Podcasts about Rag

SPONSORS: - Upgrade your denim game with Rag & Bone!. Get 20% off sitewide with code NOTTODAY at www.rag-bone.com #ragandbonepod - Take advantage of HexClad's Best Sale of the Year and GET UP TO 52% Off by going to https://hexclad.com/NOTTODAY #hexcladpartner - Control Body Odor ANYWHERE with @shop.mando and get 20% off + free shipping with promo code NOTTODAY at https://shopmando.com! #mandopod - New players play $5 and get 500 total Spins over 10 days on Cash Eruption games! New customers sign up using https://dkng.co/nottoday or through my promo code NOTTODAY. #DKPartner This week on Not Today Pal, Jamie and Rob dive into the chaos of modern dating: from using a gift card on the first date (power move or

Sherif Mansour, Head of AI at Atlassian, discusses bridging AI agents with massive-scale enterprise software deployment, drawing insights from Atlassian's millions of non-technical users. He shares his framework for avoiding "AI Slop" using Taste, Knowledge, and Workflow, and explains Atlassian's "Teamwork Graph" for complex enterprise queries beyond RAG. The conversation also explores the evolving relationship between AI and UI, and the shift from humans as workers to architects of AI-driven processes. This episode offers practical wisdom for both AI engineers and business leaders navigating the future of AI-enabled organizations. Sponsors: Framer: Framer is the all-in-one tool to design, iterate, and publish stunning websites with powerful AI features. Start creating for free and use code COGNITIVE to get one free month of Framer Pro at https://framer.com/design Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive PRODUCED BY: https://aipodcast.ing CHAPTERS: (00:00) About the Episode (03:56) Atlassian's AI Vision (08:27) Trust, Authenticity, and Slop (14:10) Taste, Knowledge, and Workflow (Part 1) (17:33) Sponsors: Framer | Tasklet (20:14) Taste, Knowledge, and Workflow (Part 2) (Part 1) (29:51) Sponsor: Shopify (31:47) Taste, Knowledge, and Workflow (Part 2) (Part 2) (31:48) Technicals: RAG vs. Graphs (40:48) Forgetting, Cost, and Optimization (52:28) The Model Commoditization Debate (55:12) The Future of AI Interfaces (01:02:44) How AI Changes SaaS (01:09:43) Debating the One-Person Unicorn (01:16:17) Becoming a Workflow Architect (01:21:39) The Browser for Work (01:33:23) How Leaders Drive Adoption (01:39:26) Conclusion: Just Go Tinker (01:40:08) Outro SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

This episode features a conversation with Cecilia Ziniti, Co-Founder and CEO of GC.AI. Cecilia traces her career from early the early days of the internet to founding an AI-driven legal platform for in-house counsel. Cecilia shares her journey, starting as a paralegal at Yahoo in the early 2000s, working on nascent legal issues related to the internet. She discusses her time at Morrison & Foerster and her role at Amazon, where she was an early member of the Alexa team, gaining deep insight into AI's potential before the rise of modern large language models (LLMs). The core discussion centers on the creation of GC AI, a legal AI tool specifically designed for in-house counsel. Cecilia explains why general LLMs like ChatGPT are insufficient for professional legal work—lacking proper citation, context, and security/privilege protections. She highlights the app's features, including enhanced document analysis (RAG implementation), a Word Add-in, and workflow-based playbooks to deliver accurate, client-forward legal analysis. The episode also touches on the current state of legal tech, the growing trend of bringing legal work in-house, and the potential for AI to shift the dynamics of the billable hour.  

In this episode of "Alter Everything," we sit down with Andrew Merrill, Alteryx product specialist and advocate, to explore best practices for integrating AI and LLMs into data analytics processes. Some topics we discuss include proven design patterns for generative AI, such as feedback loops, routing, and RAG architectures, and learn how to avoid common pitfalls like token overuse and data governance challenges. Andrew shares real-world use cases, tips for leveraging Alteryx Co-pilot, and strategies for prompt engineering to maximize workflow efficiency. Panelists: Andrew Merrill, Alteryx Consultant - @CoG, LinkedInMegan Bowers, Sr. Content Manager @ Alteryx - @MeganBowers, LinkedInShow notes: Alteryx Gen AI ToolsAlteryx Co-pilotAlteryx Inspire Interested in sharing your feedback with the Alter Everything team? Take our feedback survey here!This episode was produced by Megan Bowers, Mike Cusic, and Matt Rotundo. Special thanks to Andy Uttley for the theme music.

Chris & Gemma built a 7-figure agency by saying NO to 90% of clientsChris walked into a client meeting. Got the job brief. Then said "No way."The client looked at him like he was insane."You haven't shown me the office. I don't know your team. I can't work on this job."She'd just told him they were more expensive than every other agency.He didn't care.This is how Chris and Gemma built Mixos - a husband-and-wife recruitment agency that operates completely backwards.They REFUSE to take briefs over email. They WON'T work with clients who rush them. They'd literally rather go bankrupt than cut their fees.And somehow? Rookies from retail are billing £50k+ quarters. They've grown to 15 people in 18 months. Their LinkedIn DMs are full of warm leads.In this episode:Why they lost one job last month and Chris "felt like someone stuck a knife in him"The cocktails-in-Mallorca conversation that merged two agencies during a pandemicHow they got a psychology graduate with zero experience to £53k in 90 daysBuilding a 400-person local community that makes cold calling irrelevantWhy they walked away from their biggest client (and replaced it with 5 better ones)The "blueprint everything first" strategy that stops quality diluting as you scaleWhat happens when you tell a client, "I can't help you" in the first meetingThis isn't about growth hacks or AI tools or scaling fast.This is about two people who set impossible standards, refuse to compromise, and somehow built an agency where saying NO is their superpower.For every recruiter who's tired of competing on price and wondering if there's another way.__________________________________________Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, the AI-first recruitment platform built for modern agencies.It doesn't only track CVs and calls. It remembers everything. Every email, every interview, every conversation. Instantly searchable, always available. And now, it's entering a whole new era.With Atlas 2.0, you can ask anything and it delivers. With Magic Search, you speak and it listens. It finds the right candidates using real conversations, not simply look for keywords.Atlas 2.0 also makes business development easier than ever. With Opportunities, you can track, manage and grow client relationships, powered by generative AI and built right into your workflow.Need insights? Custom dashboards give you total visibility over your pipeline. And that's not theory. Atlas customers have reported up to 41% EBITDA growth and an 85% increase in monthly billings after adopting the platform.No admin. No silos. No lost info. Nothing but faster shortlists, better hires and more time to focus on what actually drives revenue.Atlas is your personal AI partner for modern recruiting.Don't miss the future of recruitment. Get started with Atlas today and unlock your exclusive RAG listener offer at https://recruitwithatlas.com/therag/__________________________________________Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn.Spending thousands on Recruiter licences.Building connections. Posting content. Growing networks.But here's the question almost no one can answer:How much revenue is LinkedIn actually bringing into your business?Most founders have thousands of connections but no clear process to turn that attention into cash.That's the problem we solve.At Hoxo, we help recruitment founders build predictable revenue systems on LinkedIn, not just noise or vanity metrics.Our clients are turning LinkedIn into...

Dell Technologies has unveiled enhancements to the Dell AI Factory designed to simplify and accelerate the enterprise AI journey. These portfolio additions boost performance and automation for AI workloads while removing bottlenecks, delivering greater control with integrated, resilient on-premises infrastructure. Why it matters In today's digital landscape, organisations increasingly rely on AI to stay competitive and foster innovation. The momentum is clear with 85 percent of enterprises planning to move AI on-premises within the next 24 months. Seventy-seven per cent of those seeking AI are looking for one holistic infrastructure vendor to provide capabilities across their AI journey. Dell's expanded portfolio addresses these needs with the industry's broadest end-to-end AI portfolio designed to streamline AI adoption and deliver impactful results. Simplified and automated AI journey The Dell Automation Platform, now expanded to the Dell AI Factory, will deliver smarter, more automated experiences by deploying validated, optimised solutions with a secure framework. This approach will produce repeatable outcomes, eliminate guesswork, and help unlock the full potential of AI-driven use cases across Dell's ecosystem of technology partners. Key advancements include: Software-driven tools like the AI code assistant with Tabnine and agentic AI platform with Cohere North are now automated, getting AI workloads into production faster, streamlining operations and enhancing scalability. Dell Professional Services provide turnkey interactive AI use case pilots using real customer data to validate business value ahead of scaled investments. These expert-led pilots offer a hands-on preview for experimentation with clear success metrics and KPIs, delivering tangible ROI. Breakthrough performance and efficiency for AI workloads Enhanced Data Management: How organisations manage, secure and scale that data will separate the winners from the laggards. Updates to Dell PowerScale and Dell ObjectScale, the Dell AI Data Platform's storage engines, boost performance, scalability, and data discovery capabilities. Dell PowerScale will soon be available as an independent software license on qualified Dell PowerEdge servers like the Dell PowerEdge R7725xd. This news is the latest in Dell software-driven storage innovation following the announcement of a new software-defined Dell ObjectScale. These new Dell PowerScale and Dell ObjectScale configurations will help organisations like cloud service providers realise even greater AI performance while having the flexibility to adopt the latest server and networking technologies to meet infrastructure needs. Dell PowerScale parallel NFS (pNFS) support with Flexible File Layout will enable two-way communication between the metadata server and client, allowing for better parallel distribution of data across multiple nodes in a PowerScale cluster. Deliver significant throughput, performance gains and linear scalability with parallel I/O across multiple pathways. This update is designed to provide increased parallelism, delivering massive scalability and throughput tailored for demanding AI workflows. Dell ObjectScale AI-Optimised Search offers two complementary AI-optimised search capabilities for Dell ObjectScale storage - S3 Tables and S3 Vector. These two specialised APIs provide high-speed access to complex data stored directly on ObjectScale to support analytics and key AI workloads like inferencing and retrieval-augmented generation (RAG), empowering faster decision-making and easier storage, retrieval and search of expanding datasets. PowerEdge Innovations: Dell PowerEdge servers provide the foundation for enterprise AI, delivering faster training, distributed inference and reduced time to insights - all while offering flexible cooling options to align with diverse enterprise strategies: Dell PowerEdge XE9785 and XE9785L are purpose-built for next-generation AI and HPC workloads. The air-cooled XE97...

Dive deep into the transformative power of Generative AI in the public safety sector with Chad Brothers, Vice President for Emergency Services Programs at Viiz Communications, on this episode of Cloud and Clear! Viiz Communications is addressing the critical challenges faced by 911 centers (PSAPs), including a significant staffing crisis and the distraction caused by high volumes of non-emergency calls.  Learn how their solution uses Gen AI with conversational "playbooks" and a Retrieval-Augmented Generation (RAG) approach to efficiently triage and respond to non-urgent inquiries. Chad Brothers explains how this intelligent routing lessens the workload on human telecommunicators, allowing them to focus on emergencies, and details the future plans to automate into CAD systems and integrate spatial data. Key Takeaways: Viiz Communications is an emergency services solutions provider, supporting call centers and non-emergency solutions in the public safety space.  Gen AI provides a technology solution to the staffing crisis and high volume of non-emergency calls at 911 centers. The solution uses playbooks and a RAG approach to formulate accurate, generative responses from public and non-public data.  It improves telecommunicator quality of life by reducing non-emergency call volume and context switching. True emergencies that come through administrative lines are immediately filtered out and follow a deterministic flow to a human 911 agent. Tune in to discover how AI is enhancing service and support for our telecommunicators and communities! Join us for more content by liking, sharing, and subscribing! Connect with SADA & Viiz Communications: Learn more about SADA: https://sada.com/cloud-and-clear/  Explore Viiz Communications: https://viiz.com/  Learn more about ViizVital: https://viiz.com/viizviital  Read our Viiz Communications case study: https://sada.com/customer-story/viiz-communications-launches-next-generation-911-call-solution-on-google-cloud-ccaas-with-sadas-help/  Host: Chad Johnson, Director of AI Development at Insight Guest: Chad Brothers, Vice President of Emergency Services Programs at Viiz Communications  

Kristy Hollingshead, associate director of data science at Further, joins host Andrew Miller to discuss putting GenAI to work with RAG - including the importance of RAG for building AI applications, minimizing hallucinations, the practice of red teaming, and what's next beyond RAG. Please visit Putting GenAI to Work with Business Data: Driving Value and Managing Risk for more information on Kristy's session at the TDWI December Virtual Summit. ____________ More information: ·       TDWI Conferences: https://bit.ly/3XqBhGH ·       TDWI Virtual Summits: https://bit.ly/31HJ2xr ·       Seminars: https://bit.ly/3WxQPr4 ·       More Speaking of Data Episodes: https://bit.ly/3JsQPWo Follow Us on: ·       LinkedIn - https://bit.ly/42zCZZB ·       Facebook - https://bit.ly/49uej7j ·       Instagram - https://bit.ly/3HM8x57 ·       X - https://bit.ly/3SsYu9P

AI Daily News Rundown November 15 2025:Tune in at https://podcasts.apple.com/us/podcast/ai-daily-news-rundown-anthropic-disrupts-ai-orchestrated/id1684415169?i=1000736811381Welcome to AI Unraveled, Your daily briefing on the real world business impact of AI

Send us a text I denne episoden møter vi Professor Michael Alexander Riegler, Head of AI ved Simula. Vi forklarer RAG, når AI-agenter gir verdi, og hvordan LLM-er bør kvalitetssikres i offentlig sektor. Riegler deler innsikt fra helse og ansvarlig KI. Programledere: Jens Christian Bang og Dag Rustad. Hva er RAG – når gir det verdi, og hvilke arkitekturvalg finnesFra LLM til KI-agenter – hva skiller verktøy, assistenter og autonome systemerVerktøykasse for å bygge agenter – dataflytEgen LLM vs. åpen kildekode vs. proprietær – kost/nytte og driftHvem er Simula – rolle, forskning og samarbeidLLM i offentlig sektor – behovet for et nasjonalt kvalitetssikringsregimeDigitaliseringspådden lages av Already On og CW.no. Besøk oss på digitaliseringspodden.alreadyon.com. Du finner Digitaliseringspådden på alle plattformer – lytt via Spotify, Apple Podcasts eller YouTube Podcasts.

Ryan is a current student at Parsity who build an app for his employer, Smoothie King, to suggest drinks in a chat interface using a powerful and lesser-known AI technology: RAG.RAG stands for retrieval augmented generation. Basically, providing information (like smoothie recipes) to an AI model so it can return a highly specific response.Ryan breaks down how he finds the time to build side projects like this and how he built this app.Want to build your own AI-powered app? Check out this project: parsity.io/ai-with-ragConnect with Ryan here: https://www.linkedin.com/in/rhardin378/Send us a textShameless Plugs

Reaktionen zu Wehrdienst - Pressekonferenz zu Christkindlmarkt - Landtag: Warum war es eine "etwas andere Sitzung"? - Start-Up der RAG soll Kontrolle der Wasserqualität vereinfachen

With three rounds left of the 2025 season, Oscar Piastri is still in contention to become Formula 1 World Champion for the first time. So what's it like being in the thick of an F1 title fight with so much at stake? Speaking to Tom Clarkson before the Sao Paulo Grand Prix, Oscar opens up about the pressure of a title battle and why fighting a teammate is different to racing against any other driver. He also discusses whether his relationship with teammate Lando Norris has changed this year and how he feels McLaren have handled the challenge of treating them both equally. It's easy to forget that this is only Oscar's third season as an F1 driver. With seven wins, seven podiums and five pole positions, he's taken a huge leap forward. What exactly did he work on over the winter to make so much progress this year? And how are race engineer Tom Stallard, manager Mark Webber and new physio Artturi Simila all helping his development? As well as reflecting on the highs, Oscar also talks about dealing with setbacks in Australia, at Silverstone and in Azerbaijan, which is good insight into how he'll bounce back from a difficult weekend in Brazil. It's All To Drive For in 2025. Be there! Book your seat for a Grand Prix this season at tickets.formula1.com Listen to more official F1 podcasts Every race analysed on F1 Nation Expert answers to your questions on F1 Explains THIS EPISODE IS SPONSORED BY... SelectQuote: Get the right life insurance for you, for less, and save more than 50% at selectquote.com/beyondthegrid Rag & Bone: Upgrade your denim game with Rag & Bone! Get 20% off sitewide with code GRID at www.rag-bone.com 

Mick Donaghy: How he built $1.4M from $7K (after his partnership collapsed) Mick Donaghy's mother died when he was in his twenties.Life's too short became his operating system.He left Ireland. Moved to New Zealand. Became a top-billing recruiter! A few years later, he got his shot at ownership. A partnership to launch an Australian business for the agency he worked. For many reasons, this partnership didn't work, so Mick paid back his business partner and walked away with $7,000 in his bank account.No business. No plan B.This time, he was doing it alone.GEDON was born - named after his Mum.Ultra-niche: quantity surveying and cost management. One discipline. Total focus.12 months later: $1.4M AUD in billings.65 placements. One person every three days.But here's what makes Mick different.He's not building an empire.- he's building freedom!Currently has 9 people, 5 offshore making 40%+ profit margins.Last week, he won 3 new clients from his personal brand. Zero cold calls.He just bought a 100-year-old house in Belfast. Cash.He drives an old Toyota Corolla, does 30 minutes in the sauna daily and is two and a half years into rebuilding his relationship with alcohol.He's now set a new and incredible target: 20-hour work week. $300-400K profit annually.This week on The RAG Podcast, Mick tells the full story.We cover:The partnership in Australia that COVID nearly destroyedHow he started Gedon with $7K and built it to $1.4M in year oneWhy ultra-niche made his business borderlessThe personal brand strategy that replaced cold callingWhy he refuses to scale headcountHis sobriety journey and the 20-hour work week planThis isn't about scaling fast.It's about a man who lost his mom young, tried a partnership that collapsed, and rebuilt everything from $7,000 into a million-dollar business that gives him his life back.No investor decks. No growth-at-all-costs.Just freedom over headcount.If you've ever wondered whether there's another way to build a business—one that doesn't trap you -this episode has the blueprint.__________________________________________Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, the AI-first recruitment platform built for modern agencies.It doesn't only track CVs and calls. It remembers everything. Every email, every interview, every conversation. Instantly searchable, always available. And now, it's entering a whole new era.With Atlas 2.0, you can ask anything and it delivers. With Magic Search, you speak and it listens. It finds the right candidates using real conversations, not simply look for keywords.Atlas 2.0 also makes business development easier than ever. With Opportunities, you can track, manage and grow client relationships, powered by generative AI and built right into your workflow.Need insights? Custom dashboards give you total visibility over your pipeline. And that's not theory. Atlas customers have reported up to 41% EBITDA growth and an 85% increase in monthly billings after adopting the platform.No admin. No silos. No lost info. Nothing but faster shortlists, better hires and more time to focus on what actually drives revenue.Atlas is your personal AI partner for modern recruiting.Don't miss the future of recruitment. Get started with Atlas today and unlock your exclusive RAG listener offer at https://recruitwithatlas.com/therag/__________________________________________Episode Sponsor: HoxoEvery recruitment founder is...

AI Daily News Rundown November 13 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn today's daily AI News Rundown:

Czy sztuczna inteligencja może naprawdę odciążyć lekarzy i dać im więcej czasu dla pacjentów?W tym odcinku prawdzamy, jak AI zmienia codzienność w gabinetach i szpitalach.Gościmy Huberta Zielińskiego, współtwórcę Cora.AI – polskiego startupu, który tworzy inteligentnego asystenta lekarza.Cora słucha rozmowy z pacjentem i sama tworzy notatkę medyczną, dzięki czemu lekarze mogą skupić się na tym, co najważniejsze – na człowieku.O czym porozmawiamy?– jak działa system speech-to-note i czym różni się od zwykłej transkrypcji,– dlaczego bezpieczeństwo danych medycznych to jedno z największych wyzwań,– jak AI pomaga zapobiegać wypaleniu zawodowemu lekarzy,– i dlaczego to nie jest science fiction, tylko realne wdrożenia w polskich szpitalach.Zobaczycie, jak powstaje technologia, która nie zastępuje człowieka, lecz oddaje mu czas.Jeśli AI ma zmienić medycynę, to tylko po to, by uczynić ją bardziej ludzką.Świetnie — oto pełna, gotowa lista rozdziałów do wklejenia na YouTube lub Spotify, stworzona na podstawie nowej transkrypcji odcinka

Dave has something to say about the firing of Mavs GM Nico Harrison, Dave is thinking about doing this activity with his son, LSU is trying to avoid paying Brian Kelly's buyout, and we have an MLB gambling indictment. Support us on Patreon and receive weekly episodes for as low $5 per month: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.patreon.com/circlingbackpodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Watch all of our full episodes on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.youtube.com/washedmedia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Shop Washed Merch: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.washedmedia.shop⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • (0:00) Fun & Easy Banter • (12:40) Nico GONE • (31:35) Does My Kid Need to do this Activity? • (46:25) LSU Trying Not to Pay Brian Kelly • (59:45) MLB Gambling Indictment Support This Episode's Sponsors: Fair Harbor Clothing: Head to ⁠https://www.fairharborclothing.com/⁠ and use code CIRCLING20 for 20% OFF your full price order now through 11/15 Rag & Bone: Upgrade your denim game with Rag & Bone! Get 20% off your entire order with code STEAM at ⁠http://rag-bone.com/⁠ #ragandbonepod Squarespace: Check out ⁠⁠https://squarespace.com/steam⁠⁠ for a free trial, and when you're ready to launch, use OFFER CODE: STEAM to save 10% off your first purchase of a website or domain. Rocket Money: Cancel your unwanted subscriptions and reach your financial goals faster with Rocket Money. Go to ⁠⁠https://rocketmoney.com/circling⁠⁠ today. Learn more about your ad choices. Visit megaphone.fm/adchoices

The University of Texas at Austin has until next week to respond to a controversial compact sent by the Trump Administration in early October, and some students are very opposed to the idea. Under the proposed deal, the White House would offer UT greater access to federal funds in exchange for implementing policies outlined by the administration. Several schools have already rejected the offer. Host Nikki DaVaughn sits down with Ava Hosseini and Kira Small, co-editors-in-chief of The Rag, a student-run underground magazine, to hear the two seniors' take on how the proposed compact could reshape academic freedom, student life, and the broader political climate in Austin. Plus, is the privately-funded University of Austin actually more ideologically neutral than UT? Some say yes.  Want some more Austin news? Then make sure to sign up for our Hey Austin newsletter.  And don't forget– you can support this show and get great perks by becoming a City Cast Austin Neighbor at membership.citycast.fm  Follow us @citycastaustin You can also text us or leave a voicemail.  Interested in advertising with City Cast? Find more info HERE  Learn more about the sponsors of this November 11th episode: DUER - Get 15% off at shopduer.com/ccaustin Adios - Use code CITYCAST for 50% off New Waterloo - Trick Hat Workway Babbel - Get up to 55% off at Babbel.com/CITYCAST Cozy Earth - Use code COZYAUSTIN for 40% off best-selling sheets, towels, pajamas, and more.

Tyler Martin, Senior Director of Enterprise Security Engineering & Operations at FanDuel, reflects on revolutionizing security operations by replacing traditional analyst tiers with security engineers supported by custom AI agents. Tyler shares the architecture behind SAGE, FanDuel's phishing automation system, and explains how his team progressed from human-in-the-loop validation to fully autonomous triage through bronze-silver-gold maturity stages.  The conversation explores practical challenges like context enrichment, implementing user personas connected to IDP and HRIS systems, and choosing between RAG versus CAG models for knowledge augmentation. Tyler also discusses shifts in detection strategy, arguing for leaner detection catalogs with just-in-time, query-based rules over maintaining point-in-time codified detections that no longer address active risks. Topics discussed: Restructuring security operations teams to include only security engineers while AI agents handle traditional level 1-3 triage work. Building Security Analysis and Guided Escalation, an AI-powered phishing automation system that reduced manual ticket volume. Implementing bronze-silver-gold maturity stages for AI triage: manual validation, automated closures with oversight, and full autonomous operations. Enriching AI agents with organizational context through connections to IDP systems, HRIS platforms, and user behavior analytics. Creating user personas that encode access patterns, permissions, security groups, and typical behaviors to improve AI decision-making accuracy. Designing incident response automation that spins up Slack channels, Zoom bridges, recordings, and comprehensive documentation through simple commands. Eliminating 90% of missing PIR action items through automated documentation capture and stakeholder tagging in Confluence. Shifting detection strategy from maintaining large MITRE-mapped catalogs to just-in-time query-based rules written by AI agents. Balancing signal volume and enrichment data against inference costs while avoiding context rot that degrades LLM performance. Evaluating RAG versus CAG models for knowledge augmentation and exploring multi-agent architectures with supervisory oversight layers.  Listen to more episodes:  Apple  Spotify  YouTube Website

The boys recap their Weekends in Fun, including Randy's time at the Ren Fair, Bryan Johnson did 5 grams of shrooms, Dave has a "Would you rather?" for Texas fan Dillon, and Dillon watched 'House of Dynamite.' Support us on Patreon and receive weekly episodes for as low $5 per month: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.patreon.com/circlingbackpodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Watch all of our full episodes on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.youtube.com/washedmedia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Shop Washed Merch: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.washedmedia.shop⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ • (0:00) Fun & Easy Banter • (15:35) Recapping TWIF • (37:10) Bryan Johnson is Killing Shroom Culture • (53:00) Texas Fan "Would You Rather?" • (1:05:35) Dillon Watched 'House of Dynamite' Support This Episode's Sponsors: Fair Harbor Clothing: Head to https://www.fairharborclothing.com/ and use code CIRCLING20 for 20% OFF your full price order now through 11/15 Rag & Bone: Upgrade your denim game with Rag & Bone! Get 20% off your entire order with code STEAM at http://rag-bone.com/ #ragandbonepod Squarespace: Check out ⁠https://squarespace.com/steam⁠ for a free trial, and when you're ready to launch, use OFFER CODE: STEAM to save 10% off your first purchase of a website or domain. Rocket Money: Cancel your unwanted subscriptions and reach your financial goals faster with Rocket Money. Go to ⁠https://rocketmoney.com/circling⁠ today. Learn more about your ad choices. Visit megaphone.fm/adchoices

Jed Borovik, Product Lead at Google Labs, joins Latent Space to unpack how Google is building the future of AI-powered software development with Jules. From his journey discovering GenAI through Stable Diffusion to leading one of the most ambitious coding agent projects in tech, Borovik shares behind-the-scenes insights into how Google Labs operates at the intersection of DeepMind's model development and product innovation. We explore Jules' approach to autonomous coding agents and why they run on their own infrastructure, how Google simplified their agent scaffolding as models improved, and why embeddings-based RAG is giving way to attention-based search. Borovik reveals how developers are using Jules for hours or even days at a time, the challenges of managing context windows that push 2 million tokens, and why coding agents represent both the most important AI application and the clearest path to AGI. This conversation reveals Google's positioning in the coding agent race, the evolution from internal tools to public products, and what founders, developers, and AI engineers should understand about building for a future where AI becomes the new brush for software engineering. Chapters 00:00:00 Introduction and GitHub Universe Recap 00:00:57 New York Tech Scene and East Coast Hackathons 00:02:19 From Google Search to AI Coding: Jed's Journey 00:04:19 Google Labs Mission and DeepMind Collaboration 00:06:41 Jules: Autonomous Coding Agents Explained 00:09:39 The Evolution of Agent Scaffolding and Model Quality 00:11:30 RAG vs Attention: The Shift in Code Understanding 00:13:49 Jules' Journey from Preview to Production 00:15:05 AI Engineer Summit: Community Building and Networking 00:25:06 Context Management in Long-Running Agents 00:29:02 The Future of Software Engineering with AI 00:36:26 Beyond Vibe Coding: Spec Development and Verification 00:40:20 Multimodal Input and Computer Use for Coding Agents

Why does an AI that brilliantly generates code suddenly fail at basic math? The answer explains why your LLM will fail when you least expect it.In this episode, Emmanuel Maggiori, author of “Smart Until It's Dumb” and “The AI Pocket Book,” cuts through the AI hype to reveal what LLMs actually do and, more importantly, what they can't. Drawing from his experience building AI systems and witnessing multiple AI booms and busts, Emmanuel explains why machine learning works brilliantly until it makes mistakes no human would ever make.He shares why businesses repeatedly fail at AI adoption, how hallucinations are baked into the technology, and what developers need to know about building reliable AI products.Whether you're implementing AI at work or concerned about your career, this conversation offers a grounded perspective on navigating the current AI wave without getting swept away by unrealistic promises.Key topics discussed:Why AI projects fail the same way repeatedlyHow LLMs work and why they brilliantly failWhy hallucinations can't be fixed with better promptsWhy self-driving cars still need human operatorsAdopting AI without falling into hype trapsHow engineers stay relevant in the AI eraWhy AGI predictions are mostly marketingBuilding valuable products in boring industriesTimestamps:(00:00:00) Trailer & Intro(00:02:32) Career Turning Points(00:06:41) Writing “Smart Until It's Dumb” and “The AI Pocket Book”(00:08:14) The History of AI Booms & Winters(00:11:34) Why Generative AI Hype is Different Than the Past AI Waves(00:13:26) AI is Smart Until It's Dumb(00:16:45) How LLM and Generative AI Actually Work(00:22:53) What Makes LLMs Smart(00:27:25) Foundational Model(00:30:01) RAG and Agentic AI(00:34:09) Tips on How to Adopt AI Within Companies(00:37:56) How to Reduce & Avoid AI Hallucination Problem(00:45:49) The Important Role of Benchmarks When Building AI Products(00:50:57) Advice for Software Engineers to Deal With AI Concerns(00:56:49) Advice for Junior Developers(00:59:34) Vibe Coders and Prompt Engineers: New Jobs or Just Hype?(01:01:55) The AGI Possibility(01:07:23) Three Tech Lead Wisdom_____Emmanuel Maggiori's BioEmmanuel Maggiori, PhD, is a software engineer and 10-year AI industry insider. He has developed AI for a variety of applications, from processing satellite images to packaging deals for holiday travelers. He is the author of the books Smart Until It's Dumb, Siliconned, and The AI Pocket Book.Follow Emmanuel:LinkedIn – linkedin.com/in/emaggioriWebsite – emaggiori.comLike this episode?Show notes & transcript: techleadjournal.dev/episodes/238.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.    Visit https://agntcy.org/ and add your support.   Why do today's LLMs forget key details over long context, and what would it take to give them real memory that scales?   In this episode of Eye on AI, host Craig Smith explores Manifest AI's Power Retention architecture and how it rethinks memory, context, and learning for modern models. We look at why transformers struggle with long inputs, how state space and retention models keep context at linear cost, and how scaling state size unlocks reliable recall across lengthy conversations, code, and documents. We also cover practical paths to retrofit existing transformer models, how in context learning can replace frequent fine tuning, and what this means for teams building agents and RAG systems.   Learn how product leaders and researchers measure true long context quality, which pitfalls to avoid when extending context windows, and which metrics matter most for success, including recall consistency, answer fidelity, task completion, CSAT, and cost per resolution. You will also hear how to design per user memory, set governance that prevents regressions, evaluate LLM as judge with human review, and plan a secure rollout that improves retrieval, multi step workflows, and agent reliability across chat, email, and voice. Stay Updated: Craig Smith on X:https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI   

Hasan Rizvi, EVP, Database Engineering, Oracle, talks to Bob Evans in this latest episode of Cloud Wars Live. They explore the launch of Oracle AI Database 26ai, the Autonomous AI Lakehouse, and breakthroughs in multi-cloud deployment. Rizvi also discusses vector search, agentic AI, and how Oracle is simplifying complex architectures for the AI era. It's a compelling look at how Oracle is reshaping enterprise data strategy for the age of AI.Oracle's Next-Gen Data StrategyThe Big Themes:AI Demands a Modern Data Foundation: As AI shifts operations from human scale to machine speed, enterprises must ask: “Is my data foundation ready?” Without intelligent data structures, comprehensive access, real‑time performance, and strong security, organizations will struggle to compete. The introduction of Oracle AI Database 26ai is positioned as that foundation. The urgency of this shift is clear: companies that delay risk being left behind.Agentic AI and Vectors Come to the Enterprise Database: Generative AI and autonomous agents require new data types and workflows. Oracle has built vector data types and vector indexes into the database so enterprises can perform similarity search, retrieval‑augmented generation (RAG) and agent workflows directly on their private data. Further, Oracle is enabling annotations (metadata) so LLMs can understand enterprise data schemas, improving accuracy. Finally, agentic workflows (AI that takes action) are supported within the database, reducing data movement, improving performance and strengthening security.Start‑Ups and Established Enterprises Both Benefit: The case study of Retraced (a fashion supply‑chain company) underscores how smaller, agile firms are using Oracle's autonomous AI database to innovate quickly: multi‑datatype support, agentic AI, automatic scaling, and reduced operational overhead. At the same time, Oracle's heritage in mission‑critical enterprise systems means large companies with massive workloads benefit from the same platform. The point: whether you're a start‑up or a Fortune 500, the difference will be how fast you move.The Big Quote: “We really believe that in in the age of AI, where you have to move much faster, you really don't have a choice but to start simplifying your environment. Otherwise, you're going to get left behind."More from Hasan Rizvi and Oracle:Connect with Hasan on LinkedIn and learn more about Oracle AI Database 26ai. Visit Cloud Wars for more.

How Do You Know If Your Enterprise Is AI-Ready? It starts with data. Can your enterprise architecture support AI workloads, RAG, or Agentic AI? For most, the answer is not yet. But with the right strategy, any data environment can get there. Then comes Governance. Do you have the right policies in place, the right people involved? Do you understand your use case well enough to know what success looks like? What You'll Learn: * How to assess whether your data architecture is AI-ready * Practical ways to modernize your systems for AI workloads * Real-world lessons from successful enterprise AI projects * Pitfalls to avoid when implementing GenAI and RAG systems * Strategies to align your data, tools, and teams for scalable AI * Discover how to align your data and strategy to make your enterprise truly AI-ready.

Dans cet épisode, Arnaud et Guillaume discutent des dernières évolutions dans le monde de la programmation, notamment les nouveautés de Java 25, JUnit 6, et Jackson 3. Ils abordent également les récents développements en IA, les problèmes rencontrés dans le cloud, et l'état actuel de React et du web. Dans cette conversation, les intervenants abordent divers sujets liés à la technologie, notamment les spécifications de Wasteme, l'utilisation des UUID dans les bases de données, l'approche RAG en intelligence artificielle, les outils MCP, et la création d'images avec Nano Banana. Ils discutent également des complexités du format YAML, des récents dramas dans la communauté Ruby, de l'importance d'une bonne documentation, des politiques de retour au bureau, et des avancées de Cloud Code. Enfin, ils évoquent l'initiative de cafés IA pour démystifier l'intelligence artificielle. Enregistré le 24 octobre 2025 Téléchargement de l'épisode LesCastCodeurs-Episode-331.mp3 ou en vidéo sur YouTube. News Langages GraalVM se détache du release train de Java https://blogs.oracle.com/java/post/detaching-graalvm-from-the-java-ecosystem-train Un article de Loic Mathieu sur Java 25 et ses nouvelles fonctionalités https://www.loicmathieu.fr/wordpress/informatique/java-25-whats-new/ Sortie de Groovy 5.0 ! https://groovy-lang.org/releasenotes/groovy-5.0.html Groovy 5: Évolution des versions précédentes, nouvelles fonctionnalités et simplification du code. Compatibilité JDK étendue: Full support JDK 11-25, fonctionnalités JDK 17-25 disponibles sur les JDK plus anciens. Extension majeure des méthodes: Plus de 350 méthodes améliorées, opérations sur tableaux jusqu'à 10x plus rapides, itérateurs paresseux. Améliorations des transformations AST: Nouveau @OperatorRename, génération automatique de @NamedParam pour @MapConstructor et copyWith. REPL (groovysh) modernisé: Basé sur JLine 3, support multi-plateforme, coloration syntaxique, historique et complétion. Meilleure interopérabilité Java: Pattern Matching pour instanceof, support JEP-512 (fichiers source compacts et méthodes main d'instance). Standards web modernes: Support Jakarta EE (par défaut) et Javax EE (héritage) pour la création de contenu web. Vérification de type améliorée: Contrôle des chaînes de format plus robuste que Java. Additions au langage: Génération d'itérateurs infinis, variables d'index dans les boucles, opérateur d'implication logique ==>. Améliorations diverses: Import automatique de java.time.**, var avec multi-assignation, groupes de capture nommés pour regex (=~), méthodes utilitaires de graphiques à barres ASCII. Changements impactants: Plusieurs modifications peuvent nécessiter une adaptation du code existant (visibilité, gestion des imports, comportement de certaines méthodes). **Exigences JDK*: Construction avec JDK17+, exécution avec JDK11+. Librairies Intégration de LangChain4j dans ADK pour Java, permettant aux développeurs d'utiliser n'importe quel LLM avec leurs agents ADK https://developers.googleblog.com/en/adk-for-java-opening-up-to-third-party-language-models-via-langchain4j-integration/ ADK pour Java 0.2.0 : Nouvelle version du kit de développement d'agents de Google. Intégration LangChain4j : Ouvre ADK à des modèles de langage tiers. Plus de choix de LLM : En plus de Gemini et Claude, accès aux modèles d'OpenAI, Anthropic, Mistral, etc. Modèles locaux supportés : Utilisation possible de modèles via Ollama ou Docker Model Runner. Améliorations des outils : Création d'outils à partir d'instances d'objets, meilleur support asynchrone et contrôle des boucles d'exécution. Logique et mémoire avancées : Ajout de callbacks en chaîne et de nouvelles options pour la gestion de la mémoire et le RAG (Retrieval-Augmented Generation). Build simplifié : Introduction d'un POM parent et du Maven Wrapper pour un processus de construction cohérent. JUnit 6 est sorti https://docs.junit.org/6.0.0/release-notes/ :sparkles: Java 17 and Kotlin 2.2 baseline :sunrise_over_mountains: JSpecify nullability annotations :airplane_departure: Integrated JFR support :suspension_railway: Kotlin suspend function support :octagonal_sign: Support for cancelling test execution :broom: Removal of deprecated APIs JGraphlet, une librairie Java sans dépendances pour créer des graphes de tâches à exécuter https://shaaf.dev/post/2025-08-25-think-in-graphs-not-just-chains-jgraphlet-for-taskpipelines/ JGraphlet: Bibliothèque Java légère (zéro-dépendance) pour construire des pipelines de tâches. Principes clés: Simplicité, basée sur un modèle d'exécution de graphe. Tâches: Chaque tâche a une entrée/sortie, peut être asynchrone (Task) ou synchrone (SyncTask). Pipeline: Un TaskPipeline construit et exécute le graphe, gère les I/O. Modèle Graph-First: Le flux de travail est un Graphe Orienté Acyclique (DAG). Définition des tâches comme des nœuds, des connexions comme des arêtes. Support naturel des motifs fan-out et fan-in. API simple: addTask("id", task), connect("fromId", "toId"). Fan-in: Une tâche recevant plusieurs entrées reçoit une Map (clés = IDs des tâches parentes). Exécution: pipeline.run(input) retourne un CompletableFuture (peut être bloquant via .join() ou asynchrone). Cycle de vie: TaskPipeline est AutoCloseable, garantissant la libération des ressources (try-with-resources). Contexte: PipelineContext pour partager des données/métadonnées thread-safe entre les tâches au sein d'une exécution. Mise en cache: Option de mise en cache pour les tâches afin d'éviter les re-calculs. Au tour de Microsoft de lancer son (Microsoft) Agent Framework, qui semble être une fusion / réécriture de AutoGen et de Semnatic Kernel https://x.com/pyautogen/status/1974148055701028930 Plus de détails dans le blog post : https://devblogs.microsoft.com/foundry/introducing-microsoft-agent-framework-the-open-source-engine-for-agentic-ai-apps/ SDK & runtime open-source pour systèmes multi-agents sophistiqués. Unifie Semantic Kernel et AutoGen. Piliers : Standards ouverts (MCP, A2A, OpenAPI) et interopérabilité. Passerelle recherche-production (patterns AutoGen pour l'entreprise). Extensible, modulaire, open-source, connecteurs intégrés. Prêt pour la production (observabilité, sécurité, durabilité, "human in the loop"). Relation SK/AutoGen : S'appuie sur eux, ne les remplace pas, simplifie la migration. Intégrations futures : Alignement avec Microsoft 365 Agents SDK et Azure AI Foundry Agent Service. Sortie de Jackson 3.0 (bientôt les Jackson Five !!!) https://cowtowncoder.medium.com/jackson-3-0-0-ga-released-1f669cda529a Jackson 3.0.0 a été publié le 3 octobre 2025. Objectif : base propre pour le développement à long terme, suppression de la dette technique, architecture simplifiée, amélioration de l'ergonomie. Principaux changements : Baseline Java 17 requise (vs Java 8 pour 2.x). Group ID Maven et package Java renommés en tools.jackson pour la coexistence avec Jackson 2.x. (Exception: jackson-annotations ne change pas). Suppression de toutes les fonctionnalités @Deprecated de Jackson 2.x et renommage de plusieurs entités/méthodes clés. Modification des paramètres de configuration par défaut (ex: FAIL_ON_UNKNOWN_PROPERTIES désactivé). ObjectMapper et TokenStreamFactory sont désormais immutables, la configuration se fait via des builders. Passage à des exceptions de base non vérifiées (JacksonException) pour plus de commodité. Intégration des "modules Java 8" (pour les noms de paramètres, Optional, java.time) directement dans l'ObjectMapper par défaut. Amélioration du modèle d'arbre JsonNode (plus de configurabilité, meilleure gestion des erreurs). Testcontainers Java 2.0 est sorti https://github.com/testcontainers/testcontainers-java/releases/tag/2.0.0 Removed JUnit 4 support -> ups Grails 7.0 est sortie, avec son arrivée à la fondation Apache https://grails.apache.org/blog/2025-10-18-introducing-grails-7.html Sortie d'Apache Grails 7.0.0 annoncée le 18 octobre 2025. Grails est devenu un projet de premier niveau (TLP) de l'Apache Software Foundation (ASF), graduant d'incubation. Mise à jour des dépendances vers Groovy 4.0.28, Spring Boot 3.5.6, Jakarta EE. Tout pour bien démarrer et développer des agents IA avec ADK pour Java https://glaforge.dev/talks/2025/10/22/building-ai-agents-with-adk-for-java/ Guillaume a partagé plein de resources sur le développement d'agents IA avec ADK pour Java Un article avec tous les pointeurs Un slide deck et l'enregistrement vidéo de la présentation faite lors de Devoxx Belgique Un codelab avec des instructions pour démarrer et créer ses premiers agents Plein d'autres samples pour s'inspirer et voir les possibilités offertes par le framework Et aussi un template de projet sur GitHub, avec un build Maven et un premier agent d'exemple Cloud Internet cassé, du moins la partie hébergée par AWS #hugops https://www.theregister.com/2025/10/20/aws_outage_amazon_brain_drain_corey_quinn/ Panne majeure d'AWS (région US-EAST-1) : problème DNS affectant DynamoDB, service fondamental, causant des défaillances en cascade de nombreux services internet. Réponse lente : 75 minutes pour identifier la cause profonde; la page de statut affichait initialement "tout va bien". Cause sous-jacente principale : "fuite des cerveaux" (départ d'ingénieurs AWS seniors). Perte de connaissances institutionnelles : des décennies d'expertise critique sur les systèmes AWS et les modes de défaillance historiques parties avec ces départs. Prédictions confirmées : un ancien d'AWS avait anticipé une augmentation des pannes majeures en 2024. Preuves de la perte de talents : Plus de 27 000 licenciements chez Amazon (2022-2025). Taux élevé de "départs regrettés" (69-81%). Mécontentement lié à la politique de "Return to Office" et au manque de reconnaissance de l'expertise. Conséquences : les nouvelles équipes, plus réduites, manquent de l'expérience nécessaire pour prévenir les pannes ou réduire les temps de récupération. Perspective : Le marché pourrait pardonner cette fois, mais le problème persistera, rendant les futurs incidents plus probables. Web React a gagné "par défaut" https://www.lorenstew.art/blog/react-won-by-default/ React domine par défaut, non par mérite technique, étouffant ainsi l'innovation front-end. Choix par réflexe ("tout le monde connaît React"), freinant l'évaluation d'alternatives potentiellement supérieures. Fondations techniques de React (V-DOM, complexité des Hooks, Server Components) vues comme des contraintes actuelles. Des frameworks innovants (Svelte pour la compilation, Solid pour la réactivité fine, Qwik pour la "resumability") offrent des modèles plus performants mais sont sous-adoptés. La monoculture de React génère une dette technique (runtime, réconciliation) et centre les compétences sur le framework plutôt que sur les fondamentaux web. L'API React est complexe, augmentant la charge cognitive et les risques de bugs, contrairement aux alternatives plus simples. L'effet de réseau crée une "prison": offres d'emploi spécifiques, inertie institutionnelle, leaders choisissant l'option "sûre". Nécessité de choisir les frameworks selon les contraintes du projet et le mérite technique, non par inertie. Les arguments courants (maturité de l'écosystème, recrutement, bibliothèques, stabilité) sont remis en question; une dépendance excessive peut devenir un fardeau. La monoculture ralentit l'évolution du web et détourne les talents, nuisant à la diversité essentielle pour un écosystème sain et innovant. Promouvoir la diversité des frameworks pour un écosystème plus résilient et innovant. WebAssembly 3 est sortie https://webassembly.org/news/2025-09-17-wasm-3.0/ Data et Intelligence Artificielle UUIDv4 ou UUIDv7 pour vos clés primaires ? Ça dépend… surtout pour les bases de données super distribuées ! https://medium.com/google-cloud/understanding-uuidv7-and-its-impact-on-cloud-spanner-b8d1a776b9f7 UUIDv4 : identifiants entièrement aléatoires. Cause des problèmes de performance dans les bases de données relationnelles (ex: PostgreSQL, MySQL, SQL Server) utilisant des index B-Tree. Inserts aléatoires réduisent l'efficacité du cache, entraînent des divisions de pages et la fragmentation. UUIDv7 : nouveau standard conçu pour résoudre ces problèmes. Intègre un horodatage (48 bits) en préfixe de l'identifiant, le rendant ordonné temporellement et "k-sortable". Améliore la performance dans les bases B-Tree en favorisant les inserts séquentiels, la localité du cache et réduisant la fragmentation. Problème de UUIDv7 pour certaines bases de données distribuées et scalables horizontalement comme Spanner : La nature séquentielle d'UUIDv7 (via l'horodatage) crée des "hotspots d'écriture" (points chauds) dans Spanner. Spanner distribue les données en "splits" (partitions) basées sur les plages de clés. Les clés séquentielles concentrent les écritures sur un seul "split". Ceci empêche Spanner de distribuer la charge et de scaler les écritures, créant un goulot d'étranglement ("anti-pattern"). Quand ce n'est PAS un problème pour Spanner : Si le taux d'écriture total est inférieur à environ 3 500 écritures/seconde pour un seul "split". Le hotspot est "bénin" à cette échelle et n'entraîne pas de dégradation de performance. Solutions pour Spanner : Principe clé : S'assurer que la première partie de la clé primaire est NON séquentielle pour distribuer les écritures. UUIDv7 peut être utilisé, mais pas comme préfixe. Nouvelle conception ("greenfield") : ▪︎ Utiliser une clé primaire non-séquentielle (ex: UUIDv4 simple). Pour les requêtes basées sur le temps, créer un index secondaire sur la colonne d'horodatage, mais le SHARDER (ex: shardId) pour éviter les hotspots sur l'index lui-même. Migration (garder UUIDv7) : ▪︎ Ajouter un préfixe de sharding : Introduire une colonne `shard` calculée (ex: `MOD(ABS(FARM_FINGERPRINT(order_id_v7)), N)`) et l'utiliser comme PREMIER élément d'une clé primaire composite (`PRIMARY KEY (shard, order_id_v7)`). Réordonner les colonnes (si clé primaire composite existante) : Si la clé primaire est déjà composite (ex: (order_id_v7, tenant_id)), réordonner en (tenant_id, order_id_v7). Cela aide si tenant_id a une cardinalité élevée et distribue bien. (Un tenant_id très actif pourrait toujours nécessiter un préfixe de sharding supplémentaire). RAG en prod, comment améliorer la pertinence des résultats https://blog.abdellatif.io/production-rag-processing-5m-documents Démarrage rapide avec Langchain + Llamaindex: prototype fonctionnel, mais résultats de production jugés "subpar" par les utilisateurs. Ce qui a amélioré la performance (par ROI): Génération de requêtes: LLM crée des requêtes sémantiques et mots-clés multiples basées sur le fil de discussion pour une meilleure couverture. Reranking: La technique la plus efficace, modifie grandement le classement des fragments (chunks). Stratégie de découpage (Chunking): Nécessite beaucoup d'efforts, compréhension des données, création de fragments logiques sans coupures. Métadonnées à l'LLM: L'injection de métadonnées (titre, auteur) améliore le contexte et les réponses. Routage de requêtes: Détecte et traite les questions non-RAG (ex: résumer, qui a écrit) via API/LLM distinct. Outillage Créer un serveur MCP (mode HTTP Streamable) avec Micronaut et quelques éléments de comparaison avec Quarkus https://glaforge.dev/posts/2025/09/16/creating-a-streamable-http-mcp-server-with-micronaut/ Micronaut propose désormais un support officiel pour le protocole MCP. Exemple : un serveur MCP pour les phases lunaires (similaire à une version Quarkus pour la comparaison). Définition des outils MCP via les annotations @Tool et @ToolArg. Point fort : Micronaut gère automatiquement la validation des entrées (ex: @NotBlank, @Pattern), éliminant la gestion manuelle des erreurs. Génération automatique de schémas JSON détaillés pour les structures d'entrée/sortie grâce à @JsonSchema. Nécessite une configuration pour exposer les schémas JSON générés comme ressources statiques. Dépendances clés : micronaut-mcp-server-java-sdk et les modules json-schema. Testé avec l'inspecteur MCP et intégration avec l'outil Gemini CLI. Micronaut offre une gestion élégante des entrées/sorties structurées grâce à son support JSON Schema riche. Un agent IA créatif : comment utiliser le modèle Nano Banana pour générer et éditer des images (en Java, avec ADK) https://glaforge.dev/posts/2025/09/22/creative-ai-agents-with-adk-and-nano-banana/ Modèles de langage (LLM) deviennent multimodaux : traitent diverses entrées (texte, images, vidéo, audio). Nano Banana (gemini-2.5-flash-image-preview) : modèle Gemini, génère et édite des images, pas seulement du texte. ADK (Agent Development Kit pour Java) : pour configurer des agents IA créatifs utilisant ce type de modèle. Application : Base pour des workflows créatifs complexes (ex: agent de marketing, enchaînement d'agents pour génération d'assets). Un vieil article (6 mois) qui illustre les problèmes du format de fichier YAML https://ruudvanasseldonk.com/2023/01/11/the-yaml-document-from-hell YAML est extrêmement complexe malgré son objectif de convivialité humaine. Spécification volumineuse et versionnée (YAML 1.1, 1.2 diffèrent significativement). Comportements imprévisibles et "pièges" (footguns) courants : Nombres sexagésimaux (ex: 22:22 parsé comme 1342 en YAML 1.1). Tags (!.git) pouvant mener à des erreurs ou à l'exécution de code arbitraire. "Problème de la Norvège" : no interprété comme false en YAML 1.1. Clés non-chaînes de caractères (on peut devenir une clé booléenne True). Nombres accidentels si non-guillemets (ex: 10.23 comme flottant). La coloration syntaxique n'est pas fiable pour détecter ces subtilités. Le templating de documents YAML est une mauvaise idée, source d'erreurs et complexe à gérer. Alternatives suggérées : TOML : Similaire à YAML mais plus sûr (chaînes toujours entre guillemets), permet les commentaires. JSON avec commentaires (utilisé par VS Code), mais moins répandu. Utiliser un sous-ensemble simple de YAML (difficile à faire respecter). Générer du JSON à partir de langages de programmation plus puissants : ▪︎ Nix : Excellent pour l'abstraction et la réutilisation de configuration. Python : Facilite la création de JSON avec commentaires et logique. Gros binz dans la communauté Ruby, avec l'influence de grosses boîtes, et des pratiques un peu douteuses https://joel.drapper.me/p/rubygems-takeover/ Méthodologies Les qualités d'une bonne documentation https://leerob.com/docs Rapidité Chargement très rapide des pages (préférer statique). Optimisation des images, polices et scripts. Recherche ultra-rapide (chargement et affichage des résultats). Lisibilité Concise, éviter le jargon technique. Optimisée pour le survol (gras, italique, listes, titres, images). Expérience utilisateur simple au départ, complexité progressive. Multiples exemples de code (copier/coller). Utilité Documenter les solutions de contournement (workarounds). Faciliter le feedback des lecteurs. Vérification automatisée des liens morts. Matériel d'apprentissage avec un curriculum structuré. Guides de migration pour les changements majeurs. Compatible IA Trafic majoritairement via les crawlers IA. Préférer cURL aux "clics", les prompts aux tutoriels. Barre latérale "Demander à l'IA" référençant la documentation. Prêt pour les agents Faciliter le copier/coller de contenu en Markdown pour les chatbots. Possibilité de visualiser les pages en Markdown (ex: via l'URL). Fichier llms.txt comme répertoire de fichiers Markdown. Finition soignée Zones de clic généreuses (boutons, barres latérales). Barres latérales conservant leur position de défilement et état déplié. Bons états actifs/survol. Images OG dynamiques. Titres/sections lienables avec ancres stables. Références et liens croisés entre guides, API, exemples. Balises méta/canoniques pour un affichage propre dans les moteurs de recherche. Localisée Pas de /en par défaut dans l'URL. Routage côté serveur pour la langue. Localisation des chaînes statiques et du contenu. Responsive Excellents menus mobiles / support Safari iOS. Info-bulles sur desktop, popovers sur mobile. Accessible Lien "ignorer la navigation" vers le contenu principal. Toutes les images avec des balises alt. Respect des paramètres système de mouvement réduit. Universelle Livrer la documentation "en tant que code" (JSDoc, package). Livrer via des plateformes comme Context7, ou dans node_modules. Fichiers de règles (ex: AGENTS.md) avec le produit. Évaluations et modèles spécifiques recommandés pour le produit. Loi, société et organisation Microsoft va imposer une politique de Return To Office https://www.businessinsider.com/microsoft-execs-explain-rto-mandate-in-internal-meeting-2025-9 Microsoft impose 3 jours de présence au bureau par semaine à partir de février 2026, débutant par la région de Seattle Le CEO Satya Nadella explique que le télétravail a affaibli les liens sociaux nécessaires à l'innovation Les dirigeants citent des données internes montrant que les employés présents au bureau "prospèrent" davantage L'équipe IA de Microsoft doit être présente 4 jours par semaine, règles plus strictes pour cette division stratégique Les employés peuvent demander des exceptions jusqu'au 19 septembre 2025 pour trajets complexes ou absence d'équipe locale Amy Coleman (RH) affirme que la collaboration en personne améliore l'énergie et les résultats, surtout à l'ère de l'IA La politique s'appliquera progressivement aux 228 000 employés dans le monde après les États-Unis Les réactions sont mitigées, certains employés critiquent la perte d'autonomie et les bureaux inadéquats Microsoft rattrape ses concurrents tech qui ont déjà imposé des retours au bureau plus stricts Cette décision intervient après 15 000 licenciements en 2025, créant des tensions avec les employés Comment Claude Code est né ? (l'histoire de sa création) https://newsletter.pragmaticengineer.com/p/how-claude-code-is-built Claude Code : outil de développement "AI-first" créé par Boris Cherny, Sid Bidasaria et Cat Wu. Performance impressionnante : 500M$ de revenus annuels, utilisation multipliée par 10 en 3 mois. Adoption interne massive : Plus de 80% des ingénieurs d'Anthropic l'utilisent quotidiennement, y compris les data scientists. Augmentation de productivité : 67% d'augmentation des Pull Requests (PR) par ingénieur malgré le doublement de l'équipe. Origine : Commande CLI simple évoluant vers un outil accédant au système de fichiers, exploitant le "product overhang" du modèle Claude. Raison du lancement public : Apprendre sur la sécurité et les capacités des modèles d'IA. Pile technologique "on distribution" : TypeScript, React (avec Ink), Yoga, Bun. Choisie car le modèle Claude est déjà très performant avec ces technologies. "Claude Code écrit 90% de son propre code" : Le modèle prend en charge la majeure partie du développement. Architecture légère : Simple "shell" autour du modèle Claude, minimisant la logique métier et le code (suppression constante de code superflu). Exécution locale : Privilégiée pour sa simplicité, sans virtualisation. Sécurité : Système de permissions granulaire demandant confirmation avant chaque action potentiellement dangereuse (ex: suppression de fichiers). Développement rapide : Jusqu'à 100 releases internes/jour, 1 release externe/jour. 5 Pull Requests/ingénieur/jour. Prototypage ultra-rapide (ex: 20+ prototypes d'une fonctionnalité en quelques heures) grâce aux agents IA. Innovation UI/UX : Redéfinit l'expérience du terminal grâce à l'interaction LLM, avec des fonctionnalités comme les sous-agents, les styles de sortie configurables, et un mode "Learning". Le 1er Café IA publique a Paris https://www.linkedin.com/pulse/my-first-caf%25C3%25A9-ia-paris-room-full-curiosity-an[…]o-goncalves-r9ble/?trackingId=%2FPHKdAimR4ah6Ep0Qbg94w%3D%3D Conférences La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 30-31 octobre 2025 : Agile Tour Bordeaux 2025 - Bordeaux (France) 30-31 octobre 2025 : Agile Tour Nantais 2025 - Nantes (France) 30 octobre 2025-2 novembre 2025 : PyConFR 2025 - Lyon (France) 4-7 novembre 2025 : NewCrafts 2025 - Paris (France) 5-6 novembre 2025 : Tech Show Paris - Paris (France) 5-6 novembre 2025 : Red Hat Summit: Connect Paris 2025 - Paris (France) 6 novembre 2025 : dotAI 2025 - Paris (France) 6 novembre 2025 : Agile Tour Aix-Marseille 2025 - Gardanne (France) 7 novembre 2025 : BDX I/O - Bordeaux (France) 12-14 novembre 2025 : Devoxx Morocco - Marrakech (Morocco) 13 novembre 2025 : DevFest Toulouse - Toulouse (France) 15-16 novembre 2025 : Capitole du Libre - Toulouse (France) 19 novembre 2025 : SREday Paris 2025 Q4 - Paris (France) 19-21 novembre 2025 : Agile Grenoble - Grenoble (France) 20 novembre 2025 : OVHcloud Summit - Paris (France) 21 novembre 2025 : DevFest Paris 2025 - Paris (France) 24 novembre 2025 : Forward Data & AI Conference - Paris (France) 27 novembre 2025 : DevFest Strasbourg 2025 - Strasbourg (France) 28 novembre 2025 : DevFest Lyon - Lyon (France) 1-2 décembre 2025 : Tech Rocks Summit 2025 - Paris (France) 4-5 décembre 2025 : Agile Tour Rennes - Rennes (France) 5 décembre 2025 : DevFest Dijon 2025 - Dijon (France) 9-11 décembre 2025 : APIdays Paris - Paris (France) 9-11 décembre 2025 : Green IO Paris - Paris (France) 10-11 décembre 2025 : Devops REX - Paris (France) 10-11 décembre 2025 : Open Source Experience - Paris (France) 11 décembre 2025 : Normandie.ai 2025 - Rouen (France) 14-17 janvier 2026 : SnowCamp 2026 - Grenoble (France) 29-31 janvier 2026 : Epitech Summit 2026 - Paris - Paris (France) 2-5 février 2026 : Epitech Summit 2026 - Moulins - Moulins (France) 2-6 février 2026 : Web Days Convention - Aix-en-Provence (France) 3 février 2026 : Cloud Native Days France 2026 - Paris (France) 3-4 février 2026 : Epitech Summit 2026 - Lille - Lille (France) 3-4 février 2026 : Epitech Summit 2026 - Mulhouse - Mulhouse (France) 3-4 février 2026 : Epitech Summit 2026 - Nancy - Nancy (France) 3-4 février 2026 : Epitech Summit 2026 - Nantes - Nantes (France) 3-4 février 2026 : Epitech Summit 2026 - Marseille - Marseille (France) 3-4 février 2026 : Epitech Summit 2026 - Rennes - Rennes (France) 3-4 février 2026 : Epitech Summit 2026 - Montpellier - Montpellier (France) 3-4 février 2026 : Epitech Summit 2026 - Strasbourg - Strasbourg (France) 3-4 février 2026 : Epitech Summit 2026 - Toulouse - Toulouse (France) 4-5 février 2026 : Epitech Summit 2026 - Bordeaux - Bordeaux (France) 4-5 février 2026 : Epitech Summit 2026 - Lyon - Lyon (France) 4-6 février 2026 : Epitech Summit 2026 - Nice - Nice (France) 12-13 février 2026 : Touraine Tech #26 - Tours (France) 26-27 mars 2026 : SymfonyLive Paris 2026 - Paris (France) 31 mars 2026 : ParisTestConf - Paris (France) 16-17 avril 2026 : MiXiT 2026 - Lyon (France) 22-24 avril 2026 : Devoxx France 2026 - Paris (France) 23-25 avril 2026 : Devoxx Greece - Athens (Greece) 6-7 mai 2026 : Devoxx UK 2026 - London (UK) 22 mai 2026 : AFUP Day 2026 Lille - Lille (France) 22 mai 2026 : AFUP Day 2026 Paris - Paris (France) 22 mai 2026 : AFUP Day 2026 Bordeaux - Bordeaux (France) 22 mai 2026 : AFUP Day 2026 Lyon - Lyon (France) 17 juin 2026 : Devoxx Poland - Krakow (Poland) 4 septembre 2026 : JUG Summer Camp 2026 - La Rochelle (France) 17-18 septembre 2026 : API Platform Conference 2026 - Lille (France) 5-9 octobre 2026 : Devoxx Belgium - Antwerp (Belgium) Nous contacter Pour réagir à cet épisode, venez discuter sur le groupe Google https://groups.google.com/group/lescastcodeurs Contactez-nous via X/twitter https://twitter.com/lescastcodeurs ou Bluesky https://bsky.app/profile/lescastcodeurs.com Faire un crowdcast ou une crowdquestion Soutenez Les Cast Codeurs sur Patreon https://www.patreon.com/LesCastCodeurs Tous les épisodes et toutes les infos sur https://lescastcodeurs.com/

What if business intelligence didn't stop at answering what happened, but could finally explain why? In this episode of Tech Talks Daily, I sit back down with Alberto Pan, Chief Technology Officer at Denodo, to unpack how Deep Query is redefining enterprise AI through reasoning, transparency, and context. We explore how Deep Query functions as an AI reasoning agent capable of performing open-ended research across live, governed enterprise data. Instead of relying on pre-built dashboards or static reports, it builds and executes multi-step analyses through Denodo's logical data layer, unifying fragmented data sources in real time. Alberto explains how this semantic layer provides the business meaning and governance that traditional GenAI tools lack, transforming AI from a surface-level Q&A system into a trusted analytical partner. Our conversation also digs into the bigger picture of explainable AI. Deep Query reports include a full appendix of executed queries, allowing users to trace every insight back to its source. Alberto breaks down why this level of auditability matters for enterprise trust and how Denodo's support for the Model Context Protocol (MCP) opens the door to more interoperable, agentic AI systems. As we discuss how Deep Query compares with RAG models and data lakehouses, Alberto offers a glimpse into the future of business intelligence—one where analysts become guides for AI-driven research assistants, and decision-makers gain faster, deeper, and more transparent insights than ever before. So what does the rise of reasoning agents like Deep Query mean for the next generation of enterprise AI? And how close are we to a world where AI truly understands the why behind the data? Tune in and share your thoughts after listening.   Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Jordan Shlosberg: Why agency recruiters will win (and internal TA won't)Jordan Shlosberg runs Atlas CRM—the fastest-growing, AI-native recruitment platform in the world.Thousands of recruiters use his technology every day. Real-time data. Real billings. Real problems being solved.If anyone knows what's actually working with AI in recruitment, it's him."Internal talent teams have a lot to worry about. Agency recruiters? There's a renaissance coming."Here's why:Agency recruiters have years of candidate conversations. Reference calls. Market knowledge built through relationships. The ability to cut through 1,500 AI-generated applications with actual insight.Internal TA has a resume. Sometimes a screening call. That's it.But here's the problem: agency recruitment only represents 7-8% of all hires in Europe.We could grow our share massively. Or we could shrink into irrelevance.The difference? How quickly we become AI-literate.This week on The RAG Podcast, Jordan and I go deep on what's actually happening in recruitment AI.We cover:Why Atlas crossed $1M ARR in 10 months while the market contractedHow clients are growing from 4 to 15 seats in under a yearThe fatal flaw in "agentic job boards" like Jack & JillWhy sourcing platforms only show you 50% of LinkedIn's dataThe partnership we're launching to make recruiters top 5% AI usersThis isn't another "AI is coming for your job" panic post.This is strategic intelligence from someone watching what actually works across thousands of recruiters every day.__________________________________________Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, the AI-first recruitment platform built for modern agencies.It doesn't only track CVs and calls. It remembers everything. Every email, every interview, every conversation. Instantly searchable, always available. And now, it's entering a whole new era.With Atlas 2.0, you can ask anything and it delivers. With Magic Search, you speak and it listens. It finds the right candidates using real conversations, not simply look for keywords.Atlas 2.0 also makes business development easier than ever. With Opportunities, you can track, manage and grow client relationships, powered by generative AI and built right into your workflow.Need insights? Custom dashboards give you total visibility over your pipeline. And that's not theory. Atlas customers have reported up to 41% EBITDA growth and an 85% increase in monthly billings after adopting the platform.No admin. No silos. No lost info. Nothing but faster shortlists, better hires and more time to focus on what actually drives revenue.Atlas is your personal AI partner for modern recruiting.Don't miss the future of recruitment. Get started with Atlas today and unlock your exclusive RAG listener offer at https://recruitwithatlas.com/therag/__________________________________________Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn.Spending thousands on Recruiter licences.Building connections. Posting content. Growing networks.But here's the question almost no one can answer:How much revenue is LinkedIn actually bringing into your business?Most founders have thousands of connections but no clear process to turn that attention into cash.That's the problem we solve.At Hoxo, we help recruitment founders build predictable revenue systems on LinkedIn, not just noise or vanity metrics.Our clients are turning LinkedIn into £100K–£300K in new billings within months, using their existing...

SPONSORS: Booking.com - Head over to Booking.com and start your listing today. Get Seen. Get Booked on Booking.com. Ridge Wallet - Take advantage of Ridge's biggest sale of the year and GET UP TO 47% off by going to https://www.Ridge.com/HONEYDEW  Rag & Bones - Upgrade your denim game with Rag & Bone! Get 20% off sitewide with code HONEYDEW at https://www.rag-bone.com My HoneyDew this week is comedian and actor David Koechner! Check out David on the road, and the latest film he starred in called Ganymede. David joins me this week to Highlight the Lowlights of his small town upbringing, breaking out into show business, and his long battle with alcoholism. We talk about David's experience growing up catholic in a small Missouri town, and how he would go from sneaking episodes of SNL while his parents were out of the house, to eventually getting a one season run himself. David also opens up about his struggles with alcoholism, the trouble it has got him in, and finding his way into recovery. Check out my new standup special “Live and Alive” streaming on my YouTube now! https://youtu.be/PMGWVyM2NJo?si=SrhXjgzR1pe6CyYE SUBSCRIBE TO MY YOUTUBE and watch full episodes of The Dew every toozdee! https://youtube.com/@rsickler SUBSCRIBE TO MY PATREON - The HoneyDew with Y'all, where I Highlight the Lowlights with Y'all! Get audio and video of The HoneyDew a day early, ad-free at no additional cost! It's only $5/month! AND we just added a second tier. For a total of $8/month, you get everything from the first tier, PLUS The Wayback a day early, ad-free AND censor free AND extra bonus content you won't see anywhere else! http://patreon.com/RyanSickler What's your story?? Submit at honeydewpodcast@gmail.com Get Your HoneyDew Gear Today! https://shop.ryansickler.com/ Ringtones Are Available Now! https://www.apple.com/itunes/ http://ryansickler.com/ https://thehoneydewpodcast.com/ SUBSCRIBE TO THE CRABFEAST PODCAST https://podcasts.apple.com/us/podcast/the-crabfeast-with-ryan-sickler-and-jay-larson/id1452403187

This week on The Geek in Review, Greg Lambert and Marlene Gebauer sit down to compare notes from a busy conference season. Marlene shares her experience at the American Legal Technology Awards where The Geek in Review was honored for excellence in journalism. She recounts the surreal joy of being recognized among friends and peers in legal tech, including fellow nominees like Steve Embry, and how a spontaneous speech turned out to be one of the night's highlights. The duo reflects on how events like this underscore the sense of community that continues to define the innovation side of the legal industry.Greg takes listeners behind the scenes at ClioCon, describing it as one of the most energetic user conferences around. He dives into his conversation with Clio CEO Jack Newton and how the company's recent vLex acquisition signals a bold expansion into the Big Law space. With $900 million in funding, Clio appears ready to bridge the divide between small-firm technology and enterprise-level workflows. Greg also teases an illuminating hallway chat with Ed Walters, now at Clio Library (formerly Fastcase), about the major leap forward in legal research accuracy driven by improvements in RAG (retrieval-augmented generation) and vector database indexing.Marlene offers her own takeaways from the Association of Corporate Counsel (ACC) Annual Meeting, where AI and governance dominated the agenda. She describes a landscape where in-house lawyers are wrestling with both the promise and peril of generative AI, from shadow AI concerns to data hygiene challenges. Her biggest surprise was seeing law firms themselves exhibiting at the ACC conference, signaling a shift toward direct engagement between firms and their corporate clients in shared learning spaces.Together, Greg and Marlene unpack the emerging themes of human-centered governance, the evolving role of AI in matter management, and the race among vendors to automate core workflows without losing the human touch. From Clio's plans to build AI-driven workflow mapping that could auto-draft documents, to Marlene's caution about how bespoke law firm processes might resist one-size-fits-all automation, their discussion paints a picture of a profession both accelerating and self-checking at once.The episode winds down with lighter reflections on travel mishaps, conference after-parties, and the long arc of Richard Susskind's The End of Lawyers? conversation—still ongoing, now infused with cautious optimism about AI's role in expanding access to justice. As always, they end where The Geek in Review thrives: at the intersection of humor, humility, and the hopeful chaos of legal innovation.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.] ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

Jaipal Singh Goud is the CTO at Prem AI, working on model customization and privacy-preserving compute. This episode was recorded at the Plan B studios in Lugano, Switzerland. For more information, visit https://pow.space/How do fine-tuned models and RAG systems power personalized AI agents that learn, collaborate, and transform enterprise workflows? What kind of technical challenges do we need to first examine before this becomes real?Demetrios Brinkmann - Founder of MLOps Community~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]

01. Hurts, Purple Disco Machine - Wonderful Life '25 (Record Mix) 02. Don Diablo, R3Hab, Neeka - Disco Marathon 03. Mark Dann, Giovanni Ricci - Let Me Die (Record Mix) 04. Basto! - Again & Again (Record Mix) 05. Arei, Dj Lev - Du Hast (Record Mix) 06. David Guetta, Hypaton, Bonnie Tyler - Together (Record Mix) 07. Lost Frequencies, Dimaro - Are You With Me (Record Mix) 08. Playmen, Valeron, Klavdia - Touch Me (Record Mix) 09. Alle Farben - Bad Ideas (Record Mix) 10. Alok, Jess Glynne - Summer's Back (Record Mix) 11. Twocolors, Safri Duo, Chris De Sarandy - Head Above Water (Record Mix) 12. Lykke Li, The Magician - I Follow Rivers (Record Mix) 13. Vize - Wait (Alibi Blue) (Record Mix) 14. Sean Finn - Give It to Me (Record Mix) 15. Calvin Harris, Rag'N'Bone Man - Giant (Record Mix) 16. Dimitri Vegas, Chapter & Verse, Goodboys - Good For You 17. Ian Carey, Michelle Shellers, Manyfew, Joe Stone - Keep On Rising (Record Mix) 18. Mind Electric - Things You Say (Record Mix) 19. Hugel, Topic, Arash, Daecolm - I Adore You (Record Mix) 20. Mau P - The Less I Know The Better 21. Shouse, Cub Sport - Only You (Record Mix) 22. Faul, Wad, Pnau - Changes (Record Mix) 23. Moby, Blond Ish, Kiko Franco - Natural Blues (Record Mix) 24. Zerb, Sofiya Nzau - Mwaki (Record Mix) 25. Robin Schulz, James Blunt - OK (Record Mix) 26. R.I.O., Gonsu, Jenia Smile, Ser Twister - Shine On (Record Mix) 27. Coldplay, Avicii - A Sky Full of Stars (Record Mix) 28. Mr. Belt & Wezol, Rscl - Opened Up My Soul 29. Shane Codd - Rather Be Alone (Record Mix) 30. Fisher, Aatig - Take It Off (Record Mix) 31. Byor - Superstar 32. Jonas Blue, Jp Cooper - Perfect Strangers (Record Mix) 33. Jerome Robins, Karsten Sollors - Don't Stop The Music (Record Mix) 34. Lufthaus, Sophie Ellis-Bextor - Immortal (Record Mix) 35. Nicky Romero - All Night Long 36. Klaas - The Way (Record Mix) 37. Kddk, Alex Alta - 1&2 (Record Mix) 38. Adam Lambert - Ghost Town (Record Mix) 39. Jake Shore, Rich Dietz - Everybody 40. Ben Delay - I Never Felt So Right (Record Mix) 41. Weiss, Harry Romero - Where Do We Go (Record Mix) 42. Oliver Heldens, Ian Asher, Sergio Mendes - Mas Que Nada 43. Twocolors - Heavy Metal Love (Record Mix) 44. Hypaton, David Guetta, La Bouche - Be My Lover (Record Mix) 45. Dante Klein - Gotta Feel 46. Imanbek, Younotus - Heal My Heart (Record Mix) 47. Don Diablo, Nelly Furtado - Doing Nothin' 48. Armin Van Buuren - Es Vedra (Record Mix) 49. Bob Sinclar - Cruel Summer (Record Mix) 50. One-T, Ywy, Nika - The Way To Love (Record Mix) 51. Lola Young, Ted Bear - Messy (Record Mix) 52. Aaron Smith, Luvli, Krono - Dancin' (Record Mix) 53. Alok, Ella Eyre, Kenny Dope, Never Dull - Deep Down (Record Mix) 54. Argy, Omiki - WIND (Record Mix) 55. Doechii, Dj Dark - Anxiety (Record Mix) 56. Akcent, Sera, Misha Miller - Don't Leave (Kylie) (Record Mix) 57. Sean Paul, Odd Mob - Get Busy 58. Calvin Harris, Benny Blanco - I Found You (Record Mix) 59. Teriyaki Boyz, Hayat - Tokyo Drift (Record Mix) 60. Dynoro, Gigi D'Agostino - In My Mind... (Record Mix) 61. Pete Tong, Roro, Jules Buckley, The Essential Orchest - Rhythm Of The Night (Record Mix) 62. Oneil, Kanvise, Murana - Redlight (Record Mix) 63. Shane Codd - Get Out My Head (Record Mix) 64. Block & Crown, Daisy - Mr Vain (Record Mix) 65. Goodboys, Nu Aspect, Avaion - Blindspot (Record Mix) 66. Global Deejays, Jenia Smile, Ser Twister - The Sound Of San Francisco (Record Mix) 67. Duke Dumont - Won't Look Back (Record Mix) 68. Joel Corry, Pickle, Vula - Stay Together (Baby Baby) (Record Mix) 69. Adam Port, Stryv, Malachii, Switch Disco - Move (Record Mix) 70. Fedde Le Grand - Got Your Money (Record Mix) 71. Camelphat, Elderbrook - Cola (Record Mix) 72. Zerb, Ty Dolla $Ign, Wiz Khalifa - Location (Record Mix) 73. Dj Louis - Let Me Blow Ya Mind 74. Disclosure - She's Gone, Dance On 75. Pierse, Blair - Bitter Sweet Symphony (Record Mix) 76. R3Hab, Mufasa, Rani - Believe (Record Mix) 77. Afrojack, Aloe Blacc - In My World (Record Mix) 78. Tayna, Marshmello, Ukay - Si Ai (Record Mix) 79. Arc North, Cour, New Beat Order, Lunis - Faded (Record Mix) 80. Kygo, Ava Max, Tiesto - Whatever (Record Mix) 81. Lost Culture, Morfi, Carine - Lean On (Record Mix) 82. Hugel, Alleh, Yorghaki - una noche con hugel (Record Mix) 83. Crazibiza - Fresh (Record Mix) 84. Diplo, Miguel - Don't Forget My Love (Record Mix) 85. Audien, Rory Hope - Lose It All 86. David Guetta, Sia - Beautiful People (Record Mix) 87. Lady Gaga, Dj Dark - The Dead Dance (Record Mix) 88. Nicky Romero, Giacobbi, Fatboi - Move It (Record Mix) 89. Robin Schulz, Jasmine Thompson - Sun Goes Down (Record Mix) 90. Faul & Wad, Nico & Vinz, Altego, Old Jim - How I Feel (Am I Wrong) (Record Mix) 91. Oliver Heldens, Becky Hill - Gecko (Overdrive) (Record Mix) 92. Playmen, Damiano, Michael Tsaousopoulos, Ferrylake - Naked (Record Mix) 93. Fisher - Losing It (Record Mix) 94. Otnicka, Kaskeiyp - For an Angel (Record Mix) 95. Empire Of The Sun, Tony Romera - Walking on a dream (Record Mix) 96. Misha Miller, Alexvelea, Bodega - Bam Bam (Record Mix) 97. Don Diablo - The Way I Are (Record Mix) 98. Kris Kross Amsterdam, Eyelar - Mr. Lie To Me (Record Mix) 99. C-Bool - Never Go Away (Record Mix) 100. Lucas & Steve, Laura White - Are You Ready 101. Amor - Tell Me (Record Mix) 102. Jonas Blue, Malive - Edge of Desire (Record Mix) 103. Thomas Gold - Pump Up The Jam (Record Mix) 104. Sakko, Jibaro - Carnival (Record Mix) 105. Morgan Page, Telykast - Dancing All Alone (Record Mix) 106. Melsen - Be Your Lover 107. Tujamo, Azteck, Inna - Freak (Record Mix) 108. David Guetta - The World Is Mine (Record Mix) 109. Maesic, Marshall Jefferson, Salome Das - Life Is Simple (Record Mix) 110. Showtek, Smack, Sam Gray - Take My Heart Away (Record Mix) 111. John Summit, Inez - crystallized (Record Mix) 112. Shouse - Love Tonight (Record Mix) 113. Bolier, Joe Stone, Voost - Keep This Fire Burning (Record Mix) 114. Kamrad - Be Mine (Record Mix) 115. Marshmello, Jonas Brothers, Alex Caspian - Slow Motion (Record Mix) 116. Anna Naklab, Younotus, Alle Farben - Supergirl (Record Mix) 117. Dj Snake, Bipolar Sunshine - Paradise (Record Mix) 118. Topic, A7S - Breaking Me (Record Mix) 119. Claptone, Sea Girls, Henry Camamile - Put Your Love On Me 120. Tiesto - Lay Low (Record Mix) 121. Hurts, Purple Disco Machine - Wonderful Life '25 (Record Mix) 122. Huntr-X, Ejae, Audrey Nuna, Rei Ami, Dj Dark - Golden (Record Mix) 123. J Balvin, Willy William, Gonsu, Jenia Smile, Ser Twist - Mi Gente (Record Mix) 124. Calvin Harris, John Newman - Blame! (Record Mix) 125. Semm, Orfa - How Deep Is Your Love (Record Mix) 126. Nicky Romero, Barmuda - Fade Away 127. Punch Exciters - Dance Of The Fire (Record Mix) 128. Rue Jay - I Want Your Love 129. C Block, The Distance, Riddick - So Strung Out (Record Mix) 130. Demi Lovato - Fast (Record Mix) 131. Kanvise, Lew Heart, Falcoma - All Good Things (Record Mix) 132. Ive, David Guetta - Supernova Love (Record Mix) 133. Dom Dolla, Clementine Douglas - Miracle Maker (Record Mix) 134. Dimitri Vegas, Chapter & Verse, Goodboys - Good For You 135. Alok, Daecolm, Malou - Unforgettable (Record Mix) 136. Murdbrain, Theajsound, Rachel Morgan Perry - Save Me (Record Mix) 137. Armand Van Helden, Salvatore Mancuso - my my my (Record Mix) 138. Otnicka - Celebrate the Love (Record Mix) 139. Afrojack, Aloe Blacc - In My World 140. Killteq, D.Hash, Vallhee - I Like It (Record Mix) 141. Firebeatz, Dubdogz - Give It Up (Record Mix) 142. Lost Frequencies, Janieck Devy - Reality (Record Mix) 143. Martin Jensen, Fastboy - One Day (Record Mix) 144. Daft Punk - Around The World (Record Mix) 145. Don Diablo - Momentum (Record Mix) 146. Steve Angello - Me 147. Annabell Kowalski - Hey Boy Hey Girl (Record Mix) 148. Block & Crown - Mr DJ Give Me More 149. Hosh, 1979, Jalja, Slider & Magnit - Midnight (The Hanging Tree) (Record Mix) 150. Alok, Gryffin, Julia Church - Never Letting Go (Record Mix) 151. Gregory Porter, Jonas Blue - Liquid Spirit (Record Mix) 152. John Summit - La Danza (Record Mix) 153. Joe Stone, Ferreck Dawn - Man Enough (Record Mix) 154. Ava Max - Don't Click Play (Record Mix) 155. Joezi, Lizwi - Amathole (Record Mix) 156. Alfa, Manu Chao, Pas - A Me Mi Piace (Record Mix) 157. Galwaro, Lizot, Gabry Ponte - Like a Prayer (Record Mix) 158. Topcover - First Day (Record Mix) 159. Oliver Heldens, Riton, Vula - Turn Me On (Record Mix) 160. Vanco, Aya - Ma Tnsani (Yalla Habibi) (Record Mix) 161. Bob Sinclar - Cruel Summer (Record Mix) 162. Stefy De Cicco, Ben Hamilton, Martin Jensen - Day 'N' Nite (Record Mix) 163. Avicii, Dan Tyminski - Hey Brother (Record Mix) 164. Max Oazo - Gimme! Gimme! Gimme! (Record Mix) 165. Swedish House Mafia, Pharell - One (Your Name) (Record Mix) 166. Lucas & Steve - Push The Feeling (Record Mix) 167. Boney M, R3Hab - Sunny (Record Mix) 168. Felix Jaehn, Shouse - Walk With Me (Record Mix) 169. Fred Again.., The Blessed Madonna - Marea (Weve Lost Dancing) (Record Mix) 170. Swanky Tunes, Shapov - Wannabe 171. Richard Grey - At Night (Record Mix) 172. Mirko Donnini - Thinking of You (Record Mix) 173. Fast Boy, Raf, Amice - Wave (Record Mix) 174. Tiesto, Soaky Siren - Tantalizing (Record Mix) 175. Calvin Harris, Ellie Goulding - I Need Your Love (Record Mix) 176. David Guetta - Family Affair (Dance For Me) (Record Mix) 177. Vize - Wait (Alibi Blue) (Record Mix) 178. Prospa, Josh Baker, Rahh - You Don't Own Me 179. Cassian, Yotto, Da Hool - Love Parade (Record Mix)

The JBP opens its latest episode with a conversation about proposals and engagements (29:03) before turning to the room's thoughts on the Cash Money and No Limit Verzuz over the weekend in Las Vegas (44:24). The cast then shares their concerns over Hurricane Melissa (1:41:10), Marc Lamont Hill revisits an old argument between Ish and Joe (1:53:15), and a correctional officer has received contraband charges for smuggling in wings for an inmate (2:04:37). Also, Kamala Harris says she may run for President again (2:20:13), Cam'ron is suing J. Cole (2:44:43), Part of the Show (2:51:12), and much more! Become a Patron of The Joe Budden Podcast for additional bonus episodes and visual content for all things JBP! Join our Patreon here: http://www.patreon.com/joebudden Sleeper Picks: Joe | Sasha Keable (feat. BEAM) - "work" Ice | Wale (feat. BNYX®) - "Mirroronnabenz" Parks | Dave - "My 27th Birthday" Ish | Pete Bailey - "Keep You" Marc | Danger Mouse, Black Thought, & Rag'n'Bone Man - "Up"

Jacob Bank has been building AI agents since before they were cool. While the rest of us were just figuring out what ChatGPT could do, Jacob was already 13 years deep into agent research. Now, as founder and CEO of Relay.app, Jacob is making AI agents accessible to everyone, from customer success teams to businesses that install slip-resistant floors. Jacob has a fascinating prediction: within a year, agents will be able to handle virtually any task you do on your computer. The real question won't be "can an agent do this?" but rather "how do I teach, manage, and trust my agent?"Timestamps0:00 - Preview & Introduction1:48 - Meet Jacob & An Overview of Relay.app4:08 - From Stanford AI Research to Google to Founder4:57 - AI Agents were 15 Years in the Making 8:30 - It Took 2.5 Years to Get the First Customer12:35 - What Actually Is Agentic AI?14:55 - Understanding AI Agents19:45 - How AI Accesses Information: Context Windows, and RAG24:11 - The Shift from RAG to MCP25:51 - Understanding MCP: The Restaurant Analogy30:04 - Real-World Use Cases of Workflows with AI for CSMs 33:51 - When and When Not to Use Agents 37:45 - Why SMBs Move Faster on AI Than Big Enterprises42:12 - The Two Limitations of Agents Today44:31 - We're All Managers Now46:15 - Where to Stay Current on AI47:36 - The Value of Hands-On Experience with AI ToolsWhat you'll learn:- The critical difference between workflows and agents (and why you need both)- Why "we're all managers now"—even if you're an individual contributor- The future of work isn't about doing tasks; it's about managing and calibrating your agents- Practical use cases of Agentic AI for CSMs- Why spending an hour daily experimenting with AI tools is "worth its weight in gold"Resources mentioned:- Ben's Bytes newsletter- Jeff Siu (YouTube)

Ricky Burns: How to build £1M profit in year one (after losing it all at 26)Ricky Burns made incredible money at 26.Then he drank it all away.Partied it into oblivion. Got hit with a massive VAT bill he couldn't pay. Shut the whole thing down.Most people never recover from that kind of failure.Ricky went back into employment for 10 years.Ran European divisions. Watched. Learned. Took notes on what actually works.At 33, he started again.September 2024: Pulse Group launched with his co-founder Tony.12 months later:£1.2M in fees£1M in EBITDA (profit)I don't know anyone who's achieved these numbers in year one.This week on The RAG Podcast, Ricky breaks it all down.We cover:How they hit £1M profit in 12 months (it's simpler than you think)What killed his first business (beyond the partying)The 10 years of lessons that made the comeback inevitableWhy he paired recruitment with SOW consultancyThe systems and client focus driving 83% marginsHow AI is making them more efficient without adding headcountWhy work-life balance is now non-negotiableThis isn't your typical "I scaled fast" story.This is brutal honesty about failure, sobriety, and building something sustainable the second time around.If you've ever wondered what separates 6-figure founders from 7-figure founders - or if you think you've already missed your shot - this episode has the answers.__________________________________________Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, the AI-first recruitment platform built for modern agencies.It doesn't only track CVs and calls. It remembers everything. Every email, every interview, every conversation. Instantly searchable, always available. And now, it's entering a whole new era.With Atlas 2.0, you can ask anything and it delivers. With Magic Search, you speak and it listens. It finds the right candidates using real conversations, not simply look for keywords.Atlas 2.0 also makes business development easier than ever. With Opportunities, you can track, manage and grow client relationships, powered by generative AI and built right into your workflow.Need insights? Custom dashboards give you total visibility over your pipeline. And that's not theory. Atlas customers have reported up to 41% EBITDA growth and an 85% increase in monthly billings after adopting the platform.No admin. No silos. No lost info. Nothing but faster shortlists, better hires and more time to focus on what actually drives revenue.Atlas is your personal AI partner for modern recruiting.Don't miss the future of recruitment. Get started with Atlas today and unlock your exclusive RAG listener offer at https://recruitwithatlas.com/therag/__________________________________________Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn.Spending thousands on Recruiter licences.Building connections. Posting content. Growing networks.But here's the question almost no one can answer:How much revenue is LinkedIn actually bringing into your business?Most founders have thousands of connections but no clear process to turn that attention into cash.That's the problem we solve.At Hoxo, we help recruitment founders build predictable revenue systems on LinkedIn, not just noise or vanity metrics.Our clients are turning LinkedIn into £100K–£300K in new billings within months, using their existing...

Dell Technologies has announced Dell AI Data Platform advancements designed to help enterprises turn distributed, siloed data into faster, more reliable AI outcomes. Why it matters As enterprise AI adoption surges and data grows, organisations need a platform that can securely transform distributed, siloed data into actionable insights. The Dell AI Data Platform, a critical component of the Dell AI Factory, delivers an open, modular foundation to create value from scattered data silos. By decoupling data storage from processing, it eliminates bottlenecks and provides the flexibility needed for AI workloads like training, fine-tuning, retrieval-augmented generation (RAG) or inferencing. The platform, integrated with the NVIDIA AI Data Platform reference design, is powered by four core building blocks: Storage engines for smart data placement and seamless data movement Data engines to turn data into actionable insights Built-in cyber resiliency Data management services Together, they create a scalable, flexible foundation for customers to realise AI's full potential. Dell AI Data Platform storage engines deliver peak AI performance Dell PowerScale and Dell ObjectScale, the Dell AI Data Platform's storage engines, offer the performance, security and multi-protocol access essential for AI data. Dell PowerScale delivers NAS (network-attached storage) simplicity and parallel performance for AI workloads like training, fine-tuning, inferencing and retrieval-augmented generation (RAG) pipelines. With new integration of NVIDIA GB200 and GB300 NVL72 and ongoing software updates, Dell PowerScale delivers reliable performance, simplified management at scale and seamless compatibility with applications and solution stacks. PowerScale F710, which has achieved NVIDIA Cloud Partner (NCP) certification for high-performance storage, delivers 16k+ GPU-scale with up to 5X less rack space, 88% fewer network switches and up to 72% lower power consumption compared to competitors. Dell ObjectScale, the industry's highest-performing object platform, provides extremely performant, scalable S3-native object storage for massive AI workloads. ObjectScale is available as an appliance or through a new software-defined option on Dell PowerEdge servers that is up to 8 times faster than previous-generation all-flash object storage. New advancements improve ObjectScale's speed, scalability and efficiency. S3 over RDMA support will soon enter tech preview. It will offer up to 230% higher throughput, 80% lower latency and 98% lower CPU usage compared to traditional S3. Small object performance and efficiency improvements for large deployments deliver up to 19% higher throughput and up to 18% lower latency for 10KB objects. Deeper AWS S3 integration and bucket-level compression give developers and data scientists better tools to store, move and use large amounts of data. Dell AI Data Platform data engines power real-time AI Dell is also expanding its data engines, the specialised tools in the Dell AI Data Platform that organise, query and activate AI data. Dell's data engines are built in collaboration with trusted AI leaders like NVIDIA, Elastic and Starburst. The new Data Search Engine, developed in collaboration with Elastic, speeds decision-making by allowing customers to interact with data as naturally as asking a question. Designed for tasks like RAG, semantic search and generative AI pipelines, it integrates with MetadataIQ data discovery software to search billions of files on PowerScale and ObjectScale using granular metadata. Developers can build smarter RAG applications in tools like LangChain with the engine, ingesting only updated files to save compute time and keep vector databases current. The Data Analytics Engine, developed in collaboration with Starburst, enables seamless data querying across spreadsheets, databases, cloud warehouses and lakehouses. The new Data Analytics Engine Agentic Layer transforms raw data into business-ready products in...

01. Shouse, Cub Sport - Only You (Record Mix) 02. Goodboys, Nu Aspect, Avaion - Blindspot (Record Mix) 03. David Guetta, Hypaton, Bonnie Tyler - Together (Record Mix) 04. Calvin Harris - My Way (Record Mix) 05. Armin Van Buuren, Sam Gray - Dream a Little Dream (Record Mix) 06. Alok, Gryffin, Julia Church - Never Letting Go (Record Mix) 07. Hugel, Alleh, Yorghaki - una noche con hugel (Record Mix) 08. Kanvise, Lew Heart, Falcoma - All Good Things (Record Mix) 09. Ian Carey, Michelle Shellers, Manyfew, Joe Stone - Keep On Rising (Record Mix) 10. Basto! - Gregory's Theme (Record Mix) 11. Tayna, Marshmello, Ukay - Si Ai (Record Mix) 12. Filatov & Karas - Time Won't Wait (Record Mix) 13. Block & Crown, Atilla Cetin - How Many Nations (Record Mix) 14. Zerb, Sofiya Nzau, Izzy Bizu - Kumbaya (Record Mix) 15. Alis Shuka, Byjoelmichael - Not About Us (Record Mix) 16. Cedric Gervais, Nile Rodgers - We Are Family (Record Mix) 17. Robin Schulz, Cyril, Sam Martin - World Gone Wild (Record Mix) 18. Vanco, Aya - Ma Tnsani (Yalla Habibi) (Record Mix) 19. Vize - Wait (Alibi Blue) (Record Mix) 20. C-Bool, Giang Pham - DJ Is Your Second Name (Record Mix) 21. Melsen, Dwight Steven - One More Night 22. Richard Grey - At Night (Record Mix) 23. Akcent, Sera, Misha Miller - Don't Leave (Kylie) (Record Mix) 24. Morgan Page, Telykast - Dancing All Alone (Record Mix) 25. Crazibiza, Cheesecake Boys - Nasty (Record Mix) 26. Tujamo, Azteck, Inna - Freak (Record Mix) 27. Joel Corry, Jennifer Lopez - Get Right 28. Bob Sinclar, Steve Edwards, Fisher - World, Hold On (Record Mix) 29. Eastblock Bitches, Ostblockschlampen - Sunglasses at Night (Record Mix) 30. Maesic, Marshall Jefferson, Salome Das - Life Is Simple (Record Mix) 31. Jonas Blue, Jp Cooper - Perfect Strangers (Record Mix) 32. Swanky Tunes, Shapov - Wannabe 33. Drenchill, Indiiana - Feel This Way (Record Mix) 34. Doechii, Dj Dark - Anxiety (Record Mix) 35. Twocolors, Safri Duo, Chris De Sarandy - Head Above Water (Record Mix) 36. Hugel, Topic, Arash, Daecolm - I Adore You (Record Mix) 37. Kddk, Alex Alta - 1&2 (Record Mix) 38. Alfa, Manu Chao, Pas - A Me Mi Piace (Record Mix) 39. Faul & Wad, Nico & Vinz, Altego, Old Jim - How I Feel (Am I Wrong) (Record Mix) 40. Don Diablo, R3Hab, Neeka - Disco Marathon 41. Huntr-X, Ejae, Audrey Nuna, Rei Ami, Dj Dark - Golden (Record Mix) 42. Arei, Dj Lev - Du Hast (Record Mix) 43. Fred Again.., The Blessed Madonna - Marea (Weve Lost Dancing) (Record Mix) 44. Oliver Heldens, Ian Asher, Sergio Mendes - Mas Que Nada 45. David Guetta, Sia - Beautiful People (Record Mix) 46. Argy, Omnya - Aria (Record Mix) 47. Philip George - Wish You Were Mine (Record Mix) 48. Ava Max - Don't Click Play (Record Mix) 49. Swedish House Mafia, Pharell - One (Your Name) (Record Mix) 50. Faros - Say It Right (Record Mix) 51. Alesso, Calvin Harris - Under Control (Record Mix) 52. Felix Jaehn, Shouse - Walk With Me (Record Mix) 53. Cassian, Yotto, Da Hool - Love Parade (Record Mix) 54. Lady Gaga, Dj Dark - The Dead Dance (Record Mix) 55. Eric Prydz - Proper Education (Record Mix) 56. Sofiya Nzau, Madism, Robert Miles - Hutia (Record Mix) 57. Dubdogz, Zerky - Sun Goes Down (Sound Of Violence) (Record Mix) 58. Zerb, The Chainsmokers, Ink - Addicted (Record Mix) 59. Dj Snake, Bipolar Sunshine - Paradise (Record Mix) 60. Alok, Jess Glynne - Summer's Back (Record Mix) 61. Avicii, Dan Tyminski - Hey Brother (Record Mix) 62. Jonas Blue, Malive - Edge of Desire (Record Mix) 63. Playmen, Valeron, Klavdia - Touch Me (Record Mix) 64. Robin Schulz, Erika Sirola - Speechless (Record Mix) 65. Lufthaus, Sophie Ellis-Bextor - Immortal (Record Mix) 66. Axwell, Ingrosso - More Than You Know (Record Mix) 67. R.I.O., Gonsu, Jenia Smile, Ser Twister - Shine On (Record Mix) 68. Otnicka, Kaskeiyp - For an Angel (Record Mix) 69. Hurts, Purple Disco Machine - Wonderful Life '25 (Record Mix) 70. Mark Dann, Giovanni Ricci - Let Me Die (Record Mix) 71. One-T, Ywy, Nika - The Way To Love (Record Mix) 72. Bob Sinclar - Cruel Summer (Record Mix) 73. Marshmello, Jonas Brothers, Alex Caspian - Slow Motion (Record Mix) 74. Kris Kross Amsterdam, Eyelar - Mr. Lie To Me (Record Mix) 75. Jax Jones, Martin Solveig - All Day & Night (Record Mix) 76. Disclosure - She's Gone, Dance On 77. Shouse, Cub Sport - Only You (Record Mix) 78. Mau P - The Less I Know The Better 79. Kaz James - Sun Is Shining (Record Mix) 80. Joel Corry, Pickle, Vula - Stay Together (Baby Baby) (Record Mix) 81. Sevdaliza, Yseult, Pabllo Vittar, Tiesto - Alibi (Record Mix) 82. Argy, Omiki - WIND (Record Mix) 83. Zerb, Sofiya Nzau - Mwaki (Record Mix) 84. Cyril, Dean Lewis, Amice - Fall At Your Feet (Record Mix) 85. Shane Codd - Rather Be Alone (Record Mix) 86. Imany, Ivan Spell, Daniel Magre - You Will Never Know (Record Mix) 87. Moby, Blond Ish, Kiko Franco - Natural Blues (Record Mix) 88. Demi Lovato - Fast (Record Mix) 89. Weiss, Harry Romero - Where Do We Go (Record Mix) 90. Jerome Robins, Karsten Sollors - Don't Stop The Music (Record Mix) 91. Jake Shore, Rich Dietz - Everybody 92. Block & Crown - Mr DJ Give Me More 93. Fedde Le Grand - Got Your Money (Record Mix) 94. Alle Farben, Graham Candy, Lahos - Flowers (Record Mix) 95. Tiesto, Soaky Siren - Tantalizing (Record Mix) 96. Avalan Rokston, Alex Caspian - Something to Believe In (Record Mix) 97. Hypaton, David Guetta, La Bouche - Be My Lover (Record Mix) 98. Mr. Belt & Wezol, Rscl - Opened Up My Soul 99. Zhu - In the Morning! (Record Mix) 100. Pete Tong, Roro, Jules Buckley, The Essential Orchest - Rhythm Of The Night (Record Mix) 101. Rompasso, Bedanokov - In the Dark (Record Mix) 102. Dante Klein - Gotta Feel 103. Imanbek, Younotus - Heal My Heart (Record Mix) 104. Topcover - First Day (Record Mix) 105. Stefy De Cicco, Ben Hamilton, Martin Jensen - Day 'N' Nite (Record Mix) 106. Joe Stone, Ferreck Dawn - Man Enough (Record Mix) 107. Don Diablo, Nelly Furtado - Doing Nothin' 108. Calvin Harris, John Newman - Blame! (Record Mix) 109. Teriyaki Boyz, Hayat - Tokyo Drift (Record Mix) 110. Felix, Charlotte Haining, Switch Disco - I Found You (Record Mix) 111. Basto! - Again & Again (Record Mix) 112. Afrojack, Aloe Blacc - In My World (Record Mix) 113. Lola Young, Ted Bear - Messy (Record Mix) 114. Tayna, Marshmello, Ukay - Si Ai (Record Mix) 115. Global Deejays, Jenia Smile, Ser Twister - The Sound Of San Francisco (Record Mix) 116. Dj Kuba, Neitan, Bounce Inc. - Watch Out (Record Mix) 117. Zerb, Ty Dolla $Ign, Wiz Khalifa - Location (Record Mix) 118. Murdbrain, Theajsound, Rachel Morgan Perry - Save Me (Record Mix) 119. Vize - Wait (Alibi Blue) (Record Mix) 120. Darude, Glazur, Xm - Sandstorm (Record Mix) 121. Shane Codd - Get Out My Head (Record Mix) 122. Dimitri Vegas, Like Mike, Ne-Yo - Higher Place (Record Mix) 123. Joezi, Lizwi - Amathole (Record Mix) 124. Oceana, Bodybangers - Endless Summer (Record Mix) 125. Crazibiza - Fresh (Record Mix) 126. Max Oazo - Gimme! Gimme! Gimme! (Record Mix) 127. Doechii, Dj Dark - Anxiety (Record Mix) 128. Hugel, Alleh, Yorghaki - una noche con hugel (Record Mix) 129. Playmen, Damiano, Michael Tsaousopoulos, Ferrylake - Naked (Record Mix) 130. Kygo, Ava Max, Tiesto - Whatever (Record Mix) 131. Sean Paul, Odd Mob - Get Busy 132. Relanium, Deen West - Leel Lost (Record Mix) 133. Sakko, Jibaro - Carnival (Record Mix) 134. Lana Del Rey, Kevin Blanc - Young & Beautiful (Record Mix) 135. Misha Miller, Alexvelea, Bodega - Bam Bam (Record Mix) 136. Galantis - Runaway (U & I) (Record Mix) 137. R3Hab, Mufasa, Rani - Believe (Record Mix) 138. Robin Schulz, Ilsey - Headlights (Record Mix) 139. Dj Louis - Let Me Blow Ya Mind 140. Calvin Harris, Rag'N'Bone Man - Giant (Record Mix) 141. Vanco, Aya - Ma Tnsani (Yalla Habibi) (Record Mix) 142. Madison Mars, Little League - New Vibe Who Dis (Record Mix) 143. Ive, David Guetta - Supernova Love (Record Mix) 144. Goodboys, Nu Aspect, Avaion - Blindspot (Record Mix)

In this talk, Hugo Bowne-Anderson, an independent data and AI consultant, educator, and host of the podcasts Vanishing Gradients and High Signal, shares his journey from academic research and curriculum design at DataCamp to advising teams at Netflix, Meta, and the US Air Force. Together, we explore how to build reliable, production-ready AI systems—from prompt evaluation and dataset design to embedding agents into everyday workflows.You'll learn about: How to structure teams and incentives for successful AI adoptionPractical prompting techniques for accurate timestamp and data generationBuilding and maintaining evaluation sets to avoid “prompt overfitting”- Cost-effective methods for LLM evaluation and monitoringTools and frameworks for debugging and observing AI behavior (Logfire, Braintrust, Phoenix Arise)The evolution of AI agents—from simple RAG systems to proactive, embedded assistantsHow to escape “proof of concept purgatory” and prioritize AI projects that drive business valueStep-by-step guidance for building reliable, evaluable AI agentsThis session is ideal for AI engineers, data scientists, ML product managers, and startup founders looking to move beyond experimentation into robust, scalable AI systems. Whether you're optimizing RAG pipelines, evaluating prompts, or embedding AI into products, this talk offers actionable frameworks to guide you from concept to production.LINKSEscaping POC Purgatory: Evaluation-Driven Development for AI Systems - https://www.oreilly.com/radar/escaping-poc-purgatory-evaluation-driven-development-for-ai-systems/Stop Building AI Agents - https://www.decodingai.com/p/stop-building-ai-agentsHow to Evaluate LLM Apps Before You Launch - https://www.youtube.com/watch?si=90fXJJQThSwGCaYv&v=TTr7zPLoTJI&feature=youtu.beMy Vanishing Gradients Substack - https://hugobowne.substack.com/Building LLM Applications for Data Scientists and Software Engineers https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=datatalksclubTIMECODES:00:00 Introduction and Expertise04:04 Transition to Freelance Consulting and Advising08:49 Restructuring Teams and Incentivizing AI Adoption12:22 Improving Prompting for Timestamp Generation17:38 Evaluation Sets and Failure Analysis for Reliable Software23:00 Evaluating Prompts: The Cost and Size of Gold Test Sets27:38 Software Tools for Evaluation and Monitoring33:14 Evolution of AI Tools: Proactivity and Embedded Agents40:12 The Future of AI is Not Just Chat44:38 Avoiding Proof of Concept Purgatory: Prioritizing RAG for Business Value50:19 RAG vs. Agents: Complexity and Power Trade-Offs56:21 Recommended Steps for Building Agents59:57 Defining Memory in Multi-Turn ConversationsConnect with HugoTwitter - https://x.com/hugobowneLinkedin - https://www.linkedin.com/in/hugo-bowne-anderson-045939a5/Github - https://github.com/hugobowneWebsite - https://hugobowne.github.io/Connect with DataTalks.Club:Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQCheck other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

Chip Huyen is a core developer on Nvidia's Nemo platform, a former AI researcher at Netflix, and taught machine learning at Stanford. She's a two-time founder and the author of two widely read books on AI, including AI Engineering, which has been the most-read book on the O'Reilly platform since its launch. Unlike many AI commentators, Chip has built multiple successful AI products and platforms and works directly with enterprises on their AI strategies, giving her unique visibility into what's actually happening inside companies building AI products.We discuss:1. What people think makes AI apps better vs. what actually makes AI apps better2. What pre-training vs. post-training is, and why fine-tuning should be your last resort3. How RLHF (reinforcement learning from human feedback) actually works4. Why data quality matters more than which vector database you choose5. Why high performers are seeing the most gains from AI coding tools6. Why most AI problems are actually UX issues—Brought to you by:Dscout—The UX platform to capture insights at every stage: from ideation to production: https://www.dscout.com/Justworks—The all-in-one HR solution for managing your small business with confidence: https://ad.doubleclick.net/ddm/trackclk/N9515.5688857LENNYSPODCAST/B33689522.423713855;dc_trk_aid=616485030;dc_trk_cid=237010502;dc_lat=;dc_rdid=;tag_for_child_directed_treatment=;tfua=;gdpr=$Persona—A global leader in digital identity verification: https://withpersona.com/lenny—Where to find Chip Huyen:• X: https://x.com/chipro• LinkedIn: https://www.linkedin.com/in/chiphuyen/• Website: https://huyenchip.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Chip Huyen(04:28) Chip's viral LinkedIn post(07:05) Understanding AI training: pre-training vs. post-training(08:50) Language modeling explained(13:55) The importance of post-training(15:20) Reinforcement learning and human feedback(22:23) The importance of evals in AI development(31:55) Retrieval augmented generation (RAG) explained(38:50) Challenges in AI tool adoption(43:19) Challenges in measuring productivity(45:20) The three-bucket test(49:10) The future of engineering roles(55:31) ML Engineers vs. AI engineers(57:12) Looking forward: the impact of AI(01:05:48) Model capabilities vs. perceived performance(01:08:23) Lightning round and final thoughts—Referenced:• Chip's LinkedIn post on what actually improves AI apps: https://www.linkedin.com/posts/chiphuyen_aiapplications-aiengineering-activity-7358971409227792384-y0mf/• Prediction and Entropy of Printed English: https://www.princeton.edu/~wbialek/rome/refs/shannon_51.pdf• Why experts writing AI evals is creating the fastest-growing companies in history | Brendan Foody (CEO of Mercor): https://www.lennysnewsletter.com/p/experts-writing-ai-evals-brendan-foody•Inside the expert network training every frontier AI model | Garrett Lord (Handshake CEO): https://www.lennysnewsletter.com/p/inside-handshake-garrett-lord• First interview with Scale AI's CEO: $14B Meta deal, what's working in enterprise AI, and what frontier labs are building next | Jason Droege: https://www.lennysnewsletter.com/p/first-interview-with-scale-ais-ceo-jason-droege• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Why AI evals are the hottest new skill for product builders | Hamel Husain & Shreya Shankar (creators of the #1 eval course): https://www.lennysnewsletter.com/p/why-ai-evals-are-the-hottest-new-skill• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Stanford webinar—How AI Is Changing Coding and Education, Andrew Ng & Mehran Sahami: https://www.youtube.com/watch?v=J91_npj0Nfw• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann• Lenny's vibe-coded app made on Lovable: https://gdoc-images-grab.lovable.app/• Story of Yanxi Palace: https://www.imdb.com/title/tt8865016/• Steve Jobs's quote: https://www.goodreads.com/quotes/427317-remembering-that-i-ll-be-dead-soon-is-the-most-important—Recommended books:• The Complete Sherlock Holmes: https://www.amazon.com/Complete-Sherlock-Holmes-Volumes/dp/0553328255• AI Engineering: Building Applications with Foundation Models: https://www.amazon.com/AI-Engineering-Building-Applications-Foundation/dp/1098166302• The Selfish Gene: https://www.amazon.com/Selfish-Gene-Anniversary-Introduction/dp/0199291152• From Third World to First: The Singapore Story: 1965-2000: https://www.amazon.com/Third-World-First-Singapore-1965-2000/dp/0060197765—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

SPONSORS: - Upgrade your denim game with Rag & Bone!. Get 20% off sitewide with code NOTTODAY at https://www.rag-bone.com #ragandbonepod - Control Body Odor ANYWHERE with @shop.mando and get 20% off + free shipping with promo code NOTTODAY at https://shopmando.com! #mandopod This week on Not Today Pal, Jamie's got a battle scar and a story to match — she slipped in the shower, split her lip, and had to get emergency stitches on her couch (shoutout Dr. Collins!). Rob's sympathy quickly turns into laughs as they unpack her “tough girl” look and the chaos that followed. Then it's Rob's turn to spiral — after losing every football bet in the final 30 seconds, he declares he might be done with gambling for good (again). The duo dives into everything from Sunday betting trauma and family friendship moments to beard phases, hospital horror stories, and a hilarious deep-dive into what AI thinks about giving women orgasms. Jamie and Rob roast Grok's “sex tips,” debate mid-sex check-ins, and take listener submissions on the most annoying habits of people you live with. It's classic Not Today: oversharing, emotional damage, and too many laughs to count. Have a question for Rob and Jamie? Reach out at nottodaypalpodcast@gmail.com Not Today, Pal Ep. 117 https://www.instagram.com/jamielynnsigler https://www.instagram.com/nottodaypalshow https://store.ymhstudios.com Chapters 00:00:00 - Intro 00:00:24 - Jamie's Lip & Rob's Beard 00:07:06 - Sunday Night Sadness 00:14:09 - A Tender Momemt 00:16:56 - Jamie's Weekly Instagram 00:21:12 - Ask ChatGPT 00:30:33 - Annoying Habits Of People You Live With 00:40:16 - Memory Lane Learn more about your ad choices. Visit megaphone.fm/adchoices

Kacper Łukawski, a Senior Developer Advocate at Qdrant, speaks with host Gregory M. Kapfhammer about the Qdrant vector database and similarity search engine. After introducing vector databases and the foundational concepts undergirding similarity search, they dive deep into the Rust-based implementation of Qdrant. Along with comparing and contrasting different vector databases, they also explore the best practices for the performance evaluation of systems like Qdrant. Kacper and Gregory also discuss topics such as the steps for using Python to build an AI-powered application that uses Qdrant. Brought to you by IEEE Computer Society and IEEE Software magazine.

Matt Fox achieved a life-changing exit and walked away in 90 days!Matt Fox was 72 hours from a multi-seven-figure exit when COVID killed the deal.What followed: a complete breakdown, 2 years of therapy, and a total rebuild.But he did it differently the second time.Cut from 30 stressed employees to 10 people he loved. Stripped costs. Turned it into a cash machine. By 40, he'd cleared his mortgage and bought Spanish properties with cash.Then, in November 2024, he sold the business and walked away in 3 months.In this episode:Why scaling to 30 people nearly destroyed himThe "cash cow" strategy that made him wealthy before the exitHow to build a team that doesn't need youWhat selling a business actually feels like (the bit nobody warns you about)Why 80% of recruitment founders get exits wrongThis isn't your typical scale-and-sell story. This is what it really takes to lose everything, rebuild on your terms, and exit with your sanity intact.For recruitment founders running 5-30 person agencies, wondering what happens next.Chapters00:03:00 Building Dynamite Recruitment00:09:00 Challenges and Resilience00:15:00 Restructuring for Profitability00:21:00 The Sale Process00:27:00 Lessons Learned and Future Plans__________________________________________Episode Sponsor: AtlasAdmin is a massive waste of time. That's why there's Atlas, the AI-first recruitment platform built for modern agencies.It doesn't only track CVs and calls. It remembers everything. Every email, every interview, every conversation. Instantly searchable, always available. And now, it's entering a whole new era.With Atlas 2.0, you can ask anything and it delivers. With Magic Search, you speak and it listens. It finds the right candidates using real conversations, not simply look for keywords.Atlas 2.0 also makes business development easier than ever. With Opportunities, you can track, manage and grow client relationships, powered by generative AI and built right into your workflow.Need insights? Custom dashboards give you total visibility over your pipeline. And that's not theory. Atlas customers have reported up to 41% EBITDA growth and an 85% increase in monthly billings after adopting the platform.No admin. No silos. No lost info. Nothing but faster shortlists, better hires and more time to focus on what actually drives revenue.Atlas is your personal AI partner for modern recruiting.Don't miss the future of recruitment. Get started with Atlas today and unlock your exclusive RAG listener offer at https://recruitwithatlas.com/therag/__________________________________________Episode Sponsor: HoxoEvery recruitment founder is investing in LinkedIn.Spending thousands on Recruiter licences.Building connections. Posting content. Growing networks.But here's the question almost no one can answer:How much revenue is LinkedIn actually bringing into your business?Most founders have thousands of connections but no clear process to turn that attention into cash.That's the problem we solve.At Hoxo, we help recruitment founders build predictable revenue systems on LinkedIn, not just noise or vanity metrics.Our clients are turning LinkedIn into £100K–£300K in new billings within months, using their existing networks and a simple repeatable process.To show you how it works, we've created a short training video exclusively for RAG listeners.In less than 10 minutes, you'll learn:- Why most recruiters are getting zero measurable ROI from LinkedIn- How small, niche teams are generating...

Is this one of the best or worst method books for acoustic fingerstyle guitar? You can learn to play music by simultaneously using a variety of resources including teachers, online resources, and books. Rainer's Acoustic Blues Guitar Picking School, written by Rainer Brunn, is a method book for learning to play solo fingerstyle blues guitar.  The material is generally appropriate for late beginner to intermediate players who want to learn this style.  The material progresses logically from an easy introduction to Travis style/alternating basslines and quickly ramps up to late beginner difficulty.  Text is kept to a minimum, so readers should spend some time analyzing the playing examples.  The entire book is fairly short and concise at 53 pages. The majority of Rainer's Acoustic Blues Guitar Picking School focuses on playing the blues using an alternating bassline, although some examples feature a monotonic bassline.  Each chapter generally features a concise explanation of one or two new concepts (i.e. inner and outer right-hand positions, the “long A” chord shape, hammer-ons, pull-offs, slides, etc.), provides a few playing examples to demonstrate, and finally provides a full 12 or 16 bar blues chorus utilizing the new concepts. My overall impression from going through this book is that it contains valuable information, but it is not as comprehensive as some other books.  You will gain important technical/physical skills to play fingerstyle blues, but there isn't much explanation on how to approach a new blues tune, music theory to help you choose the proper notes while improvising, etc.  Still, some people might prefer the concise text.  My advice would be to work through this book with a teacher or to combine this with another more comprehensive method book.  This book might make a great 2nd or 3rd book in your fingerstyle blues collection.  I got a great workout going through the book, I have immediately begun implementing some of the new ideas and chord shapes into my own playing, and I will be using some of the examples with my students. Chapter by chapter breakdown: Ch. 1: Intro to Travis style/ alt bass in blues keys of E, A, and C.  Intro to syncopation very soon.  If you are new to Travis style, then this will be difficult.  If you have some experience with Travis style, then this will quickly get you sounding bluesy. Ch. 2: Inner and outer RH positions – shifting thumb to pick 4th and 3rd strings while i and m fingers shift to 2nd and 1st strings.  Accompaniment behind a blues tune in D. Ch. 3: “Long A chord” – use pinky to reach 5th fret A note on 1st string.  Introduction of double alternating bass. Ch. 4: Hammer-ons, pull-offs, slides.  Intro to monotonic bass.  Intro to triplets.  Keys of E, G, and D with alt bass.  Intermediate territory. Ch. 5: Shuffle rhythm.  Advanced chord shapes (up the neck) for keys of E, A, D.  This is getting significantly more difficult – too difficult for beginners, in my opinion. Ch. 6: Thumb over the top.  Rag in C – really nice 16-bar tune. Ch. 7: Trickier hammer-ons, pull-offs, and slides over Travis bassline.  Keys of E and A. Ch. 8: Using alternating m and i picking hand fingers.  Lots of cool chromatic melodies. Ch. 9: Accompaniment.  Variations to keep you from playing the same accompaniment pattern over and over. Ch. 10: “Moveable modules” – chordal or interval ideas that can be moved around to fit over different chords/in different keys. Ch. 11: Turnarounds – some good introductory turnarounds to learn and start implementing into your blues playing. Ch. 12: Two blues tunes with discussions/analysis. Videos available online – solid performances of examples that are helpful to view. The book doesn't use the modern percussive techniques used by modern players like Michael Hedges, Don Ross, Andy McKee, Mike Dawes, etc.  No thumb slaps, guitar body percussion, or tapping.

In this explosive episode, former USC football standout Owen Hanson—once living the dream on the field—reveals how he plunged into the dark underworld of the Sinaloa Cartel, moving hundreds of millions in cocaine across continents. Known as “O-Dog”, Hanson opens up about his journey from campus celebrity and sports bookmaker to international drug trafficker working directly with El Chapo's network. Host Johnny Mitchell dives deep into Hanson's transformation—from selling steroids to teammates at USC, to orchestrating high-level cartel deals spanning Peru, Mexico, Australia, and the U.S. Hanson recounts the lavish highs, the paranoia of living double lives, and the eventual FBI sting that brought it all crashing down. Now a free man and entrepreneur, Hanson shares how he rebuilt himself after prison, founding California Ice Protein and using his story to warn others about ego, greed, and the illusion of power. This episode blends crime, redemption, and raw honesty—a gripping story of how a promising athlete became a global kingpin, and how he's now rewriting his legacy. Go Support Owen! Movie: https://www.primevideo.com/detail/Cocaine-Quarterback-Signal-Caller-for-the-Cartel/0ITIO5AR39FDEY5RIG7APVMWF9 Book: https://www.thecaliforniakid.com/ IG: https://www.instagram.com/theofficialcakid/ YouTube: @theofficialcakid This Episode Is #Sponsored By The Following: GLD! Work Hard and Change the Game. For a limited time only, new customers are getting an insane deal. Use code MITCHELL to get 50% Off plus a Free Chain at https://gld.com BetterHelp! This World Mental Health Day, we're celebrating the therapists who've helped millions of people take a step forward. If you're ready to find the right therapist for you, BetterHelp can help you start that journey. Our listeners get 10% off their first month at https://betterhelp.com/CONNECT Rag & Bone! Upgrade your denim game with Rag & Bone! Get 20% off sitewide with code CONNECT at https://rag-bone.com #ragandbonepod Join The Patreon For Bonus Content! https://www.patreon.com/theconnectshow 00:00 Intro: The Rise and Fall of Owen Hansen 01:00 College Football Glory & Wild USC Parties 04:41 Owen Hansen's Documentary & Rebuilding Trust 07:00 From Prison to Entrepreneur: Life After Release 11:00 Logistics of the International Drug Trade 17:00 Creative Smuggling: Wine, Chocolate & Global Routes 18:22 Get A Great Deal From GLD! 20:58 Bookmaking Millions: The Sports Betting Business 35:00 The Art of Collecting Debts & Avoiding Trouble 44:00 Law Enforcement Evasion and Daily Operations 46:58 Today's Sponsors 49:33 Cartel Connections & The Power of Payouts 01:00:00 Scaling Up: Canada, Australia & Moving Big Loads 01:11:00 Money Laundering and Gold: Schemes & Shell Companies 01:19:00 The Fall: Informants, Raids, and Indictments 01:31:00 Warehouse Operations, Canada, and High Volume Moves 01:40:00 High Life Burnout and Personal Toll 01:54:00 Sentencing, Cooperation, and Prison Life 02:03:00 Extradition, Testimony, and Sentence Reduction 02:08:00 Prison Reflections and Survival 02:12:00 Reinvented: Ice Cream Kingpin & The Road Ahead 02:13:00 Final Thoughts: Redemption and New Beginnings Learn more about your ad choices. Visit podcastchoices.com/adchoices

What if the real breakthrough in AI isn't the model itself, but the data that gives it knowledge? In this episode of Tech Talks Daily, I sit down with Edo Liberty, founder and Chief Scientist of Pinecone, to unpack how vector databases have quietly become the backbone of modern AI infrastructure. We explore why retrieval-augmented generation (RAG) works so effectively out of the box, and why fine-tuning large models often adds complexity without real-world value. Edo shares how Pinecone's research revealed that different models—from OpenAI to Anthropic—require differently structured context to perform well, a discovery that's reshaping how enterprises think about AI implementation. As the former Director of Research at Yahoo and AWS, Edo offers a grounded perspective on where the real innovation is happening. He explains how the shift from traditional data structures to vector representations is redefining how machines “know” and retrieve information, creating smarter, context-aware systems. We also touch on his recent transition to Chief Scientist, his excitement for returning to hands-on research, and why he believes the convergence of AI and data represents the defining technological shift of our lifetime. So, what does it mean for developers, business leaders, and anyone building with AI when knowledge becomes an accessible layer of infrastructure? Can we build systems that truly “know” as humans do? Join the conversation, and after listening, I'd love to hear your thoughts—do you think the future of AI lies in the models or in the data that feeds them?

With massive context windows and new agent frameworks, do vector databases still matter? Ram Sriharsha, CTO at Pinecone, joins the conversation to make the definitive case that they're more critical than ever. He explains that at the core of all AI is search, and externalizing this function is non-negotiable for security, auditability, and control.Ram offers a clear starting path for engineering leaders: begin with simple Retrieval-Augmented Generation (RAG) applications, but immediately implement a robust evaluation framework to manage hallucinations and ensure quality. He shares his perspective on the skills that matter most now, arguing that curiosity and the rise of the generalist engineer are critical in an AI-powered world. This episode is a guide to building the AI stack from the ground up, from using AI as a "good junior engineer" for testing to cultivating the engineering mindset of tomorrow.Bring AI into your code review process with LinearBFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Learn more about Pinecone: pinecone.ioPinecone Tutorials & Blog: Explore guides on RAG, vector databases, and moreConnect with Ram Sriharsha: LinkedInReferenced in today's show:Your New 500K AI Coworkers Just ArrivedHow I influence tech company politics as a staff software engineerCoinbase says 40% of code written by AI, mostly tests and TypescriptCelebrating 1 Trillion Web Pages ArchivedSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Be a part of the journey and allow Claptone to transport you to a place of sonic delights, with a mix designed to enchant outside of the club. Follow our golden masked friend and be the first to hear the new editions of the CLAPCAST tale... 01. Armand Van Helden x Hitty – Keep Forgettin' (Extended Mix) [Ministry Of Sound]02. Rag'n'Bone Man, Max Chapman, Mischief – Whisper (Max Chapman & Mischief Terrace Mix) [Defected]03. Lucas & Steve – Push The Feeling On (Extended Mix) [Musical Freedom]04. Huxley – My Mind (Extended Mix) [Club Sweat]05. DJ Gregory – Block Party (Tim Croft Remix) [ID]06. Ammo Avenue – Uprise (Original Mix) [Casa Bonita]07. Dario Núñez, Alex Now (ES) – Dark Beat (Extended Mix) [Golden]08. Roger Sanchez, Gipsy Kings – El Gitano (Dub Edit) [Stealth]09. Space Castorz – Peligrosa (Extended Mix) [Gasolina]10. Chris Lake, The Chemical Brothers – Galvanize (Chris Lake Extended Mix) [Positiva]11. Watermät & James Mac – Make A Livin' (Extended Mix) [Sweat It Out]12. BISCITS – Wrong Is Right (Extended Mix) [Wrong.]13. Sarah Story & Joe Goddard – Keep Needing (Original Mix) [Stories]

We dig into how search is shifting from links to answers, why reputation now outranks tactics, and how to position your brand inside LLMs before it's 10x harder. Ross Barefoot joins Matt to compare notes on pruning, big content, reviews, local, and the reality of client communication.• LLMs as a new gatekeeper layer and why fundamentals still matter• EEAT with real experience, proof, and long‑form content• Reputation first: reviews beyond Google and social mentions• Pruning thin and off‑topic content to clarify entity• RAG, freshness, and Google's role in retrieval• Hidden gems: surfacing forums and long‑tail answers• Merchant Center and local search as stable channels• Measurement gaps, anonymized referrers, and log insights• Social's rising weight in brand visibility• Client education, budgets, and communication systemsGuest Contact Information: Website: eepseo.comLinkedIn: linkedin.com/in/rossbarefootMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online. Now, host Matthew Bertram — creator of LLM Visibility™ and the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability. Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve. Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show

In today's episode we break down all your questions and tell the FULL story of Spennys injury during wine night 3.0. From the Emergency room, Lifeflight Airplane ride, waiting 3 days for surgery in a sketchy hospital, to his possible 3 year recovery. We then breakdown the never before seen bus crash Gavin and Evan had, Ryan's second Hummer Crash, And Kens $10k trip to Europe and our childish pranks. Enjoy the podcast and if you're new here please follow and rate us 5 stars! Sign up for your $1 per month trail at https://www.shopify.com/wideopen Connect with quality therapists and mental health experts who specialize in you at https://www.rula.com/WIDEOPEN #rulapod #ad Get up to $200 off Square hardware when you sign up at https://www.square.com/go/WIDEOPEN! #squarepod #ad Upgrade your denim game with Rag & Bone!. Get 20% off sitewide with code WIDEOPEN at www.rag-bone.com #ragandbonepod #ad To watch the podcast on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/LifeWideOpenYT⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Don't forget to subscribe to the podcast for free wherever you're listening or by using this link: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/LifeWideOpenWithCboysTV⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ If you like the show, telling a friend about it would be amazing! You can text, email, Tweet, or send this link to a friend: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/LifeWideOpenWithCboysTV⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ You can also check out our main YouTube channel CboysTV: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/c/CboysTV⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

A true clearance rack episode for us covering a ton of different style topics — a mea culpa moment for Berghain, the format of Tom Sachs recent drop, mid-range men's fall footwear, designer strollers, an "Are we doing...?" segment, Erewhon goes nationwide, batch cocktails, nostalgic ski hats, Taylor possibly appearing at ACL, wishlist items, and more.Subscribe to the newsletter: retailpod.substack.com willdefries.substack.com Shop the Sunday Scaries Scented Candles: www.vellabox.com/sundayscariesWatch all Retail Therapy episodes on YouTube: www.youtube.com/sundayscariespodcastSupport This Week's SponsorsShopify: www.shopify.com/scaries ($1/month trial!)Rag & Bone: www.rag-bone.com (SCARIES for 20% off)Follow AlongRetail Therapy on Instagram: www.instagram.com/retail.podWill deFries on Twitter: www.twitter.com/willdefriesWill deFries on Instagram: www.instagram.com/willdefries Barrett Dudley on Twitter: www.twitter.com/barrettdudleyBarrett Dudley on Instagram: www.instagram.com/barrettdudleySunday Scaries on Twitter: www.twitter.com/sundayscariesSunday Scaries on Instagram: www.instagram.com/sunday.scaries