-the-air update breaks a feature people rely on. A new Tahoe's built-in garage door opener stopped working post-update, and the finger-pointing that followed shows how support and testing must evolve. Convenience only works when reliability does too.Safety headlines round out the reality check. From a Kia K5 fuel-system fault that can over-pressurize tanks, to airbag inflator issues and wiring harness problems affecting pickups and SUVs, we outline the most pressing recalls and what owners should do next. Along the way, we keep the enthusiast spark alive with a Sold Cars Roundup—proof you can still get into the hobby with a '73 Charger under twenty grand or a clean Barracuda around thirty—plus highlights from a standout student technician competition that signals where the industry is headed.If you care about connected cars, cybersecurity, recalls, and the classic market, this conversation maps the risks and the opportunities with clear takeaways you can act on today. Subscribe for more smart car talk, share this episode with a friend who loves their tech as much as their torque, and leave a review to tell us what you want us to investigate next.Be sure to subscribe for more In Wheel Time Car Talk!The Lupe' Tortilla RestaurantsLupe Tortilla in Katy, Texas Gulf Coast Auto ShieldPaint protection, tint, and more!Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.---- ----- Want more In Wheel Time car talk any time? In Wheel Time is now available on Audacy! Just go to Audacy.com/InWheelTime where ever you are.----- -----Be sure to subscribe on your favorite podcast provider for the next episode of In Wheel Time Podcast and check out our live multiplatform broadcast every Saturday, 10a - 12nCT simulcasting on Audacy, YouTube, Facebook, Twitter, Twitch and InWheelTime.com.In Wheel Time Podcast can be heard on you mobile device from providers such as:Apple Podcasts, Amazon Music Podcast, Spotify, SiriusXM Podcast, iHeartRadio podcast, TuneIn + Alexa, Podcast Addict, Castro, Castbox, YouTube Podcast and more on your mobile device.Follow InWheelTime.com for the latest updates!Twitter: https://twitter.com/InWheelTimeInstagram: https://www.instagram.com/inwheeltime/https://www.youtube.com/inwheeltimehttps://www.Facebook.com/InWheelTimeFor more information about In Wheel Time Podcast, email us at info@inwheeltime.com

Susanne Heipcke is Director of Software Engineering at FICO, where she has led the Modelling Team of FICO Xpress development for more than 12 years. Her team is responsible for the development and design of the modelling tools (Xpress Mosel) and the APIs of the Xpress Optimization software suite, with past tasks including the design of application development toolkits, solution templates, and productized optimization solutions such as FICO Decision Optimizer. More recently, her team's responsibilities have expanded to include CI/CD, performance testing, and delivery infrastructure for the entire Xpress suite. Before joining Dash Optimization (acquired by FICO in 2008) in 1998, she worked for BASF-AG in Germany. Her Ph.D. research at the University of Buckingham—conducted partly at the MIT OR Center (USA) and the University Aix-Marseille II (France)—focused on solving large-scale industrial problems using a combination of constraint programming and mixed integer programming. Her work centers on all aspects of modelling, particularly through her contributions to the development of the algebraic modelling and programming language Xpress Mosel. She is the author of the book Applications of Optimization with Xpress-MP and numerous papers on different aspects of mathematical modelling. Susanne enjoys teaching mathematical optimization, having participated in teaching the mathematical modelling course in the OR master's program at the University Aix-Marseille II (2001–2004) and the Computational Mixed-Integer Programming course at the Technical University of Munich in 2020. She regularly organizes specialist training events and conference sessions, such as the “Software for Optimization Modeling and Deployment” sessions at recent INFORMS Annual Meetings (jointly with Bob Fourer), and she is actively engaged in mentoring younger colleagues. Since 2019 she has been a member of the EURO Practitioners' Forum committee (formerly the EURO Working Group Practice of OR), leading the organization of the Forum's annual meetings in 2020, 2023, and 2026. With more than 30 years of experience in applied OR, she has also contributed to numerous consulting projects worldwide, involving scheduling and planning in manufacturing, personnel staffing, aircraft routing with maintenance planning, portfolio optimization, trading, energy production planning and unit commitment, and retail logistics.Contents of this video:0:00 - Intro1:27 - Family background and early years4:15 - Attending a girls' high school4:58 - Polyglot9:11 - Learning to program during high school11:13 - Moving to Bavaria to study mathematics13:19 - Practical data processing projects14:52 - Learning about OR16:31 - Master's thesis on constraint programming (CP) applied to a problem arising at BASF20:31 - Getting inspiration from a female leader at BASF22:14 - Spending half a year at the MIT OR Center + moving to the University of Buckingham for a PhD25:02 - Adapting to the UK26:06 - Combining MIP and CP to solve production planning and scheduling problems29:19 - Joining Dash Optimization in 199830:32 - Moving to France in 199931:20 - Working form home in an era before Zoom, Git, and similar tools existed32:28 - Maternity and work33:55 - The modelling language Xpress Mosel36:38 - Launching Mosel in 200139:45 - Evolution of Mosel over the years45:16 - Mosel's long-standing team47:35 - High compatibility across different versions of Mosel 48:16 - Xpress Mosel is a free software since 201849:21 - Favorite contributions to Mosel53:21 - Software engineering and optimization58:20 - AI and optimization software1:01:12 - Organizing conferences, workshops and special sessions regarding optimization software1:03:25 - EURO Practitioners' Forum1:04:52 - Regrets?1:05:18 - Plans for the future1:06:15 - Inspiring takeaway message1:07:22 - Concluding remarks

Heute mal Studio-Flair auf Reisen: Wir sitzen auf dem Auto Motor und Sport Kongress – und haben uns einen Gast geschnappt, bei dem es beim letzten Mal schon ordentlich geknistert hat. Maria Anhalt, CEO von Elektrobit, ist zurück im Moove-Podcast und bringt eine volle Ladung Zukunftsthemen mit. Was hat sich seit ihrem letzten Besuch verändert? Warum klopfen plötzlich Sony, Foxconn und andere Tech-Riesen bei Automotive-Software-Spezialisten an? Und was verstehen wir eigentlich wirklich unter „Software im Auto“? Maria räumt auf mit Missverständnissen und erklärt Elektrobits SDV-Level-Modell: von „Software Enabled“ bis zur Innovationsplattform. Spoiler: Viele Hersteller hängen irgendwo zwischen Update-fähig und Upgrade-tauglich fest – und genau da wird's teuer. Wir reden über den nötigen Plattform-Sprung, Hardware/Software-Entkopplung, API-Economy und die Frage nach einem gemeinsamen Automotive-Betriebssystem. Danach wird's Open-Source-konkret: Eclipse S-CORE, Linux, Android Automotive – Chancen, Chaos und warum Standardisierung trotzdem alternativlos ist. Zum Schluss geht der Blick nach China und in die KI-Kristallkugel: SDV-Prognosen bis 2030, Innovations-Speed und wie GenAI- und Agenten-Workflows die Softwareentwicklung im Auto neu takten können – bis hin zu offenen KI-Interfaces im Cockpit. Viel Spaß beim Hören (oder Sehen) – und schreibt uns eure Fragen wie immer!

Live from Bangkok - 4 Mind-Blowing AI Use Cases from Our First MeetupWe're coming to you live from Bangkok after hosting our very first Create With AI meetup in Thailand - and it was absolutely incredible! The event sold out weeks in advance, and we got to see four amazing speakers showcase real-world AI applications they've built without traditional coding.In this episode, James joins from Bangkok while Kieran dials in from Norwich to break down everything that happened at the event and discuss the latest developments in AI and no-code tools.The 4 Bangkok Use Cases:1. Instagram AI Agent for E-commerce (Jake)An automated system built in Make that responds to Instagram comments with full product knowledge - inventory, pricing, store locations, all in brand voice. Game-changing for e-commerce customer service.2. Vacation Booking Platform (Stuart)A complete vacation booking system built with Claude Code that integrates with Airbnb's APIs. Stuart showed us how he's tapping into external platforms to create a full-featured booking dashboard.3. Medical Lab Dashboard (Natt)This one blew our minds. Natt came from a biochemistry background and replaced 170 separate Google Forms with one unified dashboard using Xano + Claude Code. She showed us why separating your backend (Xano) from frontend (AI-generated) might be the secret sauce for non-coders building production apps.4. Thailand's No-Code Movement (Opal)Opal runs a 10,000+ member Facebook group dedicated to no-code in Thailand, proving just how advanced and thriving the builder community is over there.What Else We Cover:The Xano + Claude Code strategy: Why building your data structure visually and letting AI handle the UI might be the winning approach for non-technical buildersAI Model Updates: Breaking down Gemini 3's Imagen breakthrough, Claude Opus 4.5's cost reduction, and why ChatGPT keeps confidently lying about datesDesign's Future: Insights from a 20-person design agency founder on whether AI will replace designers (spoiler: only the bad ones)Vibe Coding Reality Check: What experienced developers actually think about AI coding tools and where they still fall shortGoogle's Project IDX: First impressions of the new "Anti-Gravity" code editor from the ex-Windsurf teamCodex vs Claude Code vs Cursor: What we're actually using day-to-day and whyCommunity Spotlight: TechFoundHer's new "We Build" program aiming to get 150 women into building tech venturesUpcoming:Norwich meetup in DecemberMore UK events in the NorthFuture Asia meetups in planningBig announcement coming next week!Want to host your own Create With meetup? Check out our Ambassador Program at https://createwithhq.notion.site/2ab7b439d1fc8080bdcfe7dd1ea2ab69?pvs=105Follow the hosts:James Devonport: @jamesdevonport on XKieran Ball: @kieranball on XLearn more and find events near you:

#326: Microservices architecture has evolved far beyond simple distributed systems, but most development teams are still rebuilding the same foundational patterns over and over again. Mark Fussell, co-founder of Dapr and Diagrid, explains how his team at Microsoft identified this repetitive reinvention problem and created a solution that abstracts away the complexity of service discovery, messaging, state management, and security while providing true cloud portability. Dapr emerged from Microsoft's Azure incubations team with a clear mission: stop forcing developers to rebuild distributed systems patterns from scratch. The runtime provides standardized APIs for common microservices needs while allowing teams to swap underlying infrastructure components without changing application code. Whether using Kafka, RabbitMQ, Redis, or cloud-native messaging services, developers write against consistent APIs while platform teams maintain control over infrastructure choices. The conversation covers Dapr's journey from Microsoft internal project to CNCF graduated status, the technical decisions behind its multi-language approach, and how it integrates with existing frameworks like Spring Boot and .NET. Mark also discusses Diagrid's platform play around durable workflows and the emerging role of Dapr in AI agent development. Darin and Viktor explore the practical adoption challenges, the balance between developer productivity and platform engineering concerns, and why experienced developers tend to embrace abstraction layers more readily than those building their first distributed systems.   Mark's contact information: X: https://x.com/mfussell LinkedIn: https://www.linkedin.com/in/mfussell/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

This episode is a special crossover between the Practical AI podcast and The Changelog podcast. Chris was recently invited by longtime friends Jerod Santo and Adam Stacoviak, cohosts of The Changelog, to join them on the show. They discuss AI, drones, robotics, swarming technology, and the rise of high-performance edge computing with Rust.  Chris points out that open source software, small AI models, and affordable hardware are making home automation and local AI accessible to everyone. From automating household functions to experimenting with drones and single-board computers, Chris describes how hands-on maker projects are shaping a bright future for physical AI, on small budgets and right from the comfort of your own home.Featuring: Jerod Santo – LinkedInAdam Stacoviak – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XSponsors: Miro – Get the right things done faster with Miro's Innovation Workspace. AI Sidekicks, instant insights, and rapid prototyping—transform weeks of work into days. No more scattered docs or endless meetings. Help your teams get great done at Miro.com.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiUpcoming Events: Register for upcoming webinars here!This week we have extended show notes below from Chris!Swarming & Fully Autonomous Multi-Agent UxV SystemsChris's Definition of Swarming (anchor link in show notes)Chris's definition of Swarming“Swarming occurs when numerous independent fully-autonomous multi-agentic platforms exhibit highly-coordinated locomotive and emergent behaviors with agency and self-governance in any domain (air, ground, sea, undersea, space), functioning as a single independent logical distributed decentralized decisioning entity for purposes of C3 (command, control, communications) with human operators on-the-loop, to implement actions that achieve strategic, tactical, or operational effects in the furtherance of a mission.”© 2025 Chris BensonConceptual FoundationsSwarm Robotics – WikipediaHigh-level overview of swarm robotics as decentralized robot collectives.https://en.wikipedia.org/wiki/Swarm_roboticsSwarm Robotic Platforms – WikipediaSurvey of hardware platforms used in swarm robotics research.https://en.wikipedia.org/wiki/Swarm_robotic_platformsSwarm Intelligence – WikipediaBroader algorithms and theory behind collective intelligence (beyond robots).https://en.wikipedia.org/wiki/Swarm_intelligenceAnt Robotics – WikipediaNature-inspired “ant-like” robotics as a special case of swarm robotics.https://en.wikipedia.org/wiki/Ant_roboticsOpen Research & Multi-Robot Resources (Stepping-Stones Toward True Swarms)Programming Multiple Robots with ROS 2 (online book)Free book on multi-robot systems, ROS 2, and the Robot Middleware Framework (RMF).https://osrf.github.io/ros2multirobotbookSimulation with ROS 2 & Gazebo (ROS 2 Humble tutorial)Official tutorial on connecting ROS 2 to Gazebo simulation.https://docs.ros.org/en/humble/Tutorials/Advanced/Simulators/Gazebo/Gazebo.htmlSpawning Multiple Robots in Gazebo with ROS 2Hands-on tutorial to launch N robots in Gazebo, each with its own namespace.https://www.theconstruct.ai/spawning-multiple-robots-in-gazebo-with-ros2ROS 2 Multi-Robot Simulation Best Practices (Discourse thread)Discussion of patterns for multi-robot systems (domains, namespaces, Nav2, etc.).https://discourse.openrobotics.org/t/multi-robot-simulation-best-practices/38987Getting Hands-On: Consumer Robotics, ROS 2 & GazeboROS 2 (Robot Operating System 2)Official ROS 2 Documentation – Humble (LTS)Main docs for ROS 2 Humble (recommended distro) with tutorials and APIs.https://docs.ros.org/en/humbleROS 2 Installation Guide (Humble)Step-by-step install on supported platforms.https://docs.ros.org/en/humble/Installation.html“From Zero to Robotics Hero: A Beginner's Guide to ROS 2” (article)Beginner-friendly overview with ideas for where to go next (MoveIt, Nav2, multi-robot, etc.).https://riyagoja.medium.com/from-zero-to-robotics-hero-a-beginners-guide-to-ros-2-90ac9c3b87baROS 2 Tutorial for Beginners (2025 guide)Up-to-date intro that walks you from install to simulating your first robot in 2025.https://www.timesofexplore.com/2025/10/ros2-tutorial-beginners-build-first-robot-2025.htmlGazebo SimulationGazebo Sim – Official SiteModern Gazebo (Ignition) simulator; models, worlds, and docs.https://gazebosim.orgGetting Started with Gazebo (Docs)Official “start here” guide for using Gazebo and Gazebo Fuel assets.https://gazebosim.org/docs/latest/getstartedClassic Gazebo Tutorials (still useful for fundamentals)https://classic.gazebosim.org/tutorialsmicro-ROS (ROS 2 on Microcontrollers)micro-ROS – ROS 2 for MicrocontrollersOfficial site for running ROS 2 on tiny embedded boards.https://micro.ros.orgmicro-ROS GitHub OrganizationRepositories, examples, and tutor...

This roundtable explores how B2B teams can use modern demand strategies, B2C channels, and incrementality testing to prove true ad impact in 2026. The conversation highlights omni-channel expansion beyond LinkedIn, data-driven measurement, and practical ways to validate lift across pipeline and revenue.Speakers and RolesMatt Sciannella – Host and practitioner running paid media for multiple B2B clients; shares real client use cases, lift results, and practical frameworks for measurement and experimentation.Keith Putnam-Delaney – CEO of Primer; former Dropbox growth leader; expert in B2B expansion into B2C channels, audience targeting, mobile–desktop measurement problems, match rates, and lift testing.Authority: Both speakers bring hands-on experience running B2B paid programs at scale and deep insight into attribution limits, ABM constraints, and cross-channel growth strategies.Topics CoveredRising costs and saturation in traditional B2B channels (LinkedIn, Google).Why B2B brands must expand into B2C channels like Meta, YouTube, Reddit, TikTok.Mobile vs. desktop measurement gaps and cross-device limitations.Signal loss, attribution decay, and the need for server-side events.How to validate true impact using lift tests and incrementality.CPM efficiency comparisons across channels.ABM unbundling and alternatives to large, monolithic ABM platforms.Using holdout groups, geographic lift, and omnichannel testing strategies.Real client examples showing lift in inbound, share of search, and revenue.How audience targeting tools unlock TAM expansion outside LinkedIn.Questions This Video Helps AnswerHow do B2B marketers prove real ad impact without relying on last-touch attribution?How can brands expand beyond LinkedIn and still target ICP buyers effectively?What causes demand generation inefficiency and how do you fix it?How do mobile–desktop and cross-device gaps distort performance data?What is the right way to design lift tests or incrementality experiments?How can small TAM companies still scale using B2C channels?What alternative ABM workflows exist beyond large enterprise platforms?How should B2B teams interpret rising CPMs and shrinking reach?Jobs, Roles, and Responsibilities MentionedB2B growth marketingGrowth teamsSales operations managersRevenue operations rolesVPs of MarketingRegional sales directorsMedical device surgeons (ICP example)Marketing, sales, financeInfosec teamsPLG teamsField marketingOutbound sales teamsKey TakeawaysAttribution alone cannot prove channel value; lift tests reveal true incrementality.B2B audiences exist far beyond LinkedIn, and CPM efficiency is often dramatically higher on Meta, Reddit, and YouTube.Mobile-heavy consumption breaks MTA models; server-side signals and conversion APIs are now essential.ABM can be unbundled using smaller, more flexible tools and alternative data sources.Expanding TAM and using audience targeting unlocks more reach and stronger pipeline outcomes.Share of search is a powerful leading indicator for demand creation impact.Omnichannel experimentation paired with structured test design improves confidence with finance and executive teams.Frameworks and Concepts MentionedIncrementality testingHoldout groupsChannel-based lift testsGeographic lift testsAccount list split testingLeading vs. lagging indicatorsShare of search analysisServer-side conversion APIs (CAPI)Cross-device measurementAudience match ratesABM unbundlingCPM efficiency analysis

Colin Fowler and guest host, Ben Brokesh, visit TechCrunch Disrupt 2025. Listen in as they meet with some of the foremost startup entrepreneurs.  Timestamps:3:24 – HyWatts (Sam Ruben, CBDO and Co-Founder): Delivers clean, modular energy systems that turn renewable power into reliable electricity. 14:23 – Tesollo (Youngjin Kim, President and CEO; Wooseok Ryu, CTO): Solves complex problems and creates new value for their customers through advanced robotic automation solutions utilizing robotic grippers. 19:46 – Carbon Native Solutions (Keith Crossland, CEO): Invented a new class of multi-objective AI that transforms local industrial waste and minerals into high-performance, carbon-negative cement materials using standard equipment. 29:23 – Steg.AI (Eric Wengrowski, CEO): Trains in-house deep learning models for watermarking and poisoning for use through APIs, web applications, and third-party integrations. 41:27 – Ascender Systems (Jorge Muniz, Co-Founder and CEO): Patented a climbing robot that can scale utility/light/flag poles, pipes, and columns of varying shapes from 3 inches to 22 inches. 49:49 – Ponderosa.ai (Scott Benson, Founding Software Engineer): Develops cost-effective AI-enabled fire suppression drone swarms that can be broadly distributed and prepositioned in areas of high risk.

Chris cooked up a wild remote-access trick for Jellyfin that skips VPNs entirely. One tiny toggle spins up a secure tunnel on demand. Simple, absurd, and shockingly effective.Sponsored By:Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. 1Password Extended Access Management: 1Password Extended Access Management is a device trust solution for companies with Okta, and they ensure that if a device isn't trusted and secure, it can't log into your cloud apps. CrowdHealth: Discover a Better Way to Pay for Healthcare with Crowdfunded Memberships. Join CrowdHealth to get started today for $99 for your first three months using UNPLUGGED.Unraid: A powerful, easy operating system for servers and storage. Maximize your hardware with unmatched flexibility. Support LINUX UnpluggedLinks:

Dive into the dynamic world of SwiftUI, SwiftData, and Apple Intelligence in this episode, where we explore how these technologies are transforming development. Join us as we discuss Frank Kruger's innovative work on the Clean Room application, which showcases the elegance of macOS UI design. Discover how AI-driven tools like Apple Intelligence can enhance your Mac's capabilities, offering powerful APIs and translation features that simplify complex tasks. We also delve into the benefits and challenges of using VS Code for Swift development, sharing insights on optimizing Swift projects and leveraging AI for content creation. Perfect for developers and tech enthusiasts, this episode provides actionable takeaways and thought-provoking discussions that will inspire your next project. Tune in to uncover the future of development and productivity! Follow Us Frank: Twitter, Blog, GitHub James: Twitter, Blog, GitHub Merge Conflict: Twitter, Facebook, Website, Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us (https://itunes.apple.com/us/podcast/merge-conflict/id1133064277?mt=2&ls=1) ⭐⭐ Machine transcription available on http://mergeconflict.fm

Justin Tolman from Exterro joins the Forensic Focus Podcast to talk about the future of FTK and the role FTK Imager still plays in everyday casework. He explains why the original free version remains available, and what prompted the introduction of Imager Pro with added capabilities like BitLocker decryption and iOS collections. Justin also reflects on his time in law enforcement and training, and why the investigative side of the work still holds a strong pull. Looking ahead, Justin shares where FTK development is headed — from large-scale processing and streamlined review workflows to Whisper-based audio transcription and careful, targeted use of AI for tasks like summarising long documents and cross-media searching. He also previews Exterro's upcoming Inform event — a 15-hour global broadcast featuring talks from practitioners around the world — and invites the community to get involved. #DigitalForensics #DFIR #FTK #Exterro #ForensicImaging #MobileForensics #IncidentResponse  00:00 Welcome to the Forensic Focus Podcast 00:31 Introducing Justin Tolman from Exterro 01:46 Justin's Journey into Forensics 03:10 Transition to Training and Exterro 06:31 FTK Imager Pro: Features and Benefits 14:36 Training and Community Resources 16:29 Updates on FTK Suite and Scalability 19:10 On-Prem vs. Cloud Solutions 26:57 AI in Forensics: Benefits and Challenges 37:45 Addressing AI Bias in Forensics 38:53 Case Study: AI Misinterpretation in Seattle Shooting 40:14 The Importance of Validation in AI Forensics 41:18 Challenges in Identifying Legal vs. Illegal Content 43:08 The Future of AI in Forensics 44:18 Collaboration and Integration in Forensic Tools 46:07 The Role of APIs and Open Standards 47:18 Challenges with Proprietary Forensic Formats 54:36 The Need for High Compression Formats 56:32 Forensic Focus Podcast and Community Engagement 01:00:56 Upcoming Forensic Events and Presentations 01:06:23 Conclusion and Final Thoughts

Hello Interactors,I'm back! After a bit of a hiatus traveling Southern Europe, where my wife had meetings in Northern Italy and I gave a talk in Lisbon. We visited a couple spots in Spain in between. Now it's time to dive back into our exploration of economic geography. My time navigating those historic cities — while grappling with the apps on my phone — turned out to be the perfect, if slightly frustrating, introduction to the subject of the conference, Digital Geography.The presentation I prepared for the Lisbon conference, and which I hint at here, traces how the technical optimism of early desktop software evolved into the all-encompassing power of Platform Capital. We explore how digital systems like Airbnb and Google Maps have become more than just convenient tools. They are the primary architects of urban value. They don't just reflect economic patterns. They mandate them. They reorganize rent extraction by dictating interactions with commerce and concentrating control. This is the new financialized city, and the uncomfortable question we must face is this: Are we leveraging these tools toward a new beneficial height, or are the tools exploiting us in ways that transcends oversight?CARTOGRAPHY'S COMPUTATIONAL CONVERGENCEI was sweating five minutes in when I realized we were headed to the wrong place. We picked up the pace, up steep grades, glissading down narrow sidewalks avoiding trolley cars and private cars inching pinched hairpins with seven point turns. I was looking at my phone with one eye and the cobbled streets with the other.Apple Maps had led us astray. But there we were, my wife and I, having emerged from the metro stop at Lisbon's shoreline with a massive cruise ship looming over us like a misplaced high-rise. We needed to be somewhere up those notorious steep streets behind us in 10 minutes. So up we went, winding through narrow streets and passages. Lisbon is hilly. We past the clusters of tourists rolling luggage, around locals lugging groceries.I had come to present at the 4th Digital Geographies Conference, and the organizers had scheduled a walking tour of Lisbon. Yet here I was, performing the very platform-mediated tourism that the attendees came to interrogate. My own phone was likely using the same mapping API I used to book my AirBnB. These platforms were actively reshaping the Lisbon around us. The irony wasn't lost on me. We had gathered to critically examine digital geography while simultaneously embodying its contradictions.That became even more apparent as we gathered for our walking tour. We met in a square these platform algorithms don't push. It's not “liked”, “starred”, nor “Instagrammed.” But it was populated nonetheless…with locals not tourists. Mostly immigrants. The virtual was met with reality.What exactly were we examining as we stood there, phones in hand, embodying the very contradictions we'd gathered to critique?Three decades ago, as an undergraduate at UC Santa Barbara, I would have understood this moment differently. The UCSB geography department was riding the crest of the GIS revolution then. Apple and Google Maps didn't exist, and we spent our days digitizing boundaries from paper maps, overlaying data layers, building spatial databases that would make geographic information searchable, analyzable, computable. We were told we were democratizing cartography, making it a technical craft anyone could master with the right tools.But the questions that haunt me now — who decides what gets mapped? whose reality does the map represent? what work does the map do in the world? — remained largely unasked in those heady days of digital optimism.Digital geography, or ‘computer cartography' as we understood it then, was about bringing computational precision to spatial problems. We were building tools that would move maps from the drafting tables of trained cartographers to the screens of any researcher with data to visualize. Marveling at what technology might do for us has a way of stunting the urge to question what it might be doing to us.The field of digital geography has since undergone a transformation. It's one that mirrors my own trajectory from building tools and platforms at Microsoft to interrogating their societal effects. Today's digital geography emerges from the collision of two geography traditions: the quantitative, GIS-focused approach I learned at UCSB, and critical human geography's interrogation of power, representation, and spatial justice. This convergence became necessary as digital technologies escaped the desktop and embedded themselves in everyday urban life. We no longer simply make digital maps of cities and countrysides. Digital platforms are actively remaking cities themselves…and those who live in them.Contemporary digital geography, as examined at this conference, looks at how computational systems reorganize spatial relations, urban governance, and the production of place itself. When Airbnb's algorithm determines neighborhood property values, when Google Maps' routing creates and destroys retail corridors, when Uber's surge pricing redraws the geography of urban mobility — these platforms don't describe cities so much as actively reconstruct them. The representation has become more influential or ‘real' than the reality itself. This is much like the hyperreality famously described by the French cultural theorist Jean Baudrillard — a condition where the simulation or sign (like app interfaces) replaces and precedes reality. In this way, the digital map (visually and virtually) has overtaken the actual territory in importance and impact, actively shaping how we perceive and interact with the real world.As digital platforms become embedded in everyday life, we are increasingly living in a simulation. The more digital services infiltrate and reconstitute urban systems the more they evade traditional governance. Algorithmic mediation through code written to influence the rhythm of daily life and human behavior increasingly determines who we interact with and which spaces we see, access, and value. Some describe this as a form of data colonialism — extending the logic of resource extraction into everyday movements and behaviors. This turns citizens into data subjects. Our patterns feed predictive models that further shape people, place…and profits. These aren't simple pipes piped in, or one-way street lights, but dynamic architectures that reorganize society's rights.LISBON LURED, LOST, AND LIVEDThe scholars gathered in Lisbon trace precisely how digital platforms restructure housing markets, remake retail ecologies, and reformulate the rights of humans and non-humans. Their work, from analyzing platform control over cattle herds in Brazil to tracking urban displacement, exemplifies the conference's focus: making visible the often-obscured mechanisms through which platforms reshape space.Two attendees I met included Jelke Bosma (University of Amsterdam), who researches Airbnb's transformation of housing into asset classes, and Pedro Guimarães (University of Lisbon), who documents how platform-mediated tourism hollows out local retail. At the end of the tour, when a group of us were looking to chat over drinks, Pedro remarked, “If you want a recommendation for an authentic Lisbon bar experience, it no longer exists!”Yet, even as I navigated Lisbon using the very interfaces these scholars' critique, I was reminded of this central truth: we study these systems from within them. There is no outside position from which to observe platform urbanism. We are all, to varying degrees, complicit subjects. This reflection has become central to digital geography's method. It's impossible to claim critical distance from systems that mediate our own spatial practices. So, instead, a kind of intrinsic critique is developed by understanding platform effects through our own entanglements.Lisbon has become an inadvertent laboratory for this critique. Jelke Bosma's analysis of AirBnB reveals how the platform has facilitated a shift from informal “home sharing” to professionalized asset management, where multi-property hosts control an increasing share of urban housing stock. His research shows “professionally managed apartments do not only generate the largest individual revenues, they also account for a disproportionate segment of the total revenues accumulated on the platform”. This professionalization is driven by AirBnB's business model and its investment in platform supporting “asset-based professionalization,” which primarily benefits multi-listing commercial hosts. He further explains that AirBnB's algorithm “rewards properties with high availability rates,” creating what he calls “evolutionary pressures” on hosts to maximize their listings' availability. This incentivizes them to become full-time tourist accommodations, reducing the competitiveness of long-term residential renting.The complexity of this ecosystem was also apparent during our Barcelona stop. What I booked as an “Airbnb” was a Sweett property — a competitor platform that operates through AirBnb's APIs. This apartment featured Bluetooth-enabled locks and smart home controls inserted into an 1800s building. Sweett's model demonstrates how platform infrastructure not only becomes an industry standard but is leveraged and replicated by competitors in a kind of coopetition based on the pricing algorithms AirBnB normalized.In Lisbon, my rental sat in a building where every door was marked with AL (Alojamento Local), the legal framework for short-term rentals. No permanent residents remained; the architecture itself had been reshaped to platform specifications: fire escape signage next to framed photos, fire extinguishers mounted to the wall, and minimized common spaces upon entry. It's more like a hotel disaggregated into independent units.Pedro Guimarães's work provides the commercial counterpart to Jelke's residential analysis, focusing on how platforms reshape urban consumption. His longitudinal study demonstrates that the “advent of mass tourism” has triggered a fundamental “adjustment in the commercial fabric” of Lisbon's city center.This platform-mediated transformation involves a significant shift from services catering to locals to spaces optimized for leisure and consumption. Pedro's data confirms a clear decline and “absence of Food retail” and convenience shops. These essential services are replaced by a “new commercial landscape” dominated by HORECA (hotels, restaurants, and cafes), which consolidates the area's function as a tourist destination.(3)Crucially, the new businesses achieve algorithmic visibility by manufacturing “authenticity”. They leverage local culture and history, sometimes even appropriating the decor of previous, traditional establishments, as part of “routine business practices as a way of maximizing profit”. The result is the “broader construction of a new commercial ambiance” where local food and goods are standardized and adapted to meet international tourist expectations.(3)My own searches validated these findings. Searching for restaurants on Google Maps throughout Southern Europe produced a bubble of highly-rated establishments near tourist sites, many featuring nearly identical, tourist-friendly menus. The platforms had learned and enforced preferences, creating a Lisbon curated only for visitors. Furthermore, data exhaust from tourist movements becomes a resource for further optimization. Google's Popular Times feature creates feedback loops where visibility generates visits, which reinforce visibility. The city becomes legible to itself through platform data, then reshapes itself to optimize what platforms measure.The Lisbon government, while complicit, also shows resistance. Both scholars highlighted municipal attempts to regulate platform effects, including issuing licensing requirements for AirBnB, zoning restrictions, and promoting local commerce apps that compete with global platforms (e.g., Cabify vs. Uber). These interventions reveal platform urbanism can be contested. However, as Jelke noted, platforms evolve faster than regulation, finding workarounds that maintain extraction while performing compliance.All through the trip, I felt my own quiet sense of complicity. Every ride we called, every Google search we ran, every Trainline ticket I purchased, fueled the very datasets everyone was dissecting. It's an uneasy position for a critical digital geographer — studying problematic systems we help sustain. We are forced to understand these infrastructures by seeing. Can that inside view start seeking a new urban being?CODE CRACKED CITIES. GOVERNANCE GONEMy conference presentation leveraged my insider vantage from three decades at Microsoft. I traced how these digital infrastructures have sunk into everyday life by reshaping labor, space, and governance. From early desktop software I helped to build to today's platform urbanism, I showed how productivity tools became cloud platforms that now coordinate work, logistics, and mobility across cities.My framing used a notion of embeddedness through the lens of three key figures in the literature: Karl Polanyi, a political economist who argued that markets are always “embedded” in social and political institutions rather than operating on their own; Mark Granovetter, a sociologist who showed that economic action is structured by concrete social networks and relationships; and Joseph Schumpeter, an economist who described capitalism as driven by “creative destruction,” the continual remaking of industries through innovation and destruction. Platforms help mediate mobility, labor, commerce, and governance, even as they position themselves at arm's length from the regulatory and civic structures that historically governed urban infrastructures.This evolution is paradoxical. As platforms weave themselves into the operational fabric of urban life, they also recast the division of responsibilities between state, market, and infrastructure provider. Their ability to sit slightly outside traditional regimes of oversight allows them to appear as ready-made “fixes” for governments and consumers at multiple scales. Yet each fix comes with systemic costs, deepening dependencies on opaque, tightly coupled infrastructures and amplifying the vulnerabilities of urban systems when those infrastructures fail.This progression reveals distinct phases of infrastructural transformation. It began in the Desktop Era (1980s-1990s) when I started at Microsoft and software was fixed to devices, localizing information work on individual desktops. Updates arrived episodically on physical media like floppy disks — users controlled when to install them. The shift to local area networks gave IT departments a hand in that control. Soon the Internet was commercialized which fundamentally altered not just how software circulated but how it was installed and updated. How it was governed. What once required user consent — inserting a disk, clicking “install” — became silent, automatic, and infrastructural. Today's cloud services and IoT extend this transformation, embedding computational governance into vehicles, supply chains, and bodies themselves.This progression reveals distinct phases of infrastructural transformation. The Desktop Era (1980s-1990s) embedded information work in individual devices — the fix was productivity, the limit was scalability. The Network Era (1990s-2000s) transformed software into continuous services — the fix promised seamless coordination, the exposure was infrastructural dependency. The Platform Era (2000s-2010s) decoupled software from devices entirely through APIs and cloud computing — the fix was coordination at scale, the cost was asymmetric control. The current IoT and Surveillance Era embeds platform logic in everyday urban environments — the fix is pervasive coordination. This creates a total dependency on opaque infrastructures provided primarily by three companies: Google, Amazon, and Microsoft. This chokepoint is what contributes to global vulnerability and cascading failures.Recent large-scale cloud incidents, such as the latest AWS outage in Virginia in October — a week before the conference — make this evident. When a single region fails, payment systems, logistics platforms, and mobility services stall simultaneously. This pattern echoes an earlier cloud-network outage in 2021, in the same Virginia region, that effectively took much of Lisbon offline for hours, disrupting everything from transit information to local commerce. In both cases, what looks like flexible, placeless digital infrastructure turns out to be highly geographically concentrated and deeply embedded in local urban systems.And yet, in nearly every case, these platforms really do operate as fixes at many different geographical scales. For capital, they open new rent-extraction terrains. For workers, they provide precarious income patches through part-time gig work. For users, they deliver connectivity and convenience. But a paradox emerges. Those same apps include affective hooks: user interfaces offering intermittent rewards — dopamine hits stemming from posts, likes, and ratings — embedded within endless, ad-riddled feeds. For cities, they promise smooth, efficient solutions to chronic problems. Yet as my presentation argued, these fixes are mutually reinforcing, binding participants into infrastructures of dependency that appear empowering while deepening exposure to systemic risk.The paradox is clearest in places like the Sweett apartment in Barcelona. For users, it's frictionless: Bluetooth locks, smart controls, and seamless check-in. For Sweett it's all running on AirBnB's own APIs even as they compete with AirBnB. For locals, the same infrastructure can help homeowners supplement income by renting a room, but it mostly converts affordable real estate into a short-term rental market. This drives up values, rents, and displacement. Platform standards like this spread until they feel inevitable. The logic embeds so deeply in the housing system that not optimizing for transient guests starts to seem irrational. Eventually, alternative futures for the neighborhood become hard to imagine and politically unviable.What distinguishes digital platforms from earlier infrastructural transformations is their selective embeddedness. At the micro scale, interfaces shape conduct through programmable boundaries. At the meso scale, standards lock institutions into ecosystems. At the macro scale, chokepoints concentrate control in firms whose decisions cascade globally. Across all scales, platforms govern without being governed. They embed coordination while evading accountability.The conference made clear that digital geography has fully evolved from my days studying ‘computer cartography' in the 80s. It's scaled to meet a world organized by the infrastructures I went on to help build. We are no longer observing digital representations of space. We're mapping out the origins of a new way of thinking about space using algorithms. My tenure at Microsoft, spent building tools that would transform into embedded, governing platforms, was a preview of the world we now inhabit. This is a world where continuous deployment has become continuous urban reorganization. The silence of the automatic software update metastasized into the silent, pervasive governance of the city itself.Lisbon, then, is not merely a case study but a dramatic staging of hyperreality. The Alojamento Local (AL) sign outside our Lisbon apartment door is not a description of a short-term rental; it is a code enforced reality optimized for a tourist's online profile. The digital map, our simplified version of reality, has not just overtaken the actual territory; it now precedes it, dictating its function and challenging its original meaning.This convergence leaves the critical digital geographer in an inherently unstable ethical position. Studying problematic systems while structurally forced to sustain them requires critiquing the data exhaust our own movements and decisions generate.This deep understanding of digital platforms effects, gained from the trenches, is an asset. How else would this complex entanglement get revealed? It begs to move beyond just observing platform effects to articulating a collective response to this fundamental question: How do we encode accountability back into these infrastructures and rebuild a foundation for civic life that is not merely an optimization of its own surveillance? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit interplace.io

The latest In Touch With iOS with Dave he is joined by Jill McKinley, Chuck Joiner, Jeff Gamet, Eric Bolden, Marty Jencius.In Episode 396, the panel covers a packed week of Apple updates including VisionOS 26.2 beta 3, iOS/iPadOS 26.2 features, and AirPods Pro firmware changes. Jill and Eric share their joint Vision Pro demo adventure, the team debates macOS Tahoe instability and Apple's controversial liquid-glass icon redesign, everyone weighs in latest AI news from OpenAI (GPT-5.1) Google Gemini 3. We explore digital driver's licenses arriving in Illinois, MLB's new broadcast deals with ESPN & Netflix, and a surprising new cross-platform file-sharing capability between iPhone and Android. The show notes are at InTouchwithiOS.com  Direct Link to Audio  Links to our Show Give us a review on Apple Podcasts! CLICK HERE we would really appreciate it! Click this link Buy me a Coffee to support the show we would really appreciate it. intouchwithios.com/coffee  Another way to support the show is to become a Patreon member patreon.com/intouchwithios Website: In Touch With iOS YouTube Channel In Touch with iOS Magazine on Flipboard Facebook Page BlueSky Mastodon X Instagram Threads Summary This week's episode dives into an unusually busy stretch across Apple hardware, software, AI, and ecosystem services. The show opens with Vision Pro news as visionOS 26.2 beta 3 arrives days after the other platform betas. Marty reports improvements like developer cable speed fixes and faster 2D-to-3D photo conversion. Jill and Eric recount their in-person meetup where Jill experienced a fully guided Vision Pro demo — including immersive video, spatial room exploration, and plenty of curious stares from coffee-shop onlookers wondering why Jill was "peering into invisible walls." The group then turns to iOS/iPadOS 26.2, covering new AirDrop temporary-share capabilities, privacy notice updates, hypertension notification APIs, new Japanese voice-assistant options, improvements to Liquid Glass UI effects, and multitasking enhancements like the return of Slide Over on iPad. AirPods Pro 3 beta firmware triggers a discussion on instability, unwanted auto-switching, and how firmware installs appear to now proactively ask users whether they want to participate. The episode shifts to macOS Tahoe 26.2, where Jeff vents about daily crashes, memory leaks, and wake-from-sleep failures — while others report fewer issues, sparking a possible exploration of third-party apps as the culprit. The panel also critiques Apple's polarizing icon redesign in Tahoe, agreeing that many icons look bland, boxed-in, and violate Apple's own historical Human Interface Guidelines. A major section of the show covers AI developments: • OpenAI GPT-5.1 — faster, more conversational, new tone presets (professional, candid, quirky), and "thinking mode" for deeper answers. • Google Gemini 3 Pro — improved multimodal reasoning, search integrations, and cloud-based inference. Jeff notes concerns about AI systems becoming overly anthropomorphic, while Jill admits she set her GPT tone to "nerdy" and likes it. Next, Apple's rollout of driver's licenses in Wallet hits Illinois, making it one of the largest states to adopt the feature. Dave describes server delays on launch day, and the panel discusses TSA compatibility, app differences between states, privacy details displayed, and state-by-state rollout inconsistencies. Sports streaming news surfaces as MLB renews contracts with ESPN, Netflix, and NBCUniversal, while also confirming Friday Night Baseball stays on Apple TV through 2028. The group reflects on the chaos of watching live sports across too many services and whether future licensing will simplify or worsen the landscape. The episode closes with Google's surprising announcement that iPhone ↔ Android file transfers via AirDrop/Quick Share are now possible on Pixel 10 devices. The panel predicts Apple will likely break this "for security reasons," especially considering regulatory scrutiny in the EU. Topics and Links

Una and Bramus recap the season! They share some new updates and re-visit some of their favorite tips and tricks.Season 6 covered inline if() statements and custom functions, scroll state queries, carousel APIs, view transitions updates, anchor positioning, command invokers and interest invokers, customizable select, and a whole bunch of other CSS functions! Resources: Same-document view transitions have become Baseline Newly available → https://goo.gle/4nCyFSe  Solved by CSS Scroll State Queries: hide a header when scrolling down, show it again when scrolling up (scrolled state query) → https://goo.gle/49uQMpN  css-extras – A collection of useful CSS custom functions → https://goo.gle/4qFjIS5  CSS Mixins Specification (ED): Defining Mixins → ​​ https://goo.gle/3JpX4MZ  Invoker Commands: Scroll Commands (OpenUI Meeting Notes) → https://goo.gle/47onsQB  Anchored queries → https://goo.gle/4oMCvJT  Customizable select → https://goo.gle/4r9Xsjv Una Kravets (co-host) Bluesky | Twitter | YouTube | WebsiteMaking the web more colorful @googlechrome  Bramus Van Damme (co-host) Bluesky | Mastodon | YouTube | Website@GoogleChrome CSS DevRel; @CSSWG; Scuba Diver

When it comes to connecting warehouse systems, few companies are tackling the challenge as directly as TrackStar. In this episode of The New Warehouse Podcast, Kevin chats with Jeremy Schneck and Daniel Langer, Co-Founders of TrackStar, about how they're simplifying integrations across the fragmented WMS landscape. The discussion explores TrackStar's journey from a startup pivot to a Y Combinator-backed company, the growing role of APIs in supply chain connectivity, and how universal APIs are driving the next wave of warehouse innovation.Learn more about Endpoint and give Gary a break here. Get your free ID Label sample right here. Follow us on LinkedIn and YouTube.Support the show

Puedes vernos o escucharnos desde ahora en la nueva app Be Native. Descárgala ya desde el App Store: Be Native. El 13 de noviembre de 2025, Apple hizo algo histórico: lanzar el Programa de Mini Apps con comisión del 15% (la mitad de lo habitual) y actualizar las App Review Guidelines de forma radical. En este episodio te explicamos TODO lo que necesitas saber como desarrollador iOS.

This week Rewarded Video Ads rolled out to everyone, developers got better tools to reimport meshes, content sharing APIs were released to make our own versions of Roblox Moments, Today's Picks in the avatar marketplace is going festive, Studio Script Sync is in beta, game page videos got an upgrade and Roblox have opened up the ability to opt-in game passes for Robux purchases.Chapters:(00:00) Intro(01:13) Monetisation - Rewarded Video Ads(07:57) Studio - Reimport Beta(14:42) Moments - Content Sharing API(19:41) Marketplace - Evolving Today's Picks(22:58) Roblox Trivia(28:30) Studio - Script Sync Beta(34:52) Game Page - Video Previews(40:37) Monetisation - Robux and Gamepass Bundles(44:43) OutroSeason 3 Episode 8Sources:- Rewarded Video Ads— https://devforum.roblox.com/t/rewarded-video-ads-are-now-available-to-all-ads-eligible-creators/4063278- Studio Reimport (beta)— https://devforum.roblox.com/t/studio-beta-reimport-one-click-updates-for-imported-3d-content/4068650- Content Sharing APIs (beta)— https://devforum.roblox.com/t/beta-content-sharing-apis-use-upload-api-and-recommendations-api-to-drive-discovery-and-engagement/4065417- Marketplace Today's Picks— https://devforum.roblox.com/t/evolving-today%E2%80%99s-picks-in-marketplace/4063692— Submit nominations: https://survey.roblox.com/jfe/form/SV_8cZb94oj9OvQm9g- Studio Script Sync (beta)— https://devforum.roblox.com/t/studio-script-sync-now-in-beta/4065468- Video Previews— https://devforum.roblox.com/t/video-previews-for-your-games-page/4068103- “Buy Robux” Pass Bundles— https://devforum.roblox.com/t/opt-in-your-passes-for-the-buy-robux-page/4065622Hosts:- Adam (BanTech): https://lastlevel.co.uk/adam- Fedor (LoadingL0n3ly): https://x.com/LoadingL0n3ly----------------------------Watch or listen wherever you get your podcasts.Visit https://lastlevel.co.uk/podcast for more.Join the Discord: https://discord.lastlevel.co.ukBeyond The Blox is produced by Seb Jensen for Last Level Studios.

In this episode of The Marketing Factor, Austin Dandridge sits down with Julian Modiano founder of Acuto and Weavely to unpack the future of data, automation, and AI inside modern marketing agencies.Julian's rare background blends deep PPC experience from Merkle and Brainlabs with true engineering chops as a Google Cloud developer — giving him a uniquely technical and marketer-centric view of what agencies actually need. We cover data warehousing, MMM vs attribution models, AI slop, automation pitfalls, BigQuery, Looker, TikTok's rise, and whether agencies should hire developers. This episode is loaded with practical insights for performance marketers, operators, founders, and anyone building the “agency of the future.”

⚙️ Optimizing Data for Better ROI and Efficiency

Gemini 3 is officially here. ✨ ✨ ✨For about 8 months, Gemini 2.5 Pro has mostly maintained its standing as the top LLM in the world yet Google just unleashed its successor in Gemini 3.0. So, what's new in Gemini 3? And whether you're a developer or casual user, what does Google's new model unlock? Join us as we chat with Google's Logan Kilpatrick's for all the answers. Gemini 3: What's new and what it unlocks for your business with -- An Everyday AI Chat with Google DeepMind's Logan Kilpatrick and Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Gemini 3 Release Overview & FeaturesState-of-the-Art AI Benchmarks ExceededGemini 3 in Google Ecosystem ProductsGemini 3 Vibe Coding Capabilities DemoNon-Developer Use Cases for Gemini 3Multimodal Understanding and VisualizationsAgentic AI Tools: Gemini Agent & Anti GravityBusiness Growth with Gemini 3 AI IntegrationTimestamps:00:00 Gemini 3: State-of-the-Art AI05:59 "Gemini 3: Build Ambitiously"08:16 "AI Studio: Bringing Ideas Alive"12:44 Gemini App Agents & Anti-Gravity14:57 "Enhancing AI as a Thought Partner"17:01 AI Studio: Build Apps FasterKeywords:Gemini 3, Gemini 3 Pro, Google AI, AI Studio, Vibe Coding, multimodal model, agentic coding, tool calling, anti gravity, generative interfaces, Gemini app, APIs, AI capabilities, interactive experience, visual dashboard, bespoke visualization, state-of-the-art model, developer platform, agentic developer tools, benchmark results, code editor, IDE integration, product experiences, infrastructure teams, triage inbox, personal assistant, proactive agents, 2.5 Pro, model capability, product feedback, code generation, gallery applets, build mode, ambition in AI, software engineering, feature enhancement, thought partner, AI-powered building, on demand experience, interactive visualizations, coding advancements, user engagement, real-time rollout.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Head to AI.studio/build to create your first app.  Head to AI.studio/build to create your first app. 

What You'll Learn- Why legacy commerce APIs and EDI no longer suffice in today's fragmented commerce landscape- How AI and emerging protocols like MCP are accelerating the need for real-time fulfillment integration- The structure, tools, and resources defined by OnX for seamless order management across ecosystems- The nonprofit "business league" legal framework that keeps OnX vendor-agnostic and collaborative- The challenges commerce platforms face with OMS integrations and how OnX aims to reduce friction- The shift from platform-centric to protocol-centric commerce enabled by open standards- How industry players—brands, 3PLs, ERP, WMS, and commerce platforms—are rallying behind OnXHihghlights- 00:00 — Welcome, introduction to Kelly Goetsch and the focus: “Connected Commerce”- 02:00 — The fragmentation problem: marketplaces, social commerce, AI, and legacy EDI- 04:00 — The rise of MCP and Agentic Commerce Protocol as enablers for a new standard- 06:00 — Building a “big tent” network: OMS, 3PLs, WMSs, ERPs connectivity challenges- 10:00 — Commerce platform vs fulfillment backend: the tech and mindset divide- 14:00 — What is OnX? Tools, resources, member base, and the standard's scope- 18:00 — How MCP makes OnX possible, collapsing layers between selling and fulfillment- 22:00 — OnX's “business league” structure explained- 24:00 — Platform, payment, and AI player involvement and adoption challenges- 28:00 — How to participate: advisory boards, GitHub access, and community involvement- 30:00 — The future of connected commerce and invitation to join OnXQuotes[00:02:00]: "If the last decade was about composable commerce, the next one is about connected commerce." - Ninaad [00:04:00]: "AI is the reason for both of these. We're really, really collapsing down." - Kelly Goetsch [00:10:00]: "About 70% of enterprise brands still run point-to-point integration, and that has its own set of challenges." - Ninaad [00:22:00]: "The benefit of that is: we, as a community, get together and evolve and change as technology changes. And that's great." - Kelly Goetsch About the GuestKelly Goetsch is a technologist and strategist shaping the future of digital commerce and order fulfillment. Known for his leadership in the MACH Alliance and now Pipe17, Kelly has been a central voice in evolving commerce technology standards. He currently chairs the Commerce Operations Foundation, driving the development and adoption of the OnX standard for connected commerce.Links Mentioned- Commerce Operations Foundation website: commerceopsfoundation.org- Commerce Operations Foundation GitHub: github.com/commerceopsfoundation- Kelly Goetsch on LinkedIn: linkedin.com/in/kgoetsch- MACH Alliance: machalliance.org  Subscribe and Keep Learning!If you're a logistics leader looking to scale sustainably, don't miss out! Subscribe for more expert strategies on tackling modern supply chain challenges.Be sure to follow and tag the eCom Logistics Podcast on LinkedIn and YouTube

Send us a textIn this special in-person episode of The MLO Project, Frazier and Michael sit down with Florida broker and First Coast Mortgage co-founder Jason Kindler, live from Idaho at the High Table mastermind. It's a no-fluff conversation about leadership, building efficient operations, crushing limiting beliefs, and redefining what's possible for mortgage companies heading into 2026.Kindler opens up about his personal and professional journey, including surviving the crash, getting sober, and rebuilding with intention. He shares how he's preparing his team to not just survive the next boom—but scale it, stress-free. This is a raw, strategic, and transparent deep dive into the mindset and systems that separate stagnant shops from future-proof machines.Key Topics Covered:Why operational efficiency isn't optional anymoreBuilding a tech-enabled brokerage that can scale without breakingHow small brokers can compete with big retail opsWhy speed still kills—and slow still losesAI, APIs, and building the “ideal” experiencePersonal resilience: Jason's journey through addiction and recoveryLaunching a coaching portal powered by AI + years of hard-won experienceWhy most brokerages wait too long to invest in infrastructureWhy perfect doesn't exist—but the ideal is realTactical Nuggets:Designing operational models that absorb 40–50 loans overnight without chaosHow to structure teams so originators get the support they deserveWhy it's time to unlearn what worked in the pastHow Kemmer is using two years of coaching transcripts to build a GPT-powered training hubPlanning for efficiency now so you're not scrambling when the boom hitsBig Quote:“You're 100% in control of your income. I don't care what the market's doing. I've had great years in this market—and so have others. It's mindset and execution. Period.” – Jason KemmerGuest Plug:Jason is building a full coaching platform loaded with systems, calculators, AI tools, and years of strategic content for loan officers and team leaders. Connect with him on social to learn more and get on the early list.https://firstcoastmortgagefunding.com/KindlerCoaching

Frank Sentner joins the Coterie Insurance podcast for the second time. Speaking with Bobbie Collies, Frank dives into discussing his thoughts on data standardization, innovation and change in the industry. Frank has extensive experience in the insurance technology sector, and brings a lot of background and knowledge to this episode. He highlights the importance of technology, particularly APIs and data standardization, in transforming the insurance landscape. Frank also explores the future of insurance, where data becomes a commodity and the role of AI in enhancing customer experiences. He advocates for a collective approach to data rights and the necessity for the industry to adapt to new technologies and practices.Thank you to Frank for his thoughts on data and where the insurance industry is today.Follow Coterie Insurance on LinkedIn.

In this episode of Technology Reseller News, Publisher Doug Green speaks with Jason Goecke, CTO and Robert Galop, CPO of Creo Solutions, about why vCons (virtual conversations) represent a “golden grail” revenue opportunity for service providers, MSPs, and telcos. Drawing on decades of telecom and CPaaS experience, the Creo team explains how their company was founded to help providers “2x their revenue” by layering practical AI, automation, and data intelligence on top of existing communications services. Their focus today: turning the billions of conversations crossing telecom networks into actionable business value. The discussion centers on vCons as a standard container for conversation data—not just recordings, but transcripts, metadata, compliance controls, and context. On their own, vCons “don't do anything,” as Galop notes, but once you analyze them at scale with AI, they reveal issues and opportunities that would otherwise stay invisible. In one deployment, a service provider believed they had excellent first-call resolution; Creo's analytics showed that agents were only truly resolving about 24% of calls, with 76% generating follow-ups and extra work. In another case, the very first processed call exposed a serious security gap: an agent forwarding a main number without validating the caller's identity. “Conversations have been dark data,” Goecke explains. “Now you can light up every conversation and drive value from it.” Creo's Pulse Conversation Intelligence platform (part of its broader Intelligence Cloud) is designed to make this revenue opportunity turnkey for providers. Rather than asking carriers or MSPs to build AI infrastructure, Creo takes in CDRs and call recordings (or vCons directly), handles speech-to-text, diarization, vCon creation, and then runs domain-specific analytics. Service providers can immediately offer offerings such as: 100% QA coverage for contact centers (versus the typical 2%), AI note-taking and action items for every voice call (not just Zoom/Teams meetings), and deep baseline insight into what's actually happening across sales, support, and operations. APIs and webhooks then allow these insights and summaries to flow into CRMs, bots, workflow engines, and custom applications, enabling personalized experiences and smarter automation without the customer needing to “speak AI.” A key message for MSPs and channel partners is that they don't need to be AI experts to sell and deploy this. Creo positions itself as a native AI company, using AI throughout its own development and delivery processes so that partners can simply deliver better outcomes: more meetings booked, better QA coverage, reduced manual note-taking, improved compliance, and richer customer journeys. “That really makes it easy for the service providers,” Goecke notes. “We're scratching a lot of very important itches—QA, notes, follow-up—and, oh by the way, it's all AI-forward.” For service providers looking to turn vCons from theory into concrete, recurring revenue in 2026, Creo Solutions invites listeners to learn more at https://www.creosolutions.tech/ and explore the Pulse platform at https://intelligence.cloud/.

Thomas Monz, CEO of AQT (Alpine Quantum Technologies), joins Sebastian Hassinger on The New Quantum Era to chart the evolution of ion-trap quantum computing — from the earliest breakthroughs in Innsbruck to the latest roll-outs in supercomputing centers and on the cloud. Drawing on a career that spans pioneering research and entrepreneurial grit, Thomas details how AQT is bridging the gap between academic innovation and practical, scalable systems for real-world users. The conversation traverses AQT's trajectory from component supplier to systems integrator, how standard 19-inch racks and open APIs are making quantum computing accessible in Europe's top HPC centers, what Thomas anticipates from AQT launching on Amazon Braket, a quantum computing service from AWS, and what it will take for quantum to deliver genuine economic value.Guest Bio  Thomas Monz is the CEO and co-founder of AQT. A physicist by training, his work has helped transform trapped-ion quantum computing from a fundamental research topic into a commercially viable technology. After formative stints in quantum networks, high-precision measurement, and hands-on engineering, Thomas launched AQT alongside Peter Zoller and Rainer Blatt to make robust, scalable quantum computers available far beyond the university lab. He continues to be deeply engaged in both hardware development and quantum error correction research, with AQT now deploying systems at EuroHPC centers and bringing devices to Amazon Braket.Key Topics  From research prototype to rack-ready: How the pain points converting lab experiments into user-friendly hardware led AQT to build its quantum computers in the same form factors and standards as classical infrastructure, making plug-and-play integration with the supercomputing world possible.  Hybrid quantum–HPC deployments: Why systems-level thinking and classic IT lessons (such as respecting 19-inch rack and power standards) have enabled AQT to place ion-trap quantum computers in Germany and Poland as part of the EuroHPC initiative — and why abstraction at the API level is essential for developer adoption.  Error correction and code flexibility: How the physical properties of trapped ions let AQT remain agnostic to changing error-correcting codes (from repetition and surface codes to LDPC), enabling swift adaptation to new breakthroughs via software rather than expensive new hardware — and why end-users should never have to think about error correction themselves.  Scaling and networking: The challenges moving from one-dimensional to two-dimensional traps, the emerging role of integrated photonics, and AQT's vision for interconnecting quantum computers within and across HPC sites using telecom-wavelength photons.  From local to cloud: What AQT's move to Amazon Braket means for the range and sophistication of end-user applications, and how broad commercial access is shifting priorities from scientific exploration to real-world performance and customer-driven features.  Collaboration as leverage: How AQT's open approach to integration—letting partners handle job scheduling, APIs, and orchestration—positions it as a technology supplier while benefiting from advances across Europe's quantum ecosystem.Why It Matters  AQT's journey illustrates how “physics-first” quantum innovation is finally crossing into scalable, reliable real-world systems. By prioritizing integration, user experience, and abstraction, AQT is closing the gap between experimental platforms and actionable quantum advantage. From better error rates and hybrid deployments to global cloud infrastructure, the work Thomas describes signals a maturing industry rapidly moving toward both commercial impact and new scientific discoveries.Episode Highlights  How Thomas's PhD work helped implement the first three-qubit ion-trap gates and formed the foundation for AQT's technical strategy.  The pivotal insight: moving from bespoke lab systems to standardized products allowed quantum hardware to be deployed at scale.  The surprisingly smooth physical deployment of AQT machines across Europe, thanks to a “box-on-a-truck” design.  Real talk on error correction, the importance of LDPC codes, and the flexibility built into trapped-ion architectures.  The future of quantum networking: sending entangled photons between HPC facilities, and the promise of scalable cluster architectures.  What cloud access brings to the roadmap, including new end-user requirements and opportunities for innovation in error correction as a service.---- This episode offers an insider's perspective on the tight coupling of science and engineering required to bring quantum computing out of the lab and into industry. Thomas's journey is a case study in building both technology and market readiness — critical listening for anyone tracking the real-world ascent of quantum computers. In the spirit of full disclosure, Sebastian is an employee of AWS, working on quantum computing for the company, though he is not a member of the Braket service team. 

Keith discusses the evolving role of AI in real estate, highlighting its impact on property management and tenant interactions.  He contrasts traditional AI, which excels in IQ tasks but lacks emotional intelligence (EQ), with agentic AI, which can perform autonomous actions. Dana Dunford, CEO of Hemlane, explains how their platform uses AI to streamline repair requests, leasing, and tenant communication. She emphasizes the importance of human oversight for tasks requiring EQ.  Looking ahead, Dana predicts increased standardization and remote-first investing, with technology playing a crucial role in enhancing real estate management efficiency. Resources: Explore Hemlane's property management platform and request a demo at www.hemlane.com  Mention the GRE podcast when signing up with Hemlane to receive a 20% discount on the first year. Episode Page: GetRichEducation.com/580 For access to properties or free help with a GRE Investment Coach, start here: GREmarketplace.com GRE Free Investment Coaching: GREinvestmentcoach.com Get mortgage loans for investment property: RidgeLendingGroup.com or call 855-74-RIDGE  or e-mail: info@RidgeLendingGroup.com Invest with Freedom Family Investments.  For predictable 10-12% quarterly returns, visit FreedomFamilyInvestments.com/GRE or text  1-937-795-8989 to speak with a freedom coach Will you please leave a review for the show? I'd be grateful. Search "how to leave an Apple Podcasts review"  For advertising inquiries, visit: GetRichEducation.com/ad Best Financial Education: GetRichEducation.com Get our wealth-building newsletter free— GREletter.com or text 'GRE' to 66866 Our YouTube Channel: www.youtube.com/c/GetRichEducation Follow us on Instagram: @getricheducation Complete episode transcript:   Keith Weinhold  0:01   Keith, welcome to GRE. I'm your host. Keith Weinhold, what will real estate look like in five years as AI keeps making inroads into our lives, learn how people have begun using it to manage their rental properties and doing it more cost effectively than humans can. It's a forward looking episode today on get rich education.   Speaker 1  0:26   Since 2014 the powerful get rich education podcast has created more passive income for people than nearly any other show in the world. This show teaches you how to earn strong returns from passive real estate investing in the best markets without losing your time being a flipper or landlord. Show Host Keith Weinhold writes for both Forbes and Rich Dad advisors, and delivers a new show every week since 2014 there's been millions of listener downloads of 188 world nations. He has a list show guests include top selling personal finance author Robert Kiyosaki. Get rich education can be heard on every podcast platform, plus it has its own dedicated Apple and Android listener phone apps build wealth on the go with the get rich education podcast. Sign up now for the get rich education podcast, or visit get rich education.com   Corey Coates  1:11   You're listening to the show that has created more financial freedom than nearly any show in the world. This is get rich education.   Keith Weinhold  1:27   Welcome to GRE from Long Island's Hamptons to Hampton Roads, Virginia and across 188 nations worldwide. I'm Keith Weinhold, and you are listening to get rich education way back in the year 2010 when someone said AI, that could only mean one thing they were talking about, Alan Iverson today, it means artificial intelligence, because chatgpt debuted three years ago this month, and gosh, that changed a lot. It changed how you search for answers to everyday questions. We'll get into applying AI to real estate and property management shortly. But more broadly, look, here's what's interesting, the very premise of a chat bot, like just hearing that word, it sounds really cold and impersonal, yet think about it, Google was way less personal. When you Google something a decade ago, say list the three best paints for drywall, you'd get a list of links, and then you had to dig in and synthesize things and often interpolate to find your answer, or maybe you wouldn't even get the right answer. Instead, today, a chatbot on chatgpt or Gemini gives you the answer in nice, friendly sentences. Maybe they'll list some acrylic and latex paint varieties, and then after the answer, they come back and ask you a good follow up question. If you'd like to dig in for a deeper answer, they'll bring up something that you hadn't considered before, perhaps like it'll turn around and ask you if you want them to refine their answer to just the best latexes and acrylics specifically for rentals. And then it will ask, Would you like me to do that for you? And when you see that, you quickly feel like it's more friendly than that old list of links from a Google search. Yeah, that's a friendly Chatbot. And you can start to see what I mean here. It's not so cold and impersonal. Understand that these platforms ask you a friendly follow up question, because they want to keep you on that platform, just like anywhere else, does you already hear less about hallucinations than you used to when it would just cough up these weird errors? I feel like it's giving better answers than it did just a year or two ago. In my experience, one place where you need to be careful is that these platforms are being so nice to you at times they seem a little too agreeable. One way to break that is to tell the AI challenge my thinking, just those three words can give you a more complete answer. Challenge my thinking, as we already know, one danger about AI is everyone is quickly becoming really reliant on it, and this could be especially harmful to kids that haven't developed independent skills yet. Now I heard from a young teacher who quit her job. A lot of kids don't know how to read today. Why would they when they can just hit a button and it reads it out loud for them, between third and fourth grade, that's when children should transition from learning to read over to reading to learn. Kids have aI right in their hand now, not every kid, but increasingly, they aren't writing a full essay by hand with their own thoughts that they conjured up. Of course, chatgpt does that for them. Now it's probably good to teach chatgpt to kids in older grades, that is, if they don't already know it better than the teachers do, but you've increasingly got teens and young adults that say don't know how to write a cover letter for a resume because it's done for them. Now, much of what I've been talking about so far is called generative AI, and all that means is that it creates new content in response to your prompt. Today, we'll also talk about agentic AI in real estate that is spelled like agent and with IC at the end. How agentic AI is different from Oh, the chat GPT or Gemini prompts that I was talking about is that it acts on its own to perform a series of actions to reach a goal. So agentic AI gets kind of autonomous.    Keith Weinhold  6:06   Before we bring in a great guest to talk more about AI and property management. If you're looking for another episode on how to use AI more broadly in your life and broadly in real estate, check out episode 543 of the get rich education podcast that was a great episode from back in March again, that was episode 543 titled How to use AI for real estate.   Keith Weinhold  6:34   Now let's pull back and humanize things a little before we talk about bots. I just caught myself doing something kind of funny. Now, the other day, I used the hand ergometer at the gym. If you don't know what that is, while you're oftentimes standing up, you basically use your hands to crank this device's pedals in much the same way that bicycle pedals move. It exercises your biceps, triceps, forearm muscles. I have never seen anyone use this device at the gym before, not one person, but I wanted to try them, right? It seems like I often want to try something different from everyone else, and it looks just slightly odd to use this hand ergometer machine. Well, that's not the funny part. The next day, I was throwing a football around with a friend, and I couldn't figure out why throwing a spiral was so difficult for me and why my throwing accuracy was dreadful. Later, when I got home, my forearm started feeling sore. Oh, and I realized it was from using that hand ergometer. You know, this is such a typical guy thing to do, I made sure to DM that friend immediately to tell him that my football throws were lousy only because I had used a hand ergometer at the gym the day before. And he basically replied, yeah, your throws were really bad. It's funny that I felt so compelled to DM him like, hey, I really don't want ed thinking that I can't throw a football like that is so important or something. I could have done anything else with that two minutes of my life, but I cannot go about the rest of my day if Ed thinks I've got a bad football spiral like so important, like, my flight to Paris leaves in 30 minutes, but I'll put that whole trip in doubt, because I can't forget to tell ed I can usually throw a spiral on a football better than what he's thinking. Because, admit it, everybody has an ego. Some are just bigger than others. Well, I am bursting at the seams with a lot of broad real estate investing techniques and developments for you, but I'm putting that on hold until after today's show.    Keith Weinhold  8:45   We're talking with the CEO and co founder of property management platform, hemlane. It's spelled H, E, M, L, A, N, E, hemlane. I'll ask her where real estate will be within five years. She's a really intelligent woman and fully aware that your tenants don't want a bot to handle all of their maintenance requests. It's a lot like how you don't want to say representative to an automated phone system. It's hard to be nice when you're trying to clearly articulate it for the third time representative. Let's meet this week's guest.   Keith Weinhold  9:33   This week's guest is the CEO and co founder of hemlane. They're a property management platform with over 28,000 rentals and a billion dollars in payments process, just like we have been since day one here at GRE She is a strong advocate of purchasing properties anywhere. So that's often going to be outside your home state, because if best investments typically aren't right in your backyard, and why would you limit yourself? She supports real estate investors in setting up the most intelligent process to manage rentals from a distance, in case you want to self manage and do that. She's been named one of the top 20 women leaders and influencers in real estate tech. She has a distinguished resume previously working at Apple, and she received her MBA from Harvard Business School. She's an interesting person too. In her free time, she's an avid equestrian, paraglider and skier, so like me, she sort of has this substantial life outside of real estate too. Come on. You need to do that for your sanity. Well, we've been talking for almost a year now, but this is your first time on the show. Hey, welcome. It is the GRE debut of Dana Dunford.   Dana Dunford  10:44   Thanks so much Keith for having me. I'm so excited to be on your show and have been following it for a long time. So huge fan.   Keith Weinhold  10:52   Appreciate that Dunford is spelled D, u n, f, O, R, D, for listeners in the audio only. And this is a rather forward looking episode streamlining how to use AI in real estate and as a property management solution, putting that in your hands so that you could do that yourself. And before we're done, Dana is going to tell us what real estate investing will look like in five years, and if it's a good time to invest now. But first, Dana, I know you're an expert in leading having autonomous agents handle the tenant relations, things like communication and repair orders to a unit and rent collection. But I think a lot of people aren't really sure what an autonomous agent is. They're like, Hmm, is that somewhere between an autonomous car and a Roomba or something? So what is an autonomous agent?   Dana Dunford  11:42   Yeah, so there's two different types of AI, and where we are right now is with traditional AI. There's also agentic AI, where essentially AI will just take over, be proactive, think about things in advance, know exactly how to solve and make decisions. But Keith, to your point, very many out there here, AI, it's very much of a buzzword, and so I love some sort of parallels, just like you had mentioned with like the robot vacuum. I think a really good parallel would be self driving cars, because that's something that's applicable. We can all relate to. You know, you have Tesla, I have one, and it can drive me to and from work at any time, fully on that autonomous but there will be occasionally times in San Francisco where it will require me to take over the wheel because it's too foggy. There's something that goes on that's too complex of a situation. That is where I would say AI is today that traditional, where it's like it can follow exactly a process, but if the process messes up, like there's something in its way, it can't make a decision. It beeps at you and says, take over, whereas if you look at something like Waymo on the self driving car side, that is fully autonomous. There's no one there. There's no one making decisions. But it's very limited on where it can go, what it can do. Now the technology is better, and that's for another conversation, but it's just slower to go to market. And so with traditional AI, and what we're seeing now, it's fast to market. Everyone can use it, but you can't rely on it 100% you can't say it takes the wheel 100% of the time. And I don't have to think about it. And so that is where we are. I think a lot of experts in the space will say 2030, is when we will see this agentic AI. Will see it completely take over, but we're just not there today.    Keith Weinhold  13:47   All right, we're talking about the transition from traditional AI, which is in place today, to agentic AI, perhaps the Advent or popularity of that in five years, when I think about autonomous agent a lot of times, I like to look at etymology. Just what does that specifically mean? So we're talking about for another AI or a bot, if you will, to have autonomy over decision making. And when we think about autonomous agency with property management, how can we think of that application?   Dana Dunford  14:20   Yeah, I think that you need to break it down into what AI does very well right now, and what you could have aI fully take over, and where you might have some problems. And let me back up to if everyone remembers Watson, who beat Jeopardy, this was a while ago. The reason was, was actually because AI is very good at IQ. It can look up a ton of facts, or it can solve a really complex math problem. So anything on like the IQ side, AI is great to solve, but it's EQ that AI. Lacks, yeah, and EQ is me picking up the phone and saying, you know, Keith, I'm so sorry I messed up on, you know, whatever it was for you. If you're my boss, I'm so sorry here. So I'm going to make it right. Blah, blah, blah, blah, blah. And so that's where AI is not as good. And so when I think about any kind of system with real estate, you know, putting together your pro forma and looking at the cash flow and all of that, like AI can actually do it well, if you set up these are all the prompts that I would need, or take everything from insurance to interest rates and come up with the pro forma. But where AI will fail is a lot of times on the tenant communication side. And the reason for that is, let's just say, Keith, you have a apartment complex and there is the heat out. Well, if someone has a screaming baby in the background when you pick up the phone, you are going to answer that question, or you're going to talk to that tenant a lot differently if you're human versus if you're AI, you're going to say, oh my gosh, you have a four month old baby. You know, I also have kids. I know exactly what you're going through. And just so you know that HVAC technician is coming out right away, I will be here for you. I'm going to call you in five minutes. And so I always say, especially in real estate, because real estate is a people business, you really need to what, what you're trying to automate, or what you're trying to use, AI into four quadrants, and one axis, the horizontal axis, is IQ. Anything along that access it does well, but the vertical axis is EQ. And so the higher up you go on EQ, where you need relationships, the less likely it is, or my recommendation, would be, put a human in there. And so when we think about AI, it's like, if you're calling someone to confirm an appointment and remind them that, like an electrician is going to be there in an hour, you don't really need a human to do that. That's something that AI can do, and someone's going to have a delightful experience, right? But if it's something that requires that, EQ, that's where you're still going to have to have humans there.   Keith Weinhold  17:11   One thing that I often think about is, some years ago, popular email providers like Gmail, when someone would send you an email message asking you a question, Gmail basically started reading that email for you and giving you three little bubbles to click on the bottom, basically where you can click a yes answer, no answer or a follow up for more information, does that help give some relativity to what We're talking about here in property management and those tenant relations.   Dana Dunford  17:43   Yeah. I mean, I think that the Gmail with like, yes, no or No, thank you, or you get it also on LinkedIn that almost has zero EQ, because it's really just answering a question. It's not saying, Keith, I hope you had a wonderful weekend. You know, on your run, blah, blah, blah, blah, blah. It's not doing any of that. And so I think that is very much of a case of like, it's responding exactly to the email. I do think AI is getting better, where it's having that human touch involved in it when it responds to things. So now in Gmail, where you can have it draft you a response, but at the same time, it's not quite there unless it has enough context. And what I mean by context, and Gmail is such a good example, let's just say Keith today, if you look at Gmail and it's responding to an email, it is literally only responding based on the context it has in that email, right? But let's just say Keith, that you could increase context. So I gave you two axes, like EQ and IQ, high and low on both. Imagine if I could add a third axis on there, so it's almost like 3d and it's context. Now imagine that email you just mentioned came in, and it also could look at my messages, Keith with you on, let's just say Facebook, it also could look at the last shows that you had out there. It also just looked online at things, and maybe it could look at other, you know, information that you might have posted on LinkedIn. And maybe you posted on LinkedIn about your run this weekend. Now I can respond with a lot more context. Hey, Keith, saw on LinkedIn. You had this that is actually adding EQ to it, where it's making it much more personalized. And I think that is where the future of technology is going, and that's why data is such a big play here, because the more context you have, the better you are. And you know, we see that personally as a tech company, we wanted to control more of the data. We don't want to have a ton of APIs with other companies running maybe self guided tours for us, or running the maintenance coordination, because we need that all in our system. Because if we don't have access to the lease agreement to know specifically, do they have an occupant under one years old in the place it makes it. Lot more difficult for us to respond in a very eloquent way and help solve that EQ problem that a lot of AI has today.   Keith Weinhold  20:09   Talk to us more about how today autonomous agents are helping with property management, whether that's handling tenant requests for repair issues or helping virtual showing. So tell us more about how it's really helping investors today, and then what to watch out for.   Dana Dunford  20:27   Yeah, definitely. So the autonomous agents, or at least the AI agents, that we have always draft things up. Well we use them for like, some of the best places to use them are things like troubleshooting repair requests. Okay, 7% of repair requests that come into our system. And I'm sure with any of your guys' portfolios, you'll see the same thing, 7% we can get the tenant to solve without liability. However, we have to train the AI, so we have to say, Listen, we can have zero liability with this. So if the ceiling is over 10 feet tall, do not put a tenant on a ladder and tell them to change a light bulb. You need to know exactly like you know when a tenant says, My light bulbs out and it checks out. They moved in a year ago. That's their responsibility. Like you are not going to put them on a ladder unless you have more of that context. And so on the troubleshooting side, that is a great way where AI can respond and fully come up with here's a summary of everything we've done. And here, this request was either closed or actually, we need to pass this over to human that is a great way to use AI. You just need to make sure the data you're using is right and it's trained in the right way. Because if you don't have all of those additional specific, intricate type of examples that I mentioned for residential property management, you can get in a lot of trouble this same for an autonomous agent would be on the leasing side. It's very easy to do it early on when you get the tenant inquiries coming in, because now what you're trying to do is just qualify them. Is this person qualified for a tour, and if they are, what time do they want to see the property? Right? And how do I get them in as quickly as possible? With that, though, you have to train it. So, for example, I live in California. I live in San Francisco. You can't just say the credit score requirement is 650 because if the person is on Section eight, which you are required to accept in California, you have to give an alternative to credit in order to let them qualify. And so that's where these models to get, these autonomous AI agents. It becomes really important to be a subject matter expert in the space and be able to run this and have it train and know exactly what it should be saying in those cases. Now, Keith, I always say kind of as a rule of thumb, the farther down you get on something, the more challenging it is for it to be fully autonomous. And that's where you need a human involved. So for example, for us, once you're talking to service professional and communicating between them and a tenant, you very much need a human to be there to help with that. And same thing on the leasing side, there is no way, actually, if you know anyone, Keith, I would love to talk to them, but there is no way a tenant is going to go ahead and talk to an AI agent all the way to signing a lease and handing over the keys, especially if you're doing something like self guided tours, they're going to want someone on the phone talking to them. Hey, I'm here for you again. That EQ those quadrants I mentioned, really bringing that into play. So I found a lot of things with property management. At the beginning, you can use AI, but there's a certain point where you get to something where you say, I actually need a human to be calling or messaging, because you need that additional touch.   Keith Weinhold  23:47   That makes sense. This is not buying a weed eater. This is actually a rather intimate transaction. We're talking about where you and your family are going to live and thrive and eat and sleep every day we're talking with hemlane, CEO and co founder, Dana Dunford, about applying AI in real estate and property management more when we come back with Dana, I'm your host. Keith Weinhold   Keith Weinhold  24:12   you know, most people think they're playing it safe with their liquid money, but they're actually losing savings accounts and bonds don't keep up when true inflation eats six or 7% of your wealth. Every single year, I invest my liquidity with FFI freedom family investments in their flagship program, why fixed 10 to 12% returns have been predictable and paid quarterly. There is real world security backed by needs based real estate, like affordable housing, Senior Living and health care. Ask about the freedom flagship program. When you speak to a freedom coach there, and that's just one part of their family of products, they've got workshops, webinars and seminars designed to educate you before you invest. Start with as little as 25k and finally, get. Money working as hard as you do, get started at Freedom, family investments.com/gre, or send a text now it's 1-937-795-8989, yep, text their freedom coach, directly again. 1-937-795-8989   Keith Weinhold  25:23   the same place where I get my own mortgage loans is where you can get yours. Ridge lending group and MLS, 42056, they provided our listeners with more loans than anyone because they specialize in income properties. They help you build a long term plan for growing your real estate empire with leverage. Start your prequel and even chat with President chailey Ridge personally while it's on your mind, start at Ridge lending group.com that's Ridge lending group.com   Dolf Deroos  25:56   this is the king of commercial real estate, Dolf de Roos. Listen to get rich education with Keith Weinhold and Don't Quit your Daydream.   Keith Weinhold  26:13   Welcome back to get rich education. We're talking with Dana Dunford in a rather forward looking episode, applying AI to real estate investing and property management and Dana, I think I would wonder about if AI has much reasoning ability, as far as, why don't we say prioritization with a tenant repair request? If a tenant has a repair request because their kitchen cabinet doors are squeaky, that's probably something that needs to be handled differently and is going to be lower on the priority chain than if a sink just flooded all over the bathroom floor, and it's going to ruin the subfloor in a few hours if it's not addressed. So where are we at with AI's reasoning ability there?   Dana Dunford  26:57   It's actually pretty good at prioritization, so it can tell our team where things are from a priority list, however, where we found that we've had to train it more, and this is us putting logic into it from a large language model, is it hasn't picked up certain things. And let me give you an example. Keith, my toilets not working, right? Okay, well, the biggest question to ask is, how many toilets do you have in the house? How many are in the property? Because if there is one, that is definitely an emergency, if there are two, not so much of an emergency. And so that's where there's additional contacts that comes in, go search under the marketing description, how many toilets are in this house, right? And then confirm with the tenant the other one is still functioning. And so there's certain things like that that we've found we've had to personally train to get it to respond in the right way. But overall, like generally, it's pretty good at helping to de escalate things, turning off valves saying, hey, mop up. You would be surprised how many tenants don't just like mop up the water on the floor. They're like, Oh, I wanted to keep it so you could see what it looked like. It's like, no, no, no, you need to mop it up. And by the way, we need fans in there. And there's a point where you just get a remediation specialist there. It's one of the most expensive trades, because usually insurance is called if you're calling a remediation group, but really understanding the extent of it and stuff like that, AI is actually pretty good at that. And the reason why is that is an IQ thing, where it's something easily searchable on the internet that is applicable to all homes, right? And so it's much easier for them to be able to do the prioritization of repairs.   Keith Weinhold  28:39   Okay? So an investor can basically buy or leverage the hemlane software and tell me, is there an AI integration with it? And like, how does that interface actually look and how much does the investor need to use it? What's already built in? Tell us more there.   Dana Dunford  28:58   Yeah. So we have a repair coordination. So when we build features, we build features to solve problems, not to like call it a feature, right? And so there's one feature we have called repair coordination, and that is to end to end, coordinate your repair all the way from troubleshooting to confirming work is completed and paying the service professional on your behalf. How we get that done. We don't think the owner really cares, as long as it's a five star experience for them and a five star experience for the tenant. And so what we've done in our approach has been, you always have humans that you start with, and these are people who are trained specifically in all of these things we've been talking about. Then what you do is you add AI in, and it's not quite yet a co pilot, a co pilot, is actually helping, like, make those decisions, but it's making the humans faster. And then the humans can come back to us, our repair coordinators, and say, Hey, listen, this is where the AI fails a bit. This is where I had to replace something in the AI before I clicked send. And. That is a really good way to do it, because I've seen out there, and I'm even though I'm in Silicon Valley, I'm in San Francisco, like aI Mecca, I'm probably more conservative on using it in part because of tenant landlord law and just what can go wrong. And so for me personally, it's like, I see sometimes out there where people's like, use our AI repair coordinator and it's fully AI. And it's like, yeah, but we've seen cases where the AI fails, just like I mentioned, where my car asks me to take over the wheel and and that's where I think that we're just not quite there yet, and we need to give it more time, you need to make sure you're using the right technology for it, but that's where I feel like it's almost more like an assistant to me versus an actual replacement or a co pilot yet, but it will soon get there.   Keith Weinhold  30:55   Well, a lot of times the producer or I guess, landlord, in this case, they want to use AI, but consumers don't really want to consume AI content. You can imagine, if a tenant had a problem, they don't want to feel like an AI was used all the way through the process and was never involved. So tell us more about that. I mean, how do the tenants take it?   Dana Dunford  31:17   Keith, I love that question so much. Because one I think sometimes technology companies are not transparent of what is AI and what is not AI. Yeah, I think the first thing you need to do is be transparent that it's aI talking to you. If you don't do that, you've suddenly lost trust, right? Sometimes they'll brand it as a person, but it's really not. So that's the first thing I would say. The second thing I would say is, if the AI solves what they need, we have found in a very delightful way. We have found that they don't care if it's AI, if they're chatting and it's so fast and the answer is their question, then they don't care that it's aI doing it, or human they just care about, what is my problem, and how do I get that solved? Right as quickly as possible. I think if AI was slow, they would care, like, they're like, Oh, it's a slow support agent, because they're too cheap to, like, invest in support. But no, they actually get their questions resolved. We have occasionally had tenants who have said, Hey, this didn't help me. You know, connect me with an agent, and then we connect them right away with an agent. But what's interesting in those cases is the AI actually had the right answer, so it gave them exactly the answer. But the person was like, I just don't want to talk to AI. Then the question is, how do you actually change it to make them want to talk to AI? And a lot of it has to do with that. EQ, how do you add it to make it such a delightful experience for them, where you're adding so much more in? And how you say, like, Does that help answer your question? I'm happy to like say it in a different way, if that is helpful. So I think a lot of times when someone says, oh, the AI answers that, but people just want to talk to human. It's really more that the AI didn't answer it how they wanted it to be answered, or it asked too many obnoxious questions, where the person's like, just let me talk to human. You're asking me the wrong questions. This is not applicable, and that's really where you need to have a better level of where your technology should be when you're responding to someone   Keith Weinhold  33:20   just quickly. Dana, how is it integrated with dispatch, with that sink flooded all over the floor? Example, would the AI know to contact a plumber versus just a handyman that works at a lower rate? So how does it work with dispatching?   Dana Dunford  33:35   They would before anything is dispatched, because it's another human involved. We do have, at this moment, we still have humans involved checking it, but it would know because of a couple of things we have. One is preferred service professionals. So who do you want to go out? First, second, third, fourth. Then of those service professionals, what do they do? Is it just septic, you know? Do they do full plumbing, whatever it may be, and then also, what that person's hours are like, if it's a weekend and it's an emergency and someone doesn't work weekends, you're not going to call that service professional. You're going to call the next one in line who is available. So all of that is built into it, but we still always have humans look it over to say, is that the right category? Are they dispatching the right service professional? All of that, eventually that can just take over with AI doing it. But at this moment, we still put humans involved, because most services have a service call, and we need a person to say, Yes, I made that decision to send that person out, just because, you know, could be $89 and for everything service calls add up, so we want humans to make that better for you?   Keith Weinhold  34:40   Yeah. All right, so we still have a good level of human involvement. Well, Dana, before I ask how our listeners can learn more about hemlane, what does investing in real estate look like in five years? Since you are rather forward looking there   Dana Dunford  34:56   yeah, So I think there's a couple of things right now. Keith, we had spoke. And right before this show started about how challenging it is. It's a slow real estate market. Yeah, it is. I still think people will regret if they don't purchase now versus in five years. You know, I still think you should be looking for those great deals where someone has to sell and the price doesn't matter as much and you don't have as much competition. So when you look five years out, it has to become easier to invest and manage Real Estate. Today, to me, it's still a broken process. It's still so challenging to get anything done, it's still so manual to get everything done, and it's also you're dealing with people, and people get exhausted by that, like the drama and stuff like that. So I think in five years, you'll have less of that, there will be much more standardization. And an example I would give is, like, with the taxi industry and Uber Right? Like, a very consistent quality, you know what you're going to get, you're going to get from point A to point B. We need the same thing for real estate, with what you're investing in? How that happens? There's a lot of great technology companies out there doing things exciting. Things are like fractional ownership and tokenization. I think that is something that online, being a little bit more passive is going to be a lot easier. I think remote first investing is going to be the way to go, people are going to feel so much more comfortable investing not in their backyard, which I know Keith, you and I are huge proponents of. And then I also just think that in the case of how many people are going to be focused on who's their tech partner versus just who's their local partner? I think that is going to be another thing, because of all of this we mentioned with AI and those who are using more technology, even just to source the deals. I'm not talking about management. I'm talking about straight from the start, or how you finance it. Anyone who is using more technology and better technology is definitely going to win in this space.   Keith Weinhold  37:02   Yeah, investing out of state continues to grow in popularity, and platforms like hemlane, with the right AI integrations can help reduce that friction in still a pretty high friction industry over the next five years. Well, Dana, I think you really going to get the wheels turning for a lot of listeners here, if they want to learn more about hemlane, what's the best way for them to do that?   Dana Dunford  37:26   Yeah, you can go to www.hemlane.com We've everything from free packages to manage your properties to much more full service, comprehensive with that repair coordination we spoke about just please do mention this interview slash podcast, specifically Keith and GRE and you will get 20% off your first year there. So please do make sure to mention it.   Keith Weinhold  37:50   Oh, thank you for doing that for our listeners. Dana Dunford, it's been valuable as I knew it would be. Thanks so much for coming onto the show.   Dana Dunford  37:57   Great. Thanks so much for having me.   Keith Weinhold  38:02   You Brenda, how much does it cost for an investor to use hemlane? Well, there's a free software package where you don't have to leave a credit card or anything like Dana mentioned. Their website will show you that monthly. There are a few packages and fee schedules, but they all have 14 day free trials too. Now, if you use a professional manager, it's less likely that hemlane can help you. If you self manage, you can book a free demo right there from the top of their homepage. It's really easy to find. They can help you with tenant screening, background and credit checks, listing, syndication, online rent collection, tracking rent payments, late fees, and they've got dashboards for lease and tenant status, also everything to do with streamlining maintenance requests, work orders and some of the logistics of your repair coordination, H, E, M, L, A, N, E, hemlane.com, you might like the demo. You can mention GRE for 20% off your first year. That is kind of Dana to do that for us until next week, when I'll be back to help you build your wealth. I'm your host. Keith Weinhold, don't quit your Daydream.   Speaker 2  39:20   Nothing on this show should be considered specific, personal or professional advice. Please consult an appropriate tax, legal, real estate, financial or business professional for individualized advice. Opinions of guests are their own. Information is not guaranteed. All investment strategies have the potential for profit or loss. The host is operating on behalf of get rich Education LLC, exclusively   Speaker 3  39:40   The preceding program was brought to you by your home for wealth building, get richeducation.com Transcribed by https://otter.ai

In this special episode of Cloud Wars Live, Bob Evans speaks with Chad Wahlquist, Architect at Palantir, about the company's explosive Q3 growth and the accelerating adoption of its AI Platform (AIP). They explore how AIP serves as an operating system for the enterprise, enabling customers to achieve global optimization, faster ROI, and model flexibility. Wahlquist also talks about Palantir's open, interoperable architecture and its commitment to delivering value at speed, especially for customers in high-stakes, high-pressure environments.Operate Smarter, Not SlowerThe Big Themes:Speed to Value: Many companies still operate under the assumption that meaningful transformation requires multi‑year timelines (two to three years, sometimes more). Palantir is pushing the idea that you must deliver value in months, three to six months, rather than years. This shift is critical because when business markets move fast, and when competitive advantage erodes quickly, speed becomes a differentiator. If you wait for years, you may miss the window or be out‑paced.Interoperability and Ecosystem Integration: The platform isn't trying to lock you into a “box” you must keep your data in; it instead emphasizes plug‑in interoperability with systems you already have. Wahlquist mentions connectors, SDKs, APIs, and plug‑ins to partners like Snowflake, Databricks, SAP, NVIDIA. The concept: if you already have investment in some systems, don't throw them away; just connect them. This increases the speed to value and reduces friction.Ambition, Willingness to Operate in Crisis: Wahlquist points out they often engage with customers who are under pressure. These customers need value now, not two or three years out. Situations like supply chain disruption, plant outages, labor issues, etc., are real. This situational urgency forces companies to adopt architectures and partners that can deliver now. The takeaway: It's not enough to believe you'll transform in the future; transformation architecture must be built for today's fires.The Big Quote: “Our goal is really: how do we scale our customers and the outcomes they're delivering — not just the number of customers?"More from Chad and Palantir:Follow Chad on LinkedIn or get an overview of Palantir's Q3 in its letter to shareholders. Visit Cloud Wars for more.

As promised last week, today's episode provides greater context on US ePrivacy audits, CIPA/VPPA claims, and EU-US comparative law as it affects the rollout or maintenance of MarTech solutions on websites and mobile applications.References:* “The slippery slope of consent banners in preventing CIPA and VPPA claims: why effective Opt-Outs will prevail - also in the EU” (Sergio Maldonado, November 2025 - you are listening to Part I of the more comprehensive analysis)* Jennifer Oliver: privacy litigation over pixels, trackers, and cookies (Masters of Privacy, August 2025)* From wiretapping and video rentals to website pixels, SDKs, and APIs. CIPA/VPPA litigation, risk management, and practical strategies (Nov 2025 update)* Toolbox: Fast CIPA/VPPA website auditing and case law matching for legal professionals (Alpha release). This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mastersofprivacy.com/subscribe

In this episode, Frank Sohn talks with Hiren Shah, founder of B2B-Matrix, about how small and mid-sized manufacturers and distributors are modernizing their sales processes through AI-driven CPQ, CRM, and ERP integration. Hiren, a former SAP America consultant turned Salesforce expert, shares his perspective on the future of Configure-Price-Quote (CPQ), Revenue Cloud, and AI in sales automation. He explains B2B-Matrix's three-phase Salesforce AI project, where automation is already reducing clicks, quote times, and approval delays—and how the final phase will connect directly to ERP and internet data. You'll also hear his insights on: When and why companies should migrate from Salesforce CPQ to Revenue Cloud Advanced (RCA) The "death of middleware" and how modern APIs enable seamless CRM-CPQ-ERP integration The top three customer priorities today: AI, master data cleanup, and faster transaction velocity Why CPQ customers typically replace systems every eight years How B2B-Matrix white-labels its services for larger consulting firms and delivers sub-$100K CPQ projects for SMBs Beyond business, Hiren also shares his personal passion for Pilates and Hot Yoga, a balance that keeps him focused as he leads digital transformation projects for manufacturers across North America. Whether you're interested in Salesforce Revenue Cloud, CPQ modernization, AI in sales, or integration strategy, this episode offers practical, real-world insights from someone who's bridging enterprise architecture, business process design, and cloud innovation.

SHOW: 975SHOW TRANSCRIPT: The Cloudcast #975 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:LaunchAny websiteapicoach.io (note)Lessons learned after a decade of API StrategyLatest book: “Principles of Web API Design: Delivering Value with APIs and Microservices (Addison-Wesley under the Vaughn Vernon signature series)Upcoming report on AI-Assisted API DesignJames on The Cloudcast #153James on The Cloudcast #435Topic 1 - Welcome back to the show James. It's hard to believe it's been 11 years since we last spoke on the show! Give everyone a brief introduction.Topic 2 - To say we've come a long way with APIs as an industry is an understatement. But let's set the table for everyone. In your interactions with Enterprise customers, what trends or standards are currently top of mind? Topic 3 - You wrote an article (link in show notes) titled Lessons after a Decade of API Strategy. What struck me from the article was the combination of technology, business, and even culture, all of which have to come together. When talking to Enterprises these days, have we moved past understanding what APIs are and straight to solving problems with APIs?Topic 4 - What are the most common use cases you see today? API transformation? API sprawl and consolidation/documentation? Integration of SaaS/3rd party services?Topic 5 - No conversation would be complete without a discussion about AI and AI's impact on API's. I view this in several different ways. AI is creating APIs, and AI is being consumed through APIs. How do you think about AI and its impact? What's changed and what has stayed the same?Topic 6 - Second aspect to the AI topic, where and how does security fit into this intersection of AI and APIs?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

It's hump day on WHAT THE TRUCK?!? and host Malcolm Harris is bringing the heat with a jam-packed lineup covering innovation, strategy, and the latest headlines shaking up logistics. In this episode: Arthur Axelrad, CEO & Co-Founder of Dispatch Science, breaks down the launch of DataSync — the newest part of their DSX ecosystem giving carriers real-time control and visibility over operations. Discover how data is reshaping last-mile logistics and why modern architecture and APIs are key to the future. Sarah Olmstead (President, Rebel Logistics Service) and Mike Holland (Senior Director of Domestic Logistics, Five Below) join forces to dive into the ECA Marketplace — the unique “speed dating for logistics” event where shippers and carriers forge real partnerships and optimize freight strategy for 2026. Freight headlines on CDL rule reversals, Zoom Freight's bankruptcy, and U.S. port fee suspensions on Chinese vessels. Plus, Malcolm previews: ProShip's 2025 End-of-Year Parcel Roast — where shipping strategies get roasted live The Great Freight Debate featuring Craig Fuller, Ken Adamo, and Matthew “The Armchair Attorney” Leffler, live from the Traffic Club of Chicago ⁠Watch on YouTube⁠ ⁠Visit our sponsor⁠ ⁠Subscribe to the WTT newsletter⁠ ⁠Apple Podcasts⁠ ⁠Spotify⁠ ⁠More FreightWaves Podcasts⁠ #WHATTHETRUCK #FreightNews #supplychain Learn more about your ad choices. Visit megaphone.fm/adchoices

When four MIT grads decided to build a code editor while everyone else was building AI agents, they created the fastest-growing developer tool ever built. Cursor CEO Michael Truell joins a16z's Martin Casado to discuss the deliberate constraints that led to breakthroughs: why they rejected the "democratization" narrative to focus on power users, how their 2-day work trials test for agency over credentials, and the strategic decision to own the editor when conventional wisdom said it was impossible. Resources:Follow Michael on X: https://x.com/mntruell Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.