Podcasts about API

In this episode, I'm thrilled to welcome back Duncan Clark from Flourish and Canva to talk about the incredible evolution of both tools over the past few years. We dig into how the Flourish and Canva teams have grown, how they now collaborate, and what that means for users who care about data visualization, storytelling, and workflow. Duncan walks through major updates—including the new Start With Data feature, expanded enterprise security options, and deeper presentation-focused capabilities. We also explore long-standing user requests, dashboarding, and how AI may soon accelerate data-viz workflows. It's a wide-ranging and deeply insightful conversation for anyone who uses—or teaches—data visualization.Keywords: Flourish, Canva, Duncan Clark, data visualization, data storytelling, interactive graphics, data design, data tools, newsroom visualization, enterprise data security, Start With Data, presentations, dashboards, API visualization, data workflows, information design, PolicyViz PodcastSubscribe to the PolicyViz Podcast wherever you get your podcasts.Become a patron of the PolicyViz Podcast for as little as a buck a monthCheck our FlourishFollow me on Instagram, LinkedIn, Substack, Twitter, Website, YouTubeEmail: jon@policyviz.com

In "Why It's Time to Expect More from Your EDI Platform", Joe Lynch and Shane Hagen, Presales Solutions Architect at Cleo, discuss the necessity of transitioning from traditional EDI to a unified platform for strategic supply chain orchestration and superior visibility. About Shane Hagen Shane Hagen is a Presales Solutions Architect at Cleo. He designs integration solutions that seamlessly connect internal applications with external partners, leveraging both API and EDI integration patterns. Cleo's customers rely on Shane to solve complex supply-chain challenges, trusting him to bridge the gap between business objectives and technical execution. With over eight years of experience in the integration space—including a prior role at Boomi—Shane brings deep expertise in modern connectivity and enterprise workflow design. He holds a computer science degree from Penn State University. About Cleo Cleo Integration Cloud (CIC) is a cloud-based integration platform, that allows organizations to build, operate, and optimize critical supply chain orchestration processes. The CIC platform brings end-to-end integration visibility across API, EDI, and non-EDI integrations, giving technical and business users the confidence to rapidly onboard trading partners, enable integration between applications, and accelerate revenue-generation. As a supply chain orchestration software company focused on business outcomes, Cleo's focus is to ensure each customer's potential is realized by delivering strategic solutions that make it easy to discover and create value through the movement and integration of B2B enterprise data. Key Takeaways: Why It's Time to Expect More from Your EDI Platform In "Why It's Time to Expect More from Your EDI Platform", Joe Lynch and Shane Hagen, Presales Solutions Architect at Cleo, discuss the necessity of transitioning from traditional EDI to a unified platform for strategic supply chain orchestration and superior visibility. The Imperative for Seamless System Connectivity The penalty for not connecting internal systems directly to external business partners is severe: it forces manual entry, leading to processes that are time-consuming, slow, unreliable, and prone to error. Organizations must expect their EDI platform to eliminate this manual burden and ensure robust, automated data exchange. Shift from Transaction Processing to Supply Chain Orchestration Expect your platform to evolve beyond simple data exchange to become a strategic tool for supply chain orchestration. Modern cloud platforms, like Cleo Integration Cloud (CIC), manage, operate, and optimize critical B2B enterprise data movement across the entire network, driving strategic business outcomes. Enabling Profitable Partner Relationships Through Speed Working with a powerful integration platform like Cleo is the key to accelerating growth. It directly enables companies to onboard new customers, suppliers, and business partners significantly faster, which is foundational to building more prosperous, high-velocity relationships. Hybrid Integration is the New Standard (API + EDI) The complexities of the modern supply chain require integration solutions that seamlessly blend traditional EDI with contemporary API patterns. A high-value platform must provide a unified environment for designing complex, end-to-end workflows that leverage both types of connectivity. Comprehensive Visibility Across All Data Streams True operational control requires end-to-end integration visibility across every data flow—API, EDI, and non-EDI. This holistic view gives technical and business users the confidence to solve complex supply-chain challenges by quickly identifying and resolving any bottlenecks. Bridging the Gap Between Business Strategy and Technical Execution A modern EDI platform must act as the essential link between ambitious business objectives (like accelerated revenue and growth) and the technical execution required to meet them. Guest experts, like Shane Hagen, are relied upon to translate complex requirements into measurable business value. Strategic Partnerships Drive Industry Focus (The Trimble Example) Expect your integration provider to have deep, strategic alliances within key industries. Cleo's position as a proud Trimble partner highlights its experience in solving complex integration challenges for Trimble customers and demonstrates its specialized focus on critical industry ecosystems. Learn More About Why It's Time to Expect More from Your EDI Platform Shane Hagen Cleo | Linkedin Cleo Demo Case Studies The Logistics of Logistics Podcast If you enjoy the podcast, please leave a positive review, subscribe, and share it with your friends and colleagues. The Logistics of Logistics Podcast: Google, Apple, Castbox, Spotify, Stitcher, PlayerFM, Tunein, Podbean, Owltail, Libsyn, Overcast Check out The Logistics of Logistics on Youtube

In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.For for more information about Cybersecurity Cares, visit cybersecurity-cares.comReact2Shell is the latest high-profile vulnerability in the web application landscape, scoring a critical CVSS 10.0 and drawing immediate comparisons to Log4Shell.Researchers at Noma Labs disclosed a critical vulnerability in Google's Gemini Enterprise AI assistant, dubbed GeminiJack, that allowed attackers to stealthily exfiltrate sensitive enterprise data.U.S. prosecutors have charged Victoria Eduardovna Dubranova, a 33‑year‑old Ukrainian woman, in two separate indictments for her alleged involvement with pro‑Russia hacktivist groups CyberArmyofRussia_Reborn and NoName057(16).A China-aligned threat actor identified as Warp Panda has been linked to recent compromises of VMware vCenter environments at U.S.-based organizations, according to a new report from CrowdStrike. Original CrowdStrike article. CISA BRICKSTORM Backdoor breakdown. Analysis report.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

Kebakaran terjadi di Kawasan Pasar Induk Kramat Jati, Jakarta Timur, pada pagi hari ini. Api diketahui melalap sejumlah los pedagang yang diduga berada di area los buah. Hingga saat ini, petugas pemadam kebakaran masih berupaya melakukan pendinginan di lokasi.Informasi terkini sudah terhubung dengan Jurnalis Metro TV, Satrio Adi langsung dari Pasar Induk Kramat Jati, Jakarta Timur.

We dig into how AI changes the risk surface for banks and fintechs and why identity must be designed from the start. Sutton Maxwell of Curity shares how to set API guardrails, balance friction with trust, and choose hybrid architectures that meet regulation without killing speed.• What Curity does for API security and identity• Why AI pilots fail without early security design• Common mistakes when teams bolt on controls late• How to balance UX with risk‑based friction• US speed vs EU regulation on AI adoption• Hybrid, multi‑cloud, and cloud exit strategies• Practical advice for fintech founders on KYC, OAuth, OIDC• Turning compliance into a growth advantageTo connect and keep up to date with all the latest, head over to www.jointheconnector.com or hit subscribe via your podcast streaming platformThank you for tuning into our podcast about global trends in the FinTech industry.Check out our podcast channel.Learn more about The Connector. Follow us on LinkedIn.CheersKoen Vanderhoydonkkoen.vanderhoydonk@jointheconnector.com#FinTech #RegTech #Scaleup #WealthTech

We explore with Alexander from Solanteq, what makes a payments platform truly modern: cloud-native, modular, API-first, and regulation-ready, with the ability to scale from small pilots to global volume. We share a vision for “payment autopilot” and how multi-rail orchestration and AI can make payments feel invisible.• Cloud-native, modular architecture for issuing, acquiring and settlement• API-first integration with legacy and new systems• Compliance by design and predictable audits• Data streaming for analytics and added-value services• Managing legacy tails while moving to future rails• Multi-rail strategy for cross-border and instant payments• Payment orchestration across simple and complex flows• Practical roles for AI in risk, routing and efficiency• Vision for a consumer and merchant “payment autopilot”• How to contact the team to start modernisingTo connect and keep up tonight with all the latest, head over to www.join theconnector.com or hit the client on your podcast orThank you for tuning into our podcast about global trends in the FinTech industry.Check out our podcast channel.Learn more about The Connector. Follow us on LinkedIn.CheersKoen Vanderhoydonkkoen.vanderhoydonk@jointheconnector.com#FinTech #RegTech #Scaleup #WealthTech

Thiago Barbosa, partner at Salles Nogueira Advogados, joins host Aaron Stanley to break down the complex and rapidly evolving landscape of crypto asset taxation and regulation in Brazil. The discussion centers on the latest major developments from the Central Bank, which is introducing stricter requirements for Virtual Asset Service Providers, and the new Receita Federal reporting mechanism called "Decripto". Barbosa explains how these changes create an increasingly tight compliance net, particularly for retail investors who've historically operated in gray areas. He emphasizes that the IRS is investing heavily in surveillance technology to identify discrepancies between reported income and actual lifestyle spending, warning that the window for undeclared crypto wealth is rapidly closing as Brazil integrates into the global tax reporting infrastructure.You can connect with Thiago on Linkedin and Instagram------------------------------------------------------------------Brazil Crypto Report is presented by AveniaIf you're building a wallet, a crypto consumer app, or a global payment platform, Avenia is your bridge to Latin America. Instantly connect to PIX, SPEI, and CBU using stablecoins — with one API. No banks. No FX desks. No SWIFT. Move money globally, with full compliance and real-time settlement. Learn more at ⁠⁠⁠⁠⁠⁠avenia.io⁠⁠⁠⁠⁠⁠.------------------------------------------------------------------Figment is the leading independent provider of staking infrastructure with $18B assets under stake and provides the complete solution for over 1000 institutional clients in Latin America and globally. Through its enterprise-grade infrastructure, Figment enables clients such as banks and exchanges, to earn rewards on Proof-of-Stake assets such as Ethereum and Solana, while maintaining the highest standards of security, compliance, and performance.Learn more at ⁠⁠⁠⁠figment.io⁠⁠⁠⁠-------------------------------------------------------------------

https://www.otplinks.com 0:00 Welcome & today's focus: Retatrutide and “chasing the biggest number” 1:11 On The Pen intro, live schedule (Mon/Wed/Fri) & housekeeping 2:10 How Dave first heard about retatrutide (work trip, early phase 1 data) 3:35 Flashback clip: early excitement about retatrutide phase 3 trials 4:40 Why this new retatrutide data feels different for obesity medicine 5:32 TRIUMPH-4 trial overview: obesity + knee osteoarthritis population 7:00 Headline results: 28.7% average weight loss, surgery-level efficacy 8:47 Breaking down weight loss by dose (9 mg vs 12 mg; 25–35% loss rates) 11:05 What “efficacy estimate” really means (race-track analogy) 13:28 Real-world view: treatment-regimen estimate (20–23.7%) vs trial ideal 15:40 Mechanism refresher: GIP, GLP-1, glucagon and why RETA differs from TIRZ 18:05 Side effects, dysesthesia/allodynia & who stopped treatment (BMI differences) 21:02 Why the lower doses matter & who actually needs 30% weight loss 24:15 From “just make the scale go down” to quality of weight loss & body composition 28:05 Future focus: health, longevity, and peptides beyond hitting goal weight 30:40 Viewer Q&A: combining RETA + TIRZ, amylin (eloralintide) combos & “talk to your doctor” 34:38 How retatrutide changes the next decade of obesity treatment conversations 37:22 News update: high-dose Wegovy 7.2 mg approval in the EU & US outlook 40:55 Orforglipron oral GLP-1: liver-signal concerns & fast-track FDA review 45:20 Why small-molecule oral GLP-1s aren't the same as injectable peptides 48:40 New topic: Indiana “Safe Drug Act of 2025” and why Dave is concerned 51:02 Production caps, “essentially a copy” language & shifting power from prescribers to FDA 54:28 How the bill undermines personalization while ignoring real safety tools 57:05 Safety theater vs real safeguards: API sourcing, sterility & adverse-event reporting 59:45 Who actually gets hit: compliant 503A/503B compounders vs existing bad actors 1:02:05 Call to action: petition at otplinks.com & why patient voices matter 1:05:10 Change.org impact, media attention & centering the patient perspective 1:07:30 Final Q&A, subscribe, obesity.news email list & closing thanks Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

People often ask what I'm actually building with AI all day. In this episode, I break down the 6 active projects I'm coding right now to automate my work and save money:The QuickBooks Killer: Replacing a $30/month subscription with a custom Python & Plaid script for automated tax reporting.Content Agent: Automatically converting podcast audio into a written Substack newsletter.Voice-First Trading Journal: A system to log trading results and tax liabilities verbally into a secure database.Global Earnings Tracker: Monitoring earnings revisions across US and global markets.The Buffett Scan: An automated scanner finding stocks that meet Warren Buffett's investing criteria.Yutori Scouts: Using a new navigator API to dig up better market intel than Google News.

Palabras clave: iPadOS 26.2, Windows 11, Fallos de sistema, Multitarea, API, Migración de servicios ### Problemas con iPadOS 26.2 ### Críticas al Desarrollo de Software ### Experiencia con Windows 11 y Surface Pro ### Plan de Migración de Servicios

OpenAI GPT-5.2 is here! The new model shows improvements, but the bigger news might be the deal Sam Altman made with Disney to bring characters to Sora. We dive into the implications for AI & Hollywood, plus Google's Deep Research & Android XR, Runway Gen-4.5, Gemini 2.5, & WAY more AI News. HARSH, THE GUARDRAILS WILL BE. FUN, YOU MIGHT STILL HAVE. Get notified when AndThen launches: https://andthen.chat/ Come to our Discord to try our Secret Project: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // OpenAI's GPT-5.2 https://openai.com/index/introducing-gpt-5-2/ Disney OpenAI Deal For Sora & Investment https://openai.com/index/disney-sora-agreement/ https://www.wsj.com/business/media/disney-to-invest-1-billion-in-openai-license-characters-for-use-in-chatgpt-sora-3a4916e2?st=y8EdTr&reflink=article_copyURL_share Bob Iger Talks Deal on CNBC https://x.com/MorePerfectUS/status/1999162796966051953?s=20 Cease & Desist letter sent to Google day before this deal https://www.wsj.com/business/media/disney-to-invest-1-billion-in-openai-license-characters-for-use-in-chatgpt-sora-3a4916e2?st=d74Bcx&reflink=desktopwebshare_permalink Google's New AR XREAL Android Glasses (Demo starts at 12:19) https://www.youtube.com/live/a9xPC_FoaG0?si=7X4wC-x3lTu18WYk&t=739 Google Deep Research Agent (in API) https://blog.google/technology/developers/deep-research-agent-gemini-api New Updates To Google Gemini 2.5 Flash Audio https://x.com/googleaidevs/status/1998874506912538787?s=20 Runway 4.5 Launches + Lots Of New Stuff https://www.youtube.com/live/OnXu-6xecxM?si=YIzZO5egj4m_SJgV Gavin's First Runway 4.5 Output https://x.com/gavinpurcell/status/1999171408979509322?s=20 Design Within Cursor Now https://x.com/cursor_ai/status/1999147953609736464?s=20 Glif's Agent Getting Really Good https://x.com/heyglif/status/1998493507615600696?s=20 Gavin's 'fashion' shoot with GLIF Agent https://x.com/gavinpurcell/status/1998560308873527454?s=20 McDonald's Pulls AI Ad After Getting Dragged Across The Coals https://futurism.com/artificial-intelligence/mcdonalds-ai-generated-commercial Video of the T-800 From Last Week Kicking Their CEO https://x.com/CyberRobooo/status/1997290129506148654?s=20 Nano Banana Pro Five Minutes Earlier / One Hour Later / Ten Hours Later Prompt https://x.com/gizakdag/status/1998501408098668983?s=20 Making Crowds In of Famous Images https://www.reddit.com/r/aiArt/comments/1pifspt/crowded/ Duck Season / Rabbit Season By lkcampbell in our Discord https://sora.chatgpt.com/p/s_6936b1cadd008191b1042ff7f0bb913f  

Join us for this week's Defender Fridays as we explore the reality of AI-powered malware threats with Randy Pargman, Senior Director of Threat Detection at Proofpoint.At Defender Fridays, we delve into the dynamic world of information security, exploring its defensive side with seasoned professionals from across the industry. Our aim is simple yet ambitious: to foster a collaborative space where ideas flow freely, experiences are shared, and knowledge expands.In this episode, Randy challenges the hype around AI-powered polymorphic malware and examines how threat actors actually operate in practice. He discusses why defenders should focus on real-world threats rather than theoretical sophisticated attacks.Key Topics:The gap between AI malware hype and practical realityWhy threat actors prefer simple, effective methods over sophisticated techniquesThe prevalence of legitimate RMM tools in modern attacksBuilding practical detection strategies for actual threatsLessons from physical security that apply to cybersecurity defenseRandy Pargman is Senior Director of Threat Detection at Proofpoint, where he leads detection engineering, sandbox development, and threat actor tracking initiatives. Join us every Friday at 10:30am PT for live, interactive discussions with industry experts. Whether you're a seasoned professional or just curious about the field, these sessions offer an engaging dialogue between our guests, hosts, and you – our audience. Register here: https://limacharlie.io/defender-fridaysSubscribe to our YouTube channel and hit the notification bell to never miss a live session or catch up on past episodes on our website!This episode is brought to you by LimaCharlie, the world's first SecOps Cloud Platform (SCP). Build and customize your security stack like "lego blocks" with our flexible, API-first solution.Eliminate vendor sprawl and tool complexityDeploy and scale effortlessly on native multi-tenant architectureReduce costs with intelligent data routing and free 1-year retentionBuild custom solutions with 100+ security capabilities on-demandImprove response times with automation and real-time capabilitiesTry the SecOps Cloud Platform free: https://limacharlie.ioHost: Maxime Lamothe-Brassard - Founder at LimaCharlie

Terry McLean, co-founder and CEO of SageSure, joins FNO: InsureTech for a detailed look at SageSure's beginnings, the company's focus on coastal and catastrophe-exposed property, and their disciplined approach to underwriting. McLean outlines SageSure's path from its first policy in 2009 to a multi-state, multi-billion dollar business, discusses recent acquisitions, and describes the company's approach to technology and culture based on observable behaviors. The conversation covers the practical factors that have shaped SageSure's strategy in challenging markets, quoting directly from McLean's experience and the company's evolution. Key Highlights The inception of SageSure based on the recognition of permanent dislocation in coastal property markets, and the pursuit of serving preferred but underserved customers by underwriting risk with discipline and care. SageSure's focus on gradual, organic growth, prioritizing profitability for carrier partners through comprehensive underwriting, including inspection of every home insured. Insights into the rationale behind entering catastrophe-prone markets that others avoided, and the business model built around pricing accurately for risk. Exploration of SageSure's acquisitions of GeoVera and Olympus, including the specific "carrier bifurcation" strategy used in these deals and the multi-year process of integrating technology and teams. Overview of investments in proprietary technology to deliver what McLean calls a "market leading buying experience" for producers, including API-driven integration and continuous improvement based on producer feedback. Explanation of SageSure's internal culture, highlighting "behaviors we value"—namely, "We Are Fountains," "We Run Down the Hall," and "We Don't Try"—and their origin and impact on daily interactions. The background behind the SageSure name and branding transition from Coastal Risk Underwriters.

Sorare just made a big announcement: its platform is now open to builders.On today's stream, I'll break down what “open Sorare” actually means in practice, not just the marketing language. We'll talk about:• What Sorare opening its API and Solana stack enables• The types of tools, games, and products Sorare is encouraging• How this could impact third-party tools, analytics, and scouting• What it means for managers, collectors, and the broader Sorare ecosystem• The opportunities and the risks of a more open platformThis could be a major inflection point for Sorare, depending on how it's executed. Let's dig into it.

Les géants de l'intelligence artificielle préparent un protocole universel pour permettre aux IA d'interagir avec tous les services numériques sans intégration spécifique.Un langage commun pour les agents intelligentsLes intelligences artificielles peinent aujourd'hui à agir efficacement dans un monde numérique fragmenté. Chaque outil ou service utilise sa propre API, ses propres règles d'interaction. Pour qu'un agent IA exécute une tâche concrète, il doit apprendre à dialoguer avec une multitude de systèmes hétérogènes. C'est à ce problème que répond MCP, le Model Context Protocol, conçu comme un langage universel entre IA et outils numériques.Une initiative d'Anthropic, soutenue par la Linux FoundationCréé en 2024 par deux ingénieurs d'Anthropic, David Soriapara et Justin Sparsomers, MCP vient de franchir une étape décisive : son passage sous l'égide de la Linux Foundation, via une nouvelle entité baptisée Agentic AI Foundation. L'objectif est clair : faire de MCP un standard ouvert, neutre et interopérable, comme l'a été Linux pour les systèmes d'exploitation. Cette fondation assurera la gouvernance, la documentation et la diffusion du protocole.Une architecture en trois couches pour un fonctionnement transparentLe fonctionnement de MCP repose sur une structure en trois éléments : l'agent IA qui formule une demande, le serveur MCP qui traduit cette demande en actions possibles, et l'outil compatible qui exécute l'action. Chaque service numérique déclare ses fonctions, permissions et formats, tandis que l'utilisateur garde la main sur les autorisations. Le protocole agit comme une API universelle, une « grammaire » commune pour permettre aux IA de manipuler n'importe quel outil numérique.Vers une nouvelle ère d'interopérabilité pour l'IALe développement de MCP s'accélère. OpenAI l'intègre dans ChatGPT, Google déploie ses propres serveurs compatibles, et une communauté de développeurs se constitue autour du standard. MCP n'est plus un simple prototype : il amorce son industrialisation. À terme, chaque service numérique pourrait devenir plug and play pour les IA. Une révolution silencieuse, mais potentiellement majeure, dans l'architecture du web intelligent.Site officiel MCP-----------♥️ Soutien : https://mondenumerique.info/don

In this episode of the Wharton FinTech Podcast, host Meaghan McGowan sits down with Mike Yu, CEO and Co-founder of Vesta, to explore the modernization of the mortgage technology stack. Mike shares Vesta's origin story and how he and his team are rebuilding the loan origination system to be flexible, automated, and API-first. The episode explores: - How modern workflows, partner integrations, and recent developments, including Vesta's partnership with Pennymac, are reshaping lender operations - Macro trends, the growing role of AI, and how lenders are rethinking their technology stacks - The future of “self-driving” origination, and - Advice for founders building in regulated financial infrastructure

Eytan Seidman, VP of product at Shopify, joins the podcast to unpack Shopify's Winter '26 Edition and how AI is emerging into the market for developers and merchants. They discuss the new Dev MCP server, showing how tools like Cursor and Claude Desktop can rapidly scaffold Shopify apps, wire up Shopify functions, and ship payment customization and checkout UI extension experiences that lean on Shopify primitives like meta fields and meta objects across online stores and point of sale. Eytan also breaks down how Sidekick connects with apps, why the new analytics API and ShopifyQL open fresh analytics use cases, and more. Links Shopify Winter '26 Edition: https://www.shopify.com/editions/winter2026 We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Fill out our listener survey (https://t.co/oKVAEXipxu)! https://t.co/oKVAEXipxu Let us know by sending an email to our producer, Elizabeth, at elizabeth.becz@logrocket.com (mailto:elizabeth.becz@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Check out our newsletter (https://blog.logrocket.com/the-replay-newsletter/)! https://blog.logrocket.com/the-replay-newsletter/ Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Chapters 01:00 — AI as the Focus of Winter '26 02:00 — MCP Server as the Ideal Dev Workflow 03:00 — Best Clients for MCP (Cursor, Claude Desktop) 04:00 — Hallucinations & Code Validation in MCP 06:00 — Developer Judgment & Platform Primitives 07:00 — Storage Choices: Meta Fields vs External Storage 09:00 — Learning UI Patterns Through MCP 10:00 — Sidekick Overview & Merchant Automation 11:00 — Apps Inside Sidekick: Data & UI Integration 13:00 — Scopes, Data Access & Developer Responsibility 14:00 — AI-Ready Platform & Explosion of New Apps 16:00 — New Developer Demographics Entering Shopify 17:00 — Where Indie Devs Should Focus (POS, Analytics) 18:00 — New Analytics API & Opportunities 19:00 — Full Platform Coverage via MCP Tools 20:00 — Building Complete Apps in Minutes 21:00 — Large Stores, Token Limits & MCP Scaling 22:00 — Reducing Errors with UI & Function Testing 23:00 — Lessons from Building the MCP Server 25:00 — Lowering Barriers for Non-Experts 26:00 — High-Quality Rust Functions via MCP 27:00 — MCP Spec Adoption: Tools Over Resources 28:00 — Future: Speed, Quality & UI Precision 29:00 — Model Evolution, Evals & Reliability 31:00 — Core Shopify Primitives to Build On 33:00 — Docs, Community & Learning Resources

Hi, Spring fans! Welcome to another installment of a Bootiful Podcast! In this installment I talk to the legendary Rossen Stoyanchev on API versioning, declarative interface clients, RestTestClients, and more!

professorjrod@gmail.comIn this episode of Technology Tap: CompTIA Study Guide, we dive deep into cloud security fundamentals, perfect for those preparing for the CompTIA Security+ exam. Join our study group as we explore the shifting security landscape from locked server rooms to identity-based perimeters and data distributed across regions. This practical, Security+-ready guide connects architecture choices to real risks and concrete defenses, offering valuable IT certification tips and tech exam prep strategies. Whether you're focused on your CompTIA exam or looking to enhance your IT skills development, this episode provides essential insights to help you succeed in technology education and advance your career.We start by grounding the why: elasticity, pay-per-use costs, and resilience pushed organizations toward public, private, community, and hybrid clouds. From there, we map service models—SaaS, PaaS, IaaS, and XaaS—and the responsibilities each one assigns. You'll hear how thin clients reduce device risk, why a transit gateway can become a blast radius, and where serverless trims surface area while complicating visibility. Misunderstanding the shared responsibility model remains the leading cause of breaches, so we spell out exactly what providers secure and what you must own.Identity becomes the new perimeter, so we detail IAM guardrails: least privilege, no shared admins, MFA on every privileged account, short-lived credentials, and continuous auditing. We cover encryption in all three states with AES-256, TLS 1.3, HSMs, and customer-managed keys, then add CASB for SaaS control and SASE to bring ZTNA, FWaaS, and DLP to the edge where users actually work. Virtualization and containers deliver speed and density but expand the attack surface: VM escapes, snapshot theft, and poisoned images require hardened hypervisors, signed artifacts, private registries, secret management, and runtime policy. Hybrid and multi-cloud introduce inconsistent IAM and fragmented logging—centralized identity, unified SIEM, CSPM, and infrastructure-as-code guardrails bring discipline back.We wrap with the patterns attackers exploit—public storage exposure, stolen API keys, unencrypted backups, and supply chain compromises—and the operating principles that stop them: zero trust, verification over assumption, and automation that responds at machine speed. Stick around for four rapid Security+ practice questions to test your skills and cement the concepts.If this helped you study or sharpen your cloud strategy, follow and subscribe, share it with a teammate, and leave a quick review telling us which control you'll deploy first.Support the showArt By Sarah/DesmondMusic by Joakim KarudLittle chacha ProductionsJuan Rodriguez can be reached atTikTok @ProfessorJrodProfessorJRod@gmail.com@Prof_JRodInstagram ProfessorJRod

Most marketers track their AI visibility… but have no idea what to do next.This episode shows the exact GEO strategy to actually increase your mentions in ChatGPT and Perplexity.In this episode, we show you exactly how to implement GEO (Generative Engine Optimization) the strategy brands are using to increase their mentions inside LLM answers.You'll learn:Why most AI rank trackers are inaccurate and how we rebuilt Tracker to scrape real results (not API hallucinations)How to turn visibility data into action — what content to publish, what topics to prioritize, and where your gaps really areThe GEO Pyramid and why 90% of marketers focus on the wrong tacticsHow to find the exact pages LLMs are citing — and how to influence them with targeted content and outreachWhy you MUST choose bottom-of-funnel topics if you want actual pipeline from AIA step-by-step walkthrough of improving visibility for a real company using owned content + targeted citation outreachIf you want a clear, repeatable strategy for ranking in ChatGPT, Perplexity, and Google AI Overviews, this episode breaks it down.

Capabilities? Through the roof? Usage? Ground floor.Claude Agent Skills might be one of the most useful features of any front-end LLM. Yet....it's crickets in terms of chat around it. For this 'AI at Work on Wednesday' episode, we're breaking it down for beginners and will have you spinning up your own Claude Agent Skills in no time. Claude Skills: How to build Custom Agentic Abilities for beginners -- An Everyday AI Chat with 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:Claude Skills Agentic Features OverviewDifferences: Claude Skills vs. GPTs vs. GEMSModular Agentic Workflow File StructureStep-by-Step Guide: Building Claude SkillsClaude Skills YAML/Markdown Setup ProcessTesting and Validating Custom Claude SkillsAdvanced Capabilities: Executable Code & Sub-AgentsCommon Troubleshooting for Claude Skills CreationTimestamps:00:00 "Claude Skill Library Unveiled"06:27 "Claude Skills Explained"07:29 Custom GPTs and Gems Explained11:18 Claude Skills vs Projects17:31 "Refining Skill Triggers Effectively"20:17 "Beginner Cloud Skills Best Practices"23:39 "Preferring GPT and Memory Tools"25:54 "Saving Skill File Properly"28:09 Creating Skills on Claude33:43 "Creating AI News Searcher"35:36 Claude Skills Now Available37:39 "Optimizing Claude for Knowledge Tasks"41:05 "Skill Builder Library Access"Keywords:Claude skills, Claude agent skills, custom agentic abilities, large language model, agentic workflows, specialized tasks, coding capabilities, file creation, executable code, skills library, skill builder, skill creator, markdown file, skill.md, folder structure, YAML front matter, composable skills, modular instructions, automation, prompt engineering, skill triggers, skill testing, advanced features, API skill versioning, governance and efficiency,Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Vibe coding is dead simple. Head to AI.Studio/build to create your first app.  Vibe coding is dead simple. Head to AI.Studio/build to create your first app. 

In this episode, Jackson sits down with Jimena, Co-Founder and Co-CEO of Prometeo, to discuss the future of financial infrastructure in Latin America. Jimena shares her journey from tech journalism to entrepreneurship, the inspiration behind building Prometeo, and how the company is creating a unified API layer across the Americas to power open banking, real-time payments, and next-generation financial innovation. In this episode, you'll learn: - How Prometeo became one of LatAm's leading open banking infrastructure platforms - The challenges of building across highly fragmented regulatory and technical environments - Why true financial inclusion requires more than just account access - How real-time payments, cross-border rails, and agentic financial services are reshaping the region - Prometeo's philosophy on trust, cybersecurity, and building long-term infrastructure “legacy”

On this episode of The Cybersecurity Defenders Podcast we speak with Alec Fenton, VP of Security Operations at Foresite Cybersecurity about his journey from SOC analyst to security leader.Alec Fenton is a seasoned Cyber Security professional with over 15 years of extensive experience across many IT domains. With a career spanning more than a decade, Alec has honed his expertise in addressing a broad spectrum of cybersecurity challenges, leveraging his analytical prowess and hands-on approach to leadership.Throughout his career, Alec has navigated the intricate landscape of IT security, working across various sectors including managed service providers and private companies. His tenure as an analyst in the cybersecurity space has not only equipped him with a deep understanding of emerging threats and vulnerabilities but has also shaped his leadership philosophy of "lead from the front."Alec's commitment to excellence and his unwavering dedication to staying ahead of the curve in the ever-evolving field of cybersecurity have earned him recognition as a trusted advisor and thought leader in the industry. When he's not immersed in the world of IT security, Alec enjoys spending time outdoors, and help coach his son's baseball/basketball teams.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform. This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

In this episode Tor and Chet chat with Raluca Saucic and Eugene Yakavets about the new "Bring Your Own Model" feature in Android Studio which allows using other models than Gemini for agent mode, including models from Anthropic,  OpenAI, and more. We also discuss using local models via Ollama and LM Studio. Resources: Use a remote model → https://goo.gle/43N2Z5E Use a local model → https://goo.gle/3Xij27V   Chapters: 0:00 - Intro 0:49 - Bring your own model 4:13 - Bring your own key 7:24 - Anthropic model 13:17- How often do you need to remind the model of the context? 17:40 - Thinking vs planning 20:25 - What happens when the API needs to give multiple answers to a complex question? 24:14 - Supported models 31:18 - Are there any barriers when using a different model? 34:07 - Support for code completion 38:16 - GitHub's relationship with agents 44:35 - Using agents for development 56:36 - Studiobot 57:56 - Wrap up  

This episode of The Dish on Health IT features Denny Brennan, Executive Director of the Massachusetts Health Data Consortium (MHDC), in conversation with host Tony Schueth, CEO of Point-of-Care Partners (POCP), and co-host Ross Martin, MD, Senior Consultant with POCP. Together, they examine how MHDC is translating national interoperability policy into practical, statewide action, specifically around the CMS-0057 rule.After brief introductions, the conversation quickly turns to MHDC's long history and why it matters. Founded in 1978, before the internet, MHDC guided Massachusetts through nearly every major health IT transition: HIPAA, Meaningful Use, ICD-10, and now interoperability and automation. Denny explains that this continuity has created something rare in healthcare: sustained trust across payers, providers, vendors, regulators, and associations. That trust, he notes, is what allows competitors to work through shared infrastructure problems that no single organization could solve on its own.From there, the discussion turns to why the MHDC community chose to coordinate and support members in their CMS-0057 compliance journey, versus just letting each member organization go it alone. Denny emphasizes that while healthcare is regulated federally, it functions locally. Each state has its own mix of insurers, hospital systems, rules, and market pressures. In Massachusetts, where long-standing relationships already exist, MHDC saw an opportunity to move faster, test real workflows, and generate lessons that could inform efforts far beyond the state.The discussion then moved to how work to improve prior authorization became such a high-priority focus. Denny describes how the process has grown into one of the most disruptive administrative burdens for clinicians. Rules vary by plan, criteria change frequently, and the information providers need is often hard to access in real time. The result is defensive behavior. Offices routinely submit prior authorizations “just in case,” often by fax or phone, simply to avoid denials and treatment delays. That inefficiency, he explains, ripples outward by slowing patient care, driving up providers' overhead, and requiring health plans to spend more time and resources processing and reviewing the required PA alongside the unneeded submissions.The financial impact quickly becomes apparent. Denny points to evidence showing that administrative costs consume a massive share of U.S. healthcare spending, with prior authorization playing a meaningful role. If automation is implemented through a neutral, nonprofit infrastructure, MHDC believes there is a much greater chance that savings will flow back into premiums and public program costs rather than being swallowed by inefficiency.Ross adds an important dose of realism. Prior authorization friction, he notes, is not always accidental. In some cases, operational complexity functions as a utilization control mechanism. That creates a built-in tension between access, cost containment, and patient experience, and helps explain why national reform has moved slowly despite widespread frustration.At that point, the conversation shifts from why this is broken to how MHDC is trying to fix it. Denny walks through MHDC's operating model: convene the full ecosystem early and often. In a recent deep-dive session, roughly 60 representatives from health plans, providers, and the state participated in a working session focused on what an automated prior authorization workflow could realistically look like. MHDC brought a draft framework to the table. The community pressure tested it and surfaced workflow conflicts, operational blind spots, and policy misalignments that no single organization could see on its own.That collaborative process, Denny explains, is the real engine behind adoption. When stakeholders help build the solution themselves, implementation becomes a shared commitment rather than a compliance exercise. It also reduces resistance later because decisions are not delivered top-down. They are constructed collectively.The discussion then turns to FHIR adoption and why, while real, progress has taken time. Denny traces the turning point back to the 21st Century Cures Act, which reframed patient access to health data as a legal right and categorized data blocking as a regulatory violation. That policy shift, combined with the growing maturity of API-based interoperability, created the conditions for real-time data exchange to finally move from theory to practice.Ross provides a historical perspective from the standards side. Earlier generations of health data standards were conceptually elegant but extremely difficult to implement consistently. FHIR changed that equation by aligning healthcare data exchange with the same API-driven architecture that supports the modern web. He points to accelerating real-world adoption, particularly from large EHR platforms, as evidence that FHIR has entered a phase of broad, practical deployment.Although pharmacy prior authorization falls outside the formal scope of CMS 0057, Denny makes clear that MHDC could not ignore it. For many physicians, especially in oncology, dermatology, and primary care, PA for prescriptions is far more frequent and far more disruptive than PAs for medical services. If MHDC solved only one side of the problem, much of the daily burden for clinicians would remain unchanged.Pharmacy prior authorization, however, introduces a new level of complexity. PBMs, pharmacists, prescribing systems, payers, and patients are all involved, often across fragmented workflows. Denny explains that the challenge looks less like a pure technology gap and more like an orchestration problem. It is about getting the right information to the right party at the right moment across multiple handoffs.Ross shares insights from the pharmacy PA research work conducted with MHDC and POCP. One of the most striking findings was the massive year-end renewal surge that hits providers every benefit cycle as authorizations tied to prior coverage suddenly expire. He also reflects on a recent national electronic prior authorization roundtable, where deep stakeholder discussion ultimately led most participants to conclude that today's technology alone still is not sufficient to fully solve pharmacy PA. The tools are improving, but the problem remains deeply multi-layered.As the episode winds down, the tone shifts toward practical calls to action.Denny challenges the industry to separate where competition belongs from where collaboration is essential. Contract negotiations may be adversarial by nature, he notes, but interoperability initiatives cannot succeed under the same mindset. Real progress depends on bringing collaboratively minded people into the room. These are people willing to solve shared infrastructure problems even when their organizations compete elsewhere.Ross builds on that message with a longer-term challenge: sustained participation in standards development. Organizations cannot sit back and hope others shape the future on their behalf. Active involvement in national standards organizations is critical. This is not for immediate quarterly returns, but to influence the systems everyone will be required to use in the years ahead.The episode closes with a clear takeaway. MHDC did not wait for perfect conditions. It moved when the pieces were good enough, tested real workflows with real stakeholders, adjusted in the open, and began sharing lessons nationally. In an industry often slowed by fragmentation and risk aversion, this conversation offers a grounded look at what forward motion actually looks like when collaboration, policy, and technology finally align.You can find this and other episodes of The Dish on Health IT wherever you get your podcasts, including Spotify and Healthcare Now Radio. If you found this conversation valuable, share it with a colleague and be sure to subscribe so you never miss an episode. Have an idea for a topic you would like us to cover in future episodes? Fill out the form and tell us about it. Until next time, Health IT is a dish best served hot. 

Sébastien Stormacq d'AWS explique comment une nouvelle génération d'agents IA marque un tournant pour les développeurs. Contrairement aux outils d'appoint sur un poste local, ces agents tournent en continu dans le cloud, conservent une mémoire de long terme et orchestrent des tâches complexes grâce au raisonnement des modèles. Ils analysent des systèmes en production, déclenchent des actions, consultent des API externes et collaborent comme un essaim coordonné. Pour les développeurs, le changement est net : moins de logique à coder, plus d'efficacité, mais aussi une nouvelle discipline autour des garde-fous et des politiques métier.

In this special edition of the Liquid Weekly Podcast, hosts Karl Meisterheim and Taylor Page are joined by Eytan Seidman, VP of Product at Shopify, to discuss the major announcements from Winter Editions '26. Eytan reveals how Shopify is rewiring the platform to be fully AI-native, democratizing access to the Catalog MCP for building agentic shopping experiences, and introducing App Intents for Sidekick, allowing apps to register capabilities that Sidekick can invoke directly from merchant queries.The group also dives deep into the "boring but powerful" platform updates, including massive improvements to Bulk Operations concurrency, advanced filtering and increased limits for Metaobjects, and the shift to server-side rendering for Shopify.dev.Find Eytan Seidman OnlineLinkedIn: / eytanseidman Twitter (X): / eytan Timestamps00:00 Teaser: App Intents & Sidekick Capabilities00:41 Intro & Welcome01:24 Introducing Eytan Seidman, VP of Product at Shopify02:51 High-Level Overview of Winter Editions '26 Updates05:31 AI-Native Platform: Dev Assistant & MCP Server Updates11:57 Technical Deep Dive: Shopify.dev moving to Server-Side Rendering (Remix)16:38 Catalog MCP: Democratizing Agentic Shopping Experiences23:39 App Intents for Sidekick: Registering Tools & Context30:30 Merchant Control & Privacy in Sidekick Extensions39:16 Boring Updates: Bulk Operations Improvements (Concurrency & Mutation Support)42:40 Boring Updates: Metaobjects (Advanced Filtering & Increased Limits)51:13 Eytan's Top 3 Takeaways for Developers54:20 OutroResourcesShopify Editions: https://www.shopify.com/editionsMetaobjects Documentation: https://help.shopify.com/en/manual/cu...Bulk Operations API: https://shopify.dev/docs/api/usage/bu...Model Context Protocol (MCP): https://modelcontextprotocol.io/Dev ChangelogThe hosts and Eytan discuss the following updates from the Winter Editions '26 release:AI-Native Dev Platform: The Dev Assistant and Dev MCP Server now cover the entire platform, including generating Checkout UI Extensions, modifying TOML files, and utilizing the latest Polaris components.Shopify.dev Server-Side Rendering: The documentation site has moved to server-side rendering (using Remix) to improve crawler access and performance for AI agents.Catalog MCP: Developers now have access to the full catalog of products across the merchant base (normalized and searchable) to build agentic shopping experiences.App Intents for Sidekick: Apps can now register "tools" and capabilities that Sidekick can invoke based on natural language merchant queries (e.g., "Show me my recent campaign stats").Bulk Operations Improvements:Now supports all mutations. Concurrency increased to allow up to 5 operations per API client per shop simultaneously.New query to check the status of all running bulk operations.Metaobject Enhancements: Advanced Filtering: Query metaobjects by value ranges on metafields (e.g., filter testimonials by date range). Increased Limits: Separate pools for apps—each app can create up to 128 definitions with up to 1 million entries each.Sign Up for Liquid WeeklyDon't miss out on expert insights and tips—subscribe to Liquid Weekly for more content like this: https://liquidweekly.com/

Topics covered in this episode: PEP 798: Unpacking in Comprehensions Pandas 3.0.0rc0 typos A couple testing topics Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: PEP 798: Unpacking in Comprehensions After careful deliberation, the Python Steering Council is pleased to accept PEP 798 – Unpacking in Comprehensions. Examples [*it for it in its] # list with the concatenation of iterables in 'its' {*it for it in its} # set with the union of iterables in 'its' {**d for d in dicts} # dict with the combination of dicts in 'dicts' (*it for it in its) # generator of the concatenation of iterables in 'its' Also: The Steering Council is happy to unanimously accept “PEP 810, Explicit lazy imports” Brian #2: Pandas 3.0.0rc0 Pandas 3.0.0 will be released soon, and we're on Release candidate 0 Here's What's new in Pands 3.0.0 Dedicated string data type by default Inferred by default for string data (instead of object dtype) The str dtype can only hold strings (or missing values), in contrast to object dtype. (setitem with non string fails) The missing value sentinel is always NaN (np.nan) and follows the same missing value semantics as the other default dtypes. Copy-on-Write The result of any indexing operation (subsetting a DataFrame or Series in any way, i.e. including accessing a DataFrame column as a Series) or any method returning a new DataFrame or Series, always behaves as if it were a copy in terms of user API. As a consequence, if you want to modify an object (DataFrame or Series), the only way to do this is to directly modify that object itself. pd.col syntax can now be used in DataFrame.assign() and DataFrame.loc() You can now do this: df.assign(c = pd.col('a') + pd.col('b')) New Deprecation Policy Plus more - Michael #3: typos You've heard about codespell … what about typos? VSCode extension and OpenVSX extension. From Sky Kasko: Like codespell, typos checks for known misspellings instead of only allowing words from a dictionary. But typos has some extra features I really appreciate, like finding spelling mistakes inside snake_case or camelCase words. For example, if you have the line: *connecton_string = "sqlite:///my.db"* codespell won't find the misspelling, but typos will. It gave me the output: *error: `connecton` should be `connection`, `connector` ╭▸ ./main.py:1:1 │1 │ connecton_string = "sqlite:///my.db" ╰╴━━━━━━━━━* But the main advantage for me is that typos has an LSP that supports editor integrations like a VS Code extension. As far as I can tell, codespell doesn't support editor integration. (Note that the popular Code Spell Checker VS Code extension is an unrelated project that uses a traditional dictionary approach.) For more on the differences between codespell and typos, here's a comparison table I found in the typos repo: https://github.com/crate-ci/typos/blob/master/docs/comparison.md By the way, though it's not mentioned in the installation instructions, typos is published on PyPI and can be installed with uv tool install typos, for example. That said, I don't bother installing it, I just use the VS Code extension and run it as a pre-commit hook. (By the way, I'm using prek instead of pre-commit now; thanks for the tip on episode #448!) It looks like typos also publishes a GitHub action, though I haven't used it. Brian #4: A couple testing topics slowlify suggested by Brian Skinn Simulate slow, overloaded, or resource-constrained machines to reproduce CI failures and hunt flaky tests. Requires Linux with cgroups v2 Why your mock breaks later Ned Badthelder Ned's taught us before to “Mock where the object is used, not where it's defined.” To be more explicit, but probably more confusing to mock-newbies, “don't mock things that get imported, mock the object in the file it got imported to.” See? That's probably worse. Anyway, read Ned's post. If my project myproduct has user.py that uses the system builtin open() and we want to patch it: DONT DO THIS: @patch("builtins.open") This patches open() for the whole system DO THIS: @patch("myproduct.user.open") This patches open() for just the user.py file, which is what we want Apparently this issue is common and is mucking up using coverage.py Extras Brian: The Rise and Rise of FastAPI - mini documentary “Building on Lean” chapter of LeanTDD is out The next chapter I'm working on is “Finding Waste in TDD” Notes to delete before end of show: I'm not on track for an end of year completion of the first pass, so pushing goal to 1/31/26 As requested by a reader, I'm releasing both the full-so-far versions and most-recent-chapter Michael: My Vanishing Gradient's episode is out Django 6 is out Joke: tabloid - A minimal programming language inspired by clickbait headlines

Arto Minasyan is the Co-founder and President of Krisp, a company that provides AI-powered noise cancellation and voice optimization to improve clarity in virtual communication. He is also the Co-founder and CEO of 10Web, an AI-driven WordPress platform that automates website building, hosting, and performance optimization for businesses and agencies.  In this episode… Voice technology is evolving faster than most people can track, redefining how we meet, collaborate, and build online. As AI becomes woven into everyday tools, tasks that once felt clunky or technical now feel surprisingly simple. So what happens when voice AI and automated web creation become powerful enough to feel effortless? For Arto Minasyan, a longtime innovator in AI-driven communication, real progress occurs when technology removes friction from the experience instead of adding to it. He explains that people don't embrace tools simply because they're sophisticated — they stick with the ones that make life easier within seconds. That thinking guided Krisp's expansion from basic noise reduction into transcription, meeting notes, and real-time accent conversion. His work on automated WordPress creation reflects the same principle: deliver immediate results through an API rather than forcing users to navigate a complex platform. By centering speed, clarity, and intuitive workflows, Arto sees AI reshaping the way people communicate and build online. In this episode of the Inspired Insider Podcast, Dr. Jeremy Weisz sits down with Arto Minasyan, Co-founder and President of Krisp, to discuss the rise of voice AI and next-generation WordPress automation. They explore Krisp's expansion beyond noise cancellation, the power of an API-first website builder, and how timing shapes startup success. Arto also talks about the future of human-to-computer voice interaction.

Transitioning a mature organization from an API-first model to an AI-first model is no small feat. In this episode, Yash Kosaraju, CISO of Sendbird, shares the story of how they pivoted from a traditional chat API platform to an AI agent platform and how security had to evolve to keep up.Yash spoke about the industry's obsession with "Zero Trust," arguing instead for a practical "Multi-Layer Trust" approach that assumes controls will fail . We dive deep into the specific architecture of securing AI agents, including the concept of a "Trust OS," dealing with new incident response definitions (is a wrong AI answer an incident?), and the critical need to secure the bridge between AI agents and customer environments .This episode is packed with actionable advice for AppSec engineers feeling overwhelmed by the speed of AI. Yash shares how his team embeds security engineers into sprint teams for real-time feedback, the importance of "AI CTFs" for security awareness, and why enabling employees with enterprise-grade AI tools is better than blocking them entirely .Questions asked:Guest Socials - Yash's LinkedinPodcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you are interested in AI Cybersecurity, you can check out our sister podcast -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AI Security Podcast⁠Questions asked:(00:00) Introduction(02:20) Who is Yash Kosaraju? (CISO at Sendbird)(03:30) Sendbird's Pivot: From Chat API to AI Agent Platform(05:00) Balancing Speed and Security in an AI Transition(06:50) Embedding Security Engineers into AI Sprint Teams(08:20) Threats in the AI Agent World (Data & Vendor Risks)(10:50) Blind Spots: "It's Microsoft, so it must be secure"(12:00) Securing AI Agents vs. AI-Embedded Applications(13:15) The Risk of Agents Making Changes in Customer Environments(14:30) Multi-Layer Trust vs. Zero Trust (Marketing vs. Reality) (17:30) Practical Multi-Layer Security: Device, Browser, Identity, MFA(18:25) What is "Trust OS"? A Foundation for Responsible AI(20:45) Balancing Agent Security vs. Endpoint Security(24:15) AI Incident Response: When an AI Gives a Wrong Answer(29:20) Security for Platform Engineers: Enabling vs. Blocking(30:45) Providing Enterprise AI Tools (Gemini, ChatGPT, Cursor) to Employees(32:45) Building a "Security as Enabler" Culture(36:15) What Questions to Ask AI Vendors (Paying with Data?)(39:20) Personal Use of Corporate AI Accounts(43:30) Using AI to Learn AI (Gemini Conversations)(45:00) The Stress on AppSec Engineers: "I Don't Know What I'm Doing"(48:20) The AI CTF: Gamifying Security Training(50:10) Fun Questions: Outdoors, Team Building, and Indian/Korean Food

In this episode of The Cybersecurity Defenders Podcast, we discuss some intel being shared in the LimaCharlie community.For for more information about Cybersecurity Cares, visit cybersecurity-cares.comThe Tomiris cyber-espionage group, which has been under Kaspersky's watch since 2021, has evolved its tactics in a new wave of attacks observed in early 2025. Article #2.CISA has recently added CVE-2021-26829 to its known exploited vulnerabilities, or KEV catalog, marking it as a confirmed threat based on real world exploitation. Researchers at KOI Security have identified a malicious NPM package, which not only performs typical credential stealing behavior, but also includes a new, subtle tactic attempting to manipulate AI-driven security scanners via embedded prompt engineering. Article #2.Iranian state sponsored threat group MuddyWater has launched a new wave of cyber espionage attacks targeting Israeli organizations across sectors including academia, civil infrastructure, engineering, technology and utilities.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

“Open doesn't mean a free for all, but open will win.” Workday CTO Peter Bailis joins Bloomberg Intelligence Senior Technology Analyst Anurag Rana to explain how the people-and-money system of record is evolving into an open, AI-ready platform — combining zero-copy data access with strict governance and API-first design. He outlines how Sana, Illuminate, Flowise and Paradox fit together as a front door for work, embedded HR and finance agents, open-source agent building and streamlined recruiting.

In this episode of the ABB Solutions Podcast, host Mike Murphy continues the discussion with Abel Cavazos and Wayne Paschal from ABB's High Power Division. This second installment focuses on how environmental conditions, enclosure selection, and proper monitoring can significantly impact motor life and reliability, especially in high-power and high-criticality applications. Tune in to hear insights on:Motor Enclosure Selection: How WP2, TFC, TX, and TWAC designs differ, when each is appropriate, and how contamination, cooling efficiency, and horsepower size influence enclosure choice.Environmental and Cooling Considerations: Why airborne contaminants, restricted airflow, dirty cooling tubes, and clogged filters can lead to overheating, and which enclosure types help mitigate these issues.Maintenance Practices: Practical steps facilities can take to maintain high-power motors, including differential pressure monitoring, tube cleaning, fin maintenance, and planning for long turnarounds.Monitoring for Reliability: How stator RTDs, bearing RTDs, vibration checks, and temperature delta tracking help plants shift from reactive to predictive maintenance.Criticality and Feature Selection: How CR1 through CR4 ratings influence the level of monitoring required, and why adding diagnostic features helps reduce unplanned downtime.PCIC Presentation Insights: Background on the paper titled The Cost of Specifications Reducing Motor Features Based on Process Criticality Without Sacrificing Reliability, how it ties into API 541, API 547, and IEEE 841, and why it sparked new thinking around criticality at PCIC.References:Transforming industry with energy-efficient motors and reliable power generators: https://new.abb.com/motors-generators

In this episode of ClearTalk, newly appointed CTO Brad Dempsey sits down with Solutions360's new CEO, Nate Gardner, for an in-depth conversation about the future of the company and the integration industry at large. With several months in the role, Nate shares early insights from meeting customers across North America, his perspective on Solutions360's evolving platform strategy, and how the partnership with Northrim Horizon is already shaping long-term innovation.The discussion explores what makes Northrim's perpetual hold investment model so unique and why it enables Solutions360 to take a long-range, foundational approach to product development. Nate outlines how this funding is being deployed today—from modernizing core infrastructure, rewriting backend services for large-scale AI adoption, and evolving Q360's front-end experience, to investing in tools that equip internal teams to better serve customers.Brad and Nate also dig into how Q360's role as a system of record is expanding in an AI-driven world. They discuss workflow automation, new API-driven architecture in V25, the rise of integrations with partners like RAMP, and how AI will soon shift from chat-driven insights to real-time decision support and automated task execution.Finally, they touch on the exciting opportunities ahead in acquisitions, partnerships, and platform expansion, all focused on supporting the full lifecycle of an integrator or MSP.ClearTalk 52 sets the stage for a transformative era at Solutions360, offering an inside look at the strategic direction, technological vision, and investment momentum shaping what comes next.To learn more about how Solutions360 can help you run your business more effectively, click this link to connect with us: https://www.solutions360.com/our-mission-is-to-become-our-customers-most-valued-business-partner/

Sébastien Stormacq, responsable des relations développeurs chez AWS, explique comment le Vibe Coding bouleverse la manière de programmer : générer une application complète en discutant simplement avec un agent IA, même depuis son canapé.Interview : Sébastien Stormacq, responsable des relations avec les développeurs chez AWSQu'est-ce que le Vibe Coding et qu'est-ce que ça change pour les développeurs ?Le Vibe Coding consiste à programmer avec l'IA. Grâce à un chatbot intégré dans l'environnement de développement, on peut lui demander résoudre un problème, d'analyser des erreurs ou de générer du code. Cela permet d'aller beaucoup plus vite. Par exemple, j'ai personnellement créé un jeu pour iOS en quelques minutes, du fond de mon canapé. Certes l'application n'était pas parfaite, mais l'agent me proposait spontanément des corrections, et en une heure, tout fonctionnait. Sans écrire une ligne de code ! Aujourd'hui, je l'utilise au quotidien pour tout ce qui est répétitif, rébarbatif, et ça me fait gagner un temps énorme. On peut d'ailleurs télécharger l'environnement Kiro directement sur le site kiro.dev.Le Vibe Coding peut-il être utilisé à l'échelle d'une entreprise ?Le Vibe Coding est très efficace pour un développeur seul, mais il n'est pas facilement répétable en équipe. On peut vite perdre la trace de ce qui a été généré, comment et pourquoi.C'est pour cela que nous avons introduit une approche plus structurée chez AWS : le Spec Driven Development. L'agent rédige d'abord des spécifications en langage naturel, puis propose un design technique, avant de générer les tâches et le squelette du projet. Toutes ces étapes sont documentées et versionnées dans le repository, par exemple sur GitHub. Cela permet de garder un historique clair, partageable, et d'évoluer proprement, même un an plus tard. C'est cette méthode qui rend possible le passage à l'échelle.Les agents autonomes : la prochaine étape ?On voit apparaître des agents capables de tourner longtemps, sur serveur, et d'exécuter des tâches de fond : analyser des logs, réagir à des erreurs, croiser des sources de données, alerter… C'est comme avoir une personne supplémentaire dans l'équipe, disponible 24h/24.Un agent, au fond, c'est juste du code. Il s'appuie sur un modèle pour décider quels outils utiliser et dans quel ordre. Moi, j'aime comparer ça à un passe-plat : le modèle décide, l'agent exécute, puis lui renvoie les résultats jusqu'à atteindre l'objectif fixé. Aucun mystère, juste des API et une boucle logique très simple.Podcast de Sébastien Stormacq : AWS en français.-----------♥️ Soutien : https://mondenumerique.info/don

I det här specialavsnittet tar vi dig till frukosteventet “AI Breakfast for Digital Leaders” som presenterades av Adobe, Vaimo och Bluestone PIM, där vi hör Morten Naess (CPIO, Bluestone PIM), Jakob Dahlner (CTO, Elon Group) och Dennis Koraen (Head of Marketing & E-commerce, Granit) dela insikter om hur man kombinerar datakvalitet, automation och customer obsession för att skapa affärsvärde i realtid. Vi får höra om hur moderna retailbolag bygger techstackar som klarar både tillväxt och AI-omställning, om konkreta kundcase, datakvalitet som tillväxtmotor, AI-integrering i realtid, och hur man framtidssäkrar sin commerce-setup i en komplex omnikanalvärld.https://business.adobe.com/https://www.vaimo.com/sv/https://www.bluestonepim.com/08:40 – AI möjliggör skalbar contentproduktion - snabba test & iteration15:10 – Datakvalitet som bas för PIM, CX och AI-strategier28:30 – AI på kundtjänstdata - GPT som analysmotor34:55 – Utmaning: tonalitet & varumärkeskontroll i AI-genererat innehåll39:20 – AI-pilotprojekt kräver modularisering av techstack45:10 – Hallucinationer i AI - varför human QA fortfarande behövs52:05 – Vision: autonoma system för content, inköp och marknad58:30 – Lärdomar från bilbranschen - AI som säljstöd, inte hot65:15 – Nya kompetenser: adaptivitet, analys, promptförståelse71:45 – MVP-fokus krävs för att AI ska ge faktisk affärsnytta76:30 – Framtidens PIM: composable, API-först, integrerat i CX81:10 – AI demokratiserar data men kräver ny organisationsstrukturHär hittar du Morten Naess, Jakob Dahlner & Dennis Koraen:https://www.linkedin.com/in/morten-naess/ https://www.linkedin.com/in/jakob-dahlner-a1670234/ https://www.linkedin.com/in/denniskoraen/ Följ Framtidens E-handel på LinkedIn:https://www.linkedin.com/company/framtidens-e-handel/ Besök vår hemsida, YouTube & Instagram:https://www.framtidensehandel.se/ https://www.instagram.com/framtidens.ehandel/ https://www.youtube.com/channel/UCEYywBFgOr34TN8NtXeL5HQPoddproducenter Michaela Dorch & Fredrik Ankarsköld:https://www.linkedin.com/in/michaela-dorch/ https://www.linkedin.com/in/ankarskold/ Tusen tack för att du lyssnar!Support till showen http://supporter.acast.com/framtidens-e-handel. Hosted on Acast. See acast.com/privacy for more information.

Welcome to Season 5, Episode 49! Vroooommmm!!! We're exploring the story of Asian Pacific Islanders in Formula 1… and this is something we actually know a bit about. This is a sport long dominated by Europeans and a handful of South Americans, but there has been a small group of drivers of Asian Pacific descent who have made an impact in recent years.  We'll share a little about F1 racing in general as well as when API began making their mark in the sport. In addition to recent drivers like Alex Albon (our favorite), Yuki Tsunoda, Zhou Guanyu, and now Arvid Lindblad, we'll also talk about a few engineers, leaders, and teams that have prominent Asian representation.  In our recurring segment, we'll share what we're listening to. For Ted, it's the audiobook of Babel by R.F. Kuang. It's narrated by Chris Lew Kum Hoi and Billie Fulford-Brown. For Gen, it's the music of Sarah Kinsley… specifically the song Fleeting. If you like what we do, please share, follow, and like us in your podcast directory of choice or on Instagram @AAHistory101. For previous episodes and resources, please visit our site at https://asianamericanhistory101.libsyn.com or our links at http://castpie.com/AAHistory101. If you have any questions, comments or suggestions, email us at info@aahistory101.com. Segments 00:25 Intro and Catching Up 14:16 The History of API in Formula 1 Racing 38:17 What Are We Listening To: Babel by R.F. Kuang and Sarah Kinsley

In this episode of the Transform Sales Podcast Sales Software Review Series, we sat down with Marc Lewin, Co-founder and CMO of Salemaker. Salemaker is an AI powered video generation platform that helps sales and marketing teams automate and scale personalized video content with speed and consistency. Marc shares how Salemaker's advanced features like multilingual voice cloning, face syncing for natural expressions, automated scripting, website enriched variables, and AI generated avatars make it possible to produce high quality videos without the manual recording burden. From building content calendars to generating videos programmatically through API calls, Salemaker streamlines the entire video creation workflow for modern teams. If you want to save time, improve consistency, and elevate your outreach with personalized video at scale, Salemaker offers a powerful solution. Explore Salemaker here: https://software.cloudtask.com/salemaker-b768ce TransformSales #salessoftware #cloudtask

Every few years, the world of product management goes through a phase shift. When I started at Microsoft in the early 2000s, we shipped Office in boxes. Product cycles were long, engineering was expensive, and user research moved at the speed of snail mail. Fast forward a decade and the cloud era reset the speed at which we build, measure, and learn. Then mobile reshaped everything we thought we knew about attention, engagement, and distribution.Now we are standing at the edge of another shift. Not a small shift, but a tectonic one. Artificial intelligence is rewriting the rules of product creation, product discovery, product expectations, and product careers.To help make sense of this moment, I hosted a panel of world class product leaders on the Fireside PM podcast:• Rami Abu-Zahra, Amazon product leader across Kindle, Books, and Prime Video• Todd Beaupre, Product Director at YouTube leading Home and Recommendations• Joe Corkery, CEO and cofounder of Jaide Health • Tom Leung (me), Partner at Palo Alto Foundry• Lauren Nagel, VP Product at Mezmo• David Nydegger, Chief Product Officer at OvivaThese are leaders running massive consumer platforms, high stakes health tech, and fast moving developer tools. The conversation was rich, honest, and filled with specific examples. This post summarizes the discussion, adds my own reflections, and offers a practical guide for early and mid career PMs who want to stay relevant in a world where AI is redefining what great product management looks like.Table of Contents* What AI Cannot Do and Why PM Judgment Still Matters* The New AI Literacy: What PMs Must Know by 2026* Why Building AI Products Speeds Up Some Cycles and Slows Down Others* Whether the PM, Eng, UX Trifecta Still Stands* The Biggest Risks AI Introduces Into Product Development* Actionable Advice for Early and Mid Career PMs* My Takeaways and What Really Matters Going Forward* Closing Thoughts and Coaching Practice1. What AI Cannot Do and Why PM Judgment Still MattersWe opened the panel with a foundational question. As AI becomes more capable every quarter, what is left for humans to do. Where do PMs still add irreplaceable value. It is the question every PM secretly wonders.Todd put it simply: “At the end of the day, you have to make some judgment calls. We are not going to turn that over anytime soon.”This theme came up again and again. AI is phenomenal at synthesizing, drafting, exploring, and narrowing. But it does not have conviction. It does not have lived experience. It does not feel user pain. It does not carry responsibility.Joe from Jaide Health captured it perfectly when he said: “AI cannot feel the pain your users have. It can help meet their goals, but it will not get you that deep understanding.”There is still no replacement for sitting with a frustrated healthcare customer who cannot get their clinical data into your system, or a creator on YouTube who feels the algorithm is punishing their art, or a devops engineer staring at an RCA output that feels 20 percent off.Every PM knows this feeling: the moment when all signals point one way, but your gut tells you the data is incomplete or misleading. This is the craft that AI does not have.Why judgment becomes even more important in an AI worldDavid, who runs product at a regulated health company, said something incredibly important: “Knowing what great looks like becomes more essential, not less. The PM's that thrive in AI are the ones with great product sense.”This is counterintuitive for many. But when the operational work becomes automated, the differentiation shifts toward taste, intuition, sequencing, and prioritization.Lauren asked the million dollar question. “How are we going to train junior PMs if AI is doing the legwork. Who teaches them how to think.”This is a profound point. If AI closes the gap between junior and senior PMs in execution tasks, the difference will emerge almost entirely in judgment. Knowing how to probe user problems. Knowing when a feature is good enough. Knowing which tradeoffs matter. Knowing which flaw is fatal and which is cosmetic.AI is incredible at writing a PRD. AI is terrible at knowing whether the PRD is any good.Which means the future PM becomes more strategic, more intuitive, more customer obsessed, and more willing to make thoughtful bets under uncertainty.2. The New AI Literacy: What PMs Must Know by 2026I asked the panel what AI literacy actually means for PMs. Not the hype. Not the buzzwords. The real work.Instead of giving gimmicky answers, the discussion converged on a clear set of skills that PMs must master.Skill 1: Understanding context engineeringDavid laid this out clearly: “Knowing what LMS are good at and what they are not good at, and knowing how to give them the right context, has become a foundational PM skill.”Most PMs think prompt engineering is about clever phrasing. In reality, the future is about context engineering. Feeding models the right data. Choosing the right constraints. Deciding what to ignore. Curating inputs that shape outputs in reliable ways.Context engineering is to AI product development what Figma was to collaborative design. If you cannot do it, you are not going to be effective.Skill 2: Evals, evals, evalsRami said something that resonated with the entire panel: “Last year was all about prompts. This year is all about evals.”He is right.• How do you build a golden dataset.• How do you evaluate accuracy.• How do you detect drift.• How do you measure hallucination rates.• How do you combine UX evals with model evals.• How do you decide what good looks like.• How do you define safe versus unsafe boundaries.AI evaluation is now a core PM responsibility. Not exclusively. But PMs must understand what engineers are testing for, what failure modes exist, and how to design test sets that reflect the real world.Lauren said her PMs write evals side by side with engineering. That is where the world is going.Skill 3: Knowing when to trust AI output and when to override itTodd noted: “It is one thing to get an answer that sounds good. It is another thing to know if it is actually good.”This is the heart of the role. AI can produce strategic recommendations that look polished, structured, and wise. But the real question is whether they are grounded in reality, aligned with your constraints, and consistent with your product vision.A PM without the ability to tell real insight from confident nonsense will be replaced by someone who can.Skill 4: Understanding the physics of model changesThis one surprised many people, but it was a recurring point.Rami noted: “When you upgrade a model, the outputs can be totally different. The evals start failing. The experience shifts.”PMs must understand:• Models get deprecated• Models drift• Model updates can break well tuned prompts• API pricing has real COGS implications• Latency varies• Context windows vary• Some tasks need agents, some need RAG, some need a small finetuned modelThis is product work now. The PM of 2026 must know these constraints as well as a PM of the cloud era understood database limits or API rate limits.Skill 5: How to construct AI powered prototypes in hours, not weeksIt now takes one afternoon to build something meaningful. Zero code required. Prompt, test, refine. Whether you use Replit, Cursor, Vercel, or sandboxed agents, the speed is shocking.But this makes taste and problem selection even more important. The future PM must be able to quickly validate whether a concept is worth building beyond the demo stage.3. Why Building AI Products Speeds Up Some Cycles and Slows Down OthersThis part of the conversation was fascinating because people expected AI to accelerate everything. The panel had a very different view.Fast: Prototyping and concept validationLauren described how her teams can build working versions of an AI powered Root Cause Analysis feature in days, test it with customers, and get directional feedback immediately.“You can think bigger because the cost of trying things is much lower,” she said.For founders, early PMs, and anyone validating hypotheses, this is liberating. You can test ten ideas in a week. That used to take a quarter.Slow: Productionizing AI featuresThe surprising part is that shipping the V1 of an AI feature is slower than most expect.Joe noted: “You can get prototypes instantly. But turning that into a real product that works reliably is still hard.”Why. Because:• You need evals.• You need monitoring.• You need guardrails.• You need safety reviews.• You need deterministic parts of the workflow.• You need to manage COGS.• You need to design fallbacks.• You need to handle unpredictable inputs.• You need to think about hallucination risk.• You need new UI surfaces for non deterministic outputs.Lauren said bluntly: “Vibe coding is fast. Moving that vibe code to production is still a four month process.”This should be printed on a poster in every AI startup office.Very Slow: Iterating on AI powered featuresAnother counterintuitive point. Many teams ship a great V1 but struggle to improve it significantly afterward.David said their nutrition AI feature launched well but: “We struggled really hard to make it better. Each iteration was easy to try but difficult to improve in a meaningful way.”Why is iteration so difficult.Because model improvements may not translate directly into UX improvements. Users need consistency. Drift creates churn. Small changes in context or prompts can cause large changes in behavior.Teams are learning a hard truth: AI powered features do not behave like typical deterministic product flows. They require new iteration muscles that most orgs do not yet have.4. The PM, Eng, UX Trifecta in the AI EraI asked whether the classic PM, Eng, UX triad is still the right model. The audience was expecting disagreement. The panel was surprisingly aligned.The trifecta is not going anywhereRami put it simply: “We still need experts in all three domains to raise the bar.”Joe added: “AI makes it possible for PMs to do more technical work. But it does not replace engineering. Same for design.”AI blurs the edges of the roles, but it does not collapse them. In fact, each role becomes more valuable because the work becomes more abstract.• PMs focus on judgment, sequencing, evaluation, and customer centric problem framing• Engineers focus on agents, systems, architecture, guardrails, latency, and reliability• Designers focus on dynamic UX, non deterministic UX patterns, and new affordances for AI outputsWhat does changeAI makes the PM-Eng relationship more intense. The backbone of AI features is a combination of model orchestration, evaluation, prompting, and context curation. PMs must be tighter than ever with engineering to design these systems.David noted that his teams focus more on individual talents. Some PMs are great at context engineering. Some designers excel at polishing AI generated layouts. Some engineers are brilliant at prompt chaining. AI reveals strengths quickly.The trifecta remains. The skill distribution within it evolves.5. The Biggest Risks AI Introduces Into Product DevelopmentWhen we asked what scares PMs most about AI, the conversation became blunt and honest. Risk 1: Loss of user trustLauren warned: “If people keep shipping low quality AI features, user trust in AI erodes. And then your good AI product suffers from the skepticism.”This is very real. Many early AI features across industries are low quality, gimmicky, or unreliable. Users quickly learn to distrust these experiences.Which means PMs must resist the pressure to ship before the feature is ready.Risk 2: Skill atrophyTodd shared a story that hit home for many PMs. “Junior folks just want to plug in the prompt and take whatever the AI gives them. That is a recipe for having no job later.”PMs who outsource their thinking to AI will lose their judgment. Judgment cannot be regained easily.This is the silent career killer.Risk 3: Safety hazards in sensitive domainsDavid was direct: “If we have one unsafe output, we have to shut the feature off. We cannot afford even small mistakes.”In healthcare, finance, education, and legal industries, the tolerance for error is near zero. AI must be monitored relentlessly. Human in the loop systems are mandatory. The cycles are slower but the stakes are higher.Risk 4: The high bar for AI compared to humansJoe said something I have thought about for years: “AI is held to a much higher standard than human decision making. Humans make mistakes constantly, but we forgive them. AI makes one mistake and it is unacceptable.”This slows adoption in certain industries and creates unrealistic expectations.Risk 5: Model deprecation and instabilityRami described a real problem AI PMs face: “Models get deprecated faster than they get replaced. The next model is not always GA. Outputs change. Prompts break.”This creates product instability that PMs must anticipate and design around.Risk 6: Differentiation becomes hardI shared this perspective because I see so many early stage startups struggle with it.If your whole product is a wrapper around an LLM, competitors will copy you in a week. The real differentiation will not come from using AI. It will come from how deeply you understand the customer, how you integrate AI with proprietary data, and how you create durable workflows.6. Actionable Advice for Early and Mid Career PMsThis was one of my favorite parts of the panel because the advice was humble, practical, and immediately useful.A. Develop deep user empathy. This will become your biggest differentiator.Lauren said it clearly: “Maintain your empathy. Understand the pain your user really has.”AI makes execution cheap. It makes insight valuable.If you can articulate user pain precisely.If you can differentiate surface friction from underlying need.If you can see around corners.If you can prototype solutions and test them in hours.If you can connect dots between what AI can do and what users need.You will thrive.Tactical steps:• Sit in on customer support calls every week.• Watch 10 user sessions for every feature you own.• Talk to customers until patterns emerge.• Ask “why” five times in every conversation.• Maintain a user pain log and update it constantly.B. Become great at context engineeringThis will matter as much as SQL mattered ten years ago.Action steps:• Practice writing prompts with structured context blocks.• Build a library of prompts that work for your product.• Study how adding, removing, or reordering context changes output.• Learn RAG patterns.• Learn when structured data beats embeddings.• Learn when smaller local models outperform big ones.C. Learn eval frameworksThis is non negotiable.You need to know:• Precision vs recall tradeoffs• How to build golden datasets• How to design scenario based evals for UX• How to test for hallucination• How to monitor drift• How to set quality thresholds• How to build dashboards that reflect real world input distributionsYou do not need to write the code.You do need to define the eval strategy.D. Strengthen your product senseYou cannot outsource product taste.Todd said it best: “Imagine asking AI to generate 20 percent growth for you. It will not tell you what great looks like.”To strengthen your product sense:• Review the best products weekly.• Take screenshots of great UX patterns.• Map user flows from apps you admire.• Break products down into primitives.• Ask yourself why a product decision works.• Predict what great would look like before you design it.The PMs who thrive will be the ones who can recognize magic when they see it.E. Stay curiousRami's closing advice was simple and perfect: “Stay curious. Keep learning. It never gets old.”AI changes monthly. The PM who is excited by new ideas will outperform the PM who clings to old patterns.Practical habits:• Read one AI research paper summary each week.• Follow evaluation and model updates from major vendors.• Build at least one small AI prototype a month.• Join AI PM communities.• Teach juniors what you learn. Nothing accelerates mastery faster.F. Embrace velocity and side projectsTodd said that some of his biggest career breakthroughs came from solving problems on the side.This is more true now than ever.If you have an idea, you can build an MVP over a weekend. If it solves a real problem, someone will notice.G. Stay close to engineeringNot because you need to code, but because AI features require tighter PM engineering collaboration.Learn enough to be dangerous:• How embeddings work• How vector stores behave• What latency tradeoffs exist• How agents chain tasks• How model versioning works• How context limits shape UX• Why some prompts blow up API costsIf you can speak this language, you will earn trust and accelerate cycles.H. Understand the business deeplyJoe's advice was timeless: “Know who pays you and how much they pay. Solve real problems and know the business model.”PMs who understand unit economics, COGS, pricing, and funnel dynamics will stand out.7. Tom's Takeaways and What Really Matters Going ForwardI ended the recording by sharing what I personally believe after moderating this discussion and working closely with a variety of AI teams over the past 2 years.Judgment becomes the most valuable PM skillAs AI gets better at analysis, synthesis, and execution, your value shifts to:• Choosing the right problem• Sequencing decisions• Making 55 45 calls• Understanding user pain• Making tradeoffs• Deciding when good is good enough• Defining success• Communicating vision• Influencing the orgAgents can write specs.LLMs can produce strategies.But only humans can choose the right one and commit.Learning speed becomes a competitive advantageI said this on the panel and I believe it more every month.Because of AI, you now have:• Infinite coaches• Infinite mentors• Infinite experts• Infinite documentation• Infinite learning loopsA PM who learns slowly will not survive the next decade. Curiosity, empathy, and velocity will separate great from goodMany panelists said versions of this. The common pattern was:• Understand users deeply• Combine multiple tools creatively• Move quickly• Learn constantlyThe future rewards generalists with taste, speed, and emotional intelligence.Differentiation requires going beyond wrapper appsThis is one of my biggest concerns for early stage founders. If your entire product is a wrapper around a model, you are vulnerable.Durable value will come from:• Proprietary data• Proprietary workflows• Deep domain insight• Organizational trust• Distribution advantage• Safety and reliability• Integration with existing systemsAI is a component, not a moat.8. Closing ThoughtsHosting this panel made me more optimistic about the future of product management. Not because AI will not change the job. It already has. But because the fundamental craft remains alive.Product management has always been about understanding people, making decisions with incomplete information, telling compelling stories, and guiding teams through ambiguity and being right often.AI accelerates the craft. It amplifies the best PMs and exposes the weak ones. It rewards curiosity, empathy, velocity, and judgment.If you want tailored support on your PM career, leadership journey, or executive path, I offer 1 on 1 career, executive, and product coaching at tomleungcoaching.com.OK team. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Linux 6.18 is officially out, and officially an LTS release, 6.19 has plenty to be excited about, including the color pipeline API. NVIDIA is making progress with Wayland and other regions, Fedora is moving away from FBCON, and Flowblade sees a Wayland-only future. NPM has a worm problem, and we're still gaining ground on Steam! For tips, we have scx for rolling your own userspace scheduler, and a fix for Yakuake for your old-school terminal needs. You can find the show notes at https://bit.ly/44ISvVi and have a great week! Host: Jonathan Bennett Co-Host: Jeff Massie Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Want access to the ad-free video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

In this episode of The Digital Marketing Podcast, Daniel Rowles introduces us to the process of Vibe Coding, a revolutionary approach to software development that leverages AI to make app creation accessible to anyone, regardless of coding experience. Vibe coding shifts the focus from writing manual code to guiding AI with natural language prompts, allowing non-developers to build interactive apps, tools, and even businesses. Daniel explores the three tiers of vibe coding, from basic one-page web apps to full-scale, secure, AI-powered platforms , and shares practical steps, tools and security tips to get started. The second half of the episode features a compelling interview with Christo Snyman, a podcast listener who used vibe coding to launch his AI assistant platform Traderly.ai. Christo takes us behind the scenes of building a real-world startup with no prior coding background, sharing his full tech stack, hard-earned lessons, and the mindset needed to succeed. In This Episode: What is Vibe Coding? Understand how natural language prompts can now be used to create working code, dramatically lowering the barrier to digital creation. The Three Levels of Vibe Coding Level 1: Build one-page apps using HTML, CSS, and React, no backend required Level 2: Add memory, interactivity, and live AI responses through API access Level 3: Create fully-fledged apps with user authentication, databases, and deployment Practical Use Cases - From interactive Google algorithm timelines to embedded AI tools for keyword research and content planning, Daniel shares how these tools are being used on Target Internet's own website. Christo's Journey - From Idea to Startup. Learn how Christo turned a common business pain point — small service businesses missing leads due to message overload — into a scalable SaaS platform. Discover his full tech stack including React, Azure Functions, PostgreSQL, Firebase, OpenAI, WordPress, and more. Key Takeaways: Anyone can now build apps using AI tools, whether it's a timeline, calculator, chatbot, or full customer-facing product. AI-assisted development removes fear and unlocks creativity, especially for entrepreneurs without a dev background. Start small and iterate, your Minimal Viable Product doesn't need to be perfect, it needs to be useful. Vibe coding is the bridge between ideas and execution - fast, flexible and increasingly powerful. The future of marketing and tech creation is conversational and it's already here.

Linux 6.18 is officially out, and officially an LTS release, 6.19 has plenty to be excited about, including the color pipeline API. NVIDIA is making progress with Wayland and other regions, Fedora is moving away from FBCON, and Flowblade sees a Wayland-only future. NPM has a worm problem, and we're still gaining ground on Steam! For tips, we have scx for rolling your own userspace scheduler, and a fix for Yakuake for your old-school terminal needs. You can find the show notes at https://bit.ly/44ISvVi and have a great week! Host: Jonathan Bennett Co-Host: Jeff Massie Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Want access to the ad-free video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

In this video I'll tell you what I'd do if I was broke, and how dividends would help save me. Join the world's largest free Dividend Discord ➜ https://discord.gg/kkSr5FY Join my channel membership as a GenEx Partner to access new perks: https://www.youtube.com/channel/UCuOS-UH_s4KGhArN6HdRB0Q/join Seeking Alpha Affiliate Referral Link ➜ https://link.seekingalpha.com/2352ZCK/4G6SHH/ Click my FAST Graphs Link (Use coupon code AFFILIATE25 to get 25% off your 1st payment) ➜ https://fastgraphs.com/?ref=GenExDividendInvestor Please use my Amazon Affiliates Link ➜ https://amzn.to/2YLxsiW Thanks! As an Amazon Associate I earn from qualifying purchases. Support me & get Patreon perks ➜ https://www.patreon.com/join/genexdividendinvestor Use my Financial Modeling Prep affiliate link for awesome stock API data (up to a 25% discount) ➡️ https://site.financialmodelingprep.com/pricing-plans?couponCode=genex25

Send us a textA week where the lawful intercept backdoor became the front door, a supply chain hop hit 200+ companies, a bargain app faced a malware lawsuit, and a university breach turned into a donor-targeting roadmap. We share simple moves to lower risk fast and set guardrails that actually hold.• Salt Typhoon abusing CALEA at major US telecoms• Negligence, unpatched routers and weak passwords• Why SMS is transparent and how to switch to Signal• Kill SMS 2FA and use authenticators or YubiKey• Gainsight-to-Salesforce island hopping at scale• Audit connected apps and revoke stale API keys• Arizona AG lawsuit calling Timu malware• Shop via browser sandbox and use masked payments• UPenn donor data leak and Oracle exploit• Whaling protections with voice verification and data scrubbing• Practical recap: trust nothing, verify everythingPlease follow us or subscribe on your podcast app, and watch the video on our YouTube or at theproblemlounge.com. If you have topics or guest ideas, we would love to hear from you Support the show

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.

You've been lied to about AI.

Scott and CJ sit down live at JSNation NYC with Iwo Plaza, creator of TypeGPU, to dig into how WebGPU is unlocking a new wave of graphics and compute power on the web. They chat about shader authoring in TypeScript, the future of GPU-powered AI in the browser, and what it takes to build a killer developer-friendly graphics library. Show Notes 00:00 Welcome to Syntax! 00:32 What is TypeGPU? High-level overview and why it exists 01:20 WebGPU vs WebGL – the new era of GPU access on the web 01:47 Why shader languages are hard + making them accessible 02:24 Iwo's background in C++, OpenGL, and discovering JS 03:06 Sharing graphics work on the web vs native platforms 03:29 WebGPU frustrations that inspired TypeGPU 04:17 Making GPU–CPU data exchange easier with Zod-like schemas 05:01 Writing shaders in JavaScript + the unified type system 05:38 How the “use_gpu” directive works under the hood 06:05 Building a compiler that turns TypeScript into shader code 07:00 Type inference, primitives, structs, and TypeScript magic 08:21 Leveraging existing tooling via Unplugin + bundler integration 09:15 How TypeGPU extracts ASTs and generates TinyEST metadata 10:10 Runtime shader generation vs build-time macros 11:07 How the AST is traversed + maintaining transparency in output 11:43 Example projects like Jelly Shader and community reception 12:05 Brought to you by Sentry.io 12:30 Does TypeGPU replace 3JS? How it fits the existing ecosystem 13:20 Low-level control vs high-level abstractions 14:04 Upcoming Three.js integration – plugging TypeGPU into materials compute shaders 15:34 Making GPU development more approachable 16:26 Docs, examples, and the philosophy behind TypeGPU documentation 17:03 Building features by building examples first 18:13 Using examples as a test suite + how docs shape API design 19:00 Docs as a forcing function for intuitive APIs 20:21 GPU for AI – browser inference and future abstractions 21:11 How AI examples inform new libraries (noise, inference, etc.) 21:57 Keeping the core package small and flexible 22:44 Building “TypeGPU AI”-style extensions without bloating the core 23:07 The cost of AI examples and building everything from scratch 23:41 Standard library design and future of the ecosystem 24:04 Closing thoughts from Iwo – OSS, GPU renaissance, and encouragement 24:34 Sick Picks & Shameless Plugs Sick Picks Iwo: Perogies Shameless Plugs Iwo: Syntax Podcast Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

Topics covered in this episode: Advent of Code starts today Django 6 is coming Advanced, Overlooked Python Typing codespell Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: Advent of Code starts today A few changes, like 12 days this year, which honestly, I'm grateful for. See also: elf: Advent of Code CLI helper for Python Michael #2: Django 6 is coming Expected December 2025 Django 6.0 supports Python 3.12, 3.13, and 3.14 Built-in support for the Content Security Policy (CSP) standard is now available, making it easier to protect web applications against content injection attacks such as cross-site scripting (XSS). The Django Template Language now supports template partials, making it easier to encapsulate and reuse small named fragments within a template file. Django now includes a built-in Tasks framework for running code outside the HTTP request–response cycle. This enables offloading work, such as sending emails or processing data, to background workers. Email handling in Django now uses Python's modern email API, introduced in Python 3.6. This API, centered around the email.message.EmailMessage class Brian #3: Advanced, Overlooked Python Typing get_args, TypeGuard, TypeIs, and more goodies Michael #4: codespell Learned from this PR for the Talk Python book. Fix common misspellings in text files. It's designed primarily for checking misspelled words in source code (backslash escapes are skipped), but it can be used with other files as well. It does not check for word membership in a complete dictionary, but instead looks for a set of common misspellings. Therefore it should catch errors like "adn", but it will not catch "adnasdfasdf". It shouldn't generate false-positives when you use a niche term it doesn't know about. Extras Brian: Is mkdocs maintained? Hatch 1.16 Michael: Follow up on tach from Gerben Dekker: tach has been unmaintained for a bit but is not anymore. It was the main product from Gauge which is a Y combinator startup that pivoted to something unrelated and abandoned tach. However, https://github.com/DetachHead forked it but now got access to the main repo and has committed to maintaining it. ruff analyze graph is fully independent of tach - we actually started to look into alternatives for tach when it became unmaintained and then found ruff analyze graph. For our use case, with just a bit of manipulation on top of ruff analyze graph we replaced our use of deptry (which was slower - and I try to be careful depending on one-man projects). A Review of Michael Kennedy's book, “Talk Python in Production” - Thanks Doug Joke: NoaaS

In this episode, I'm talking with Vincent Warmerdam about treating LLMs as just another API in your Python app, with clear boundaries, small focused endpoints, and good monitoring. We'll dig into patterns for wrapping these calls, caching and inspecting responses, and deciding where an LLM API actually earns its keep in your architecture. Episode sponsors Seer: AI Debugging, Code TALKPYTHON NordStellar Talk Python Courses Links from the show Vincent on X: @fishnets88 Vincent on Mastodon: @koaning LLM Building Blocks for Python Co-urse: training.talkpython.fm Top Talk Python Episodes of 2024: talkpython.fm LLM Usage - Datasette: llm.datasette.io DiskCache - Disk Backed Cache (Documentation): grantjenks.com smartfunc - Turn docstrings into LLM-functions: github.com Ollama: ollama.com LM Studio - Local AI: lmstudio.ai marimo - A Next-Generation Python Notebook: marimo.io Pydantic: pydantic.dev Instructor - Complex Schemas & Validation (Python): python.useinstructor.com Diving into PydanticAI with marimo: youtube.com Cline - AI Coding Agent: cline.bot OpenRouter - The Unified Interface For LLMs: openrouter.ai Leafcloud: leaf.cloud OpenAI looks for its "Google Chrome" moment with new Atlas web browser: arstechnica.com Watch this episode on YouTube: youtube.com Episode #528 deep-dive: talkpython.fm/528 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Welcome to this classic episode. Classics are my favorite episodes from the past 10 years, published once a month. These are N of 1 conversations with N of 1 people. Palmer Luckey is a relentless builder and original thinker. He founded Oculus, bringing virtual reality to the mainstream, and is now reshaping the future of defense and technology with Anduril. I hope you enjoy this conversation. Palmer is the founder of Anduril, which makes next-generation military technology for the US and its allies. Since bringing the company to life in 2017, Palmer and Anduril have disrupted the established order in the Defense industry. Prior to Anduril, Palmer founded Oculus VR, a virtual reality business that he sold to Facebook for $2 billion. Palmer is only in his early 30s, but he has already experienced more than most people will in a 40-year career. We talk about innovation, invention, differentiated thinking, and so much more. Please enjoy this great discussion with Palmer Luckey. Listen to Patrick's Business Breakdowns with Anduril CEO. For the full show notes, transcript, and links to mentioned content, check out the episode page here. ----- This episode is brought to you by WorkOS. WorkOS is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. With a single API, developers can implement essential enterprise capabilities that typically require months of engineering work. By handling the complex infrastructure of enterprise features, WorkOS allows developers to focus on their core product while meeting the security and compliance requirements of Fortune 500 companies. Visit WorkOS to Transform your application into an enterprise-ready solution in minutes, not months. ----- Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.  Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. Follow us on Twitter: @patrick_oshag | @joincolossus Show Notes (00:00:00) Welcome to Invest Like the Best (00:01:15) Meet Palmer Luckey (00:02:03) The importance of synthetic long-chain hydrocarbon fuel (00:08:12) Ranking America's potential for innovation (00:11:18) Why there aren't more ⁠Thiel Fellowships⁠ (00:13:31) The principles that motivate and drive him (00:16:56) What it has been like working in the world of defense after the attack on Israel (00:19:09) Surprising lessons learned when building a large company (00:22:37) How to approach a new field initially (00:27:20) Meeting other out-of-the-box thinkers (00:31:46) Inventors working backward from existing systems versus forward from their ideals (00:33:26) The most pressing issue in national security (00:39:36) What matters most for America from a defense perspective (00:42:33) How to determine which problems to prioritize (00:48:59) Lessons learned from working with AI (00:55:56) How Apple is shaping the future of VR (01:00:11) Which videogame a prospective employee should excel at (01:02:41) Why ⁠Oculus⁠ was so successful in marketing (01:09:48) The kindest thing