Podcasts about SQL

Journalist Lee Sanders is back with a full breakdown, analysis, and reaction to WWE Monday Night RAW – December 15, 2025 live from The Giant Center in Hershey, Pennsylvania

Nik and Michael discuss a listener question about archiving a database. Here are some links to things they mentioned: Listener request to talk about archiving https://www.youtube.com/watch?v=KFRK8PiIvTg&lc=UgyiFrO37gEgUaVhRgN4AaABAg Our episode on “Is pg_dump a backup tool?” https://postgres.fm/episodes/is-pg_dump-a-backup-tool ~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

“Najgorsza część publikacji zajmuje mi około 10 minut - tak zwany Human Touch.” Łukasz opisuje swój system automatyzacji publikacji Patoarchitektów, gdzie AI agents robią transkrypcję, generują SEO, intro i posty - ale ostateczny bottleneck to ręczne poprawianie, bo “wygenerowane posty wychodzą takim korporacyjnym marketingiem, że można rzygać tęczą.” Ironia: cała infrastruktura (K3s w Azure, Claude z MCP, OpenAI Agent SDK, Airtable, RenderForm) działa automatycznie, ale człowiek musi ratować jakość contentu. Stos technologiczny? Agent Jane pobiera transkrypcję przez HappyScribe, ekstraktuje linki z Google Drive Szymona, generuje podsumowania przez Anthropic Sonnet (najlepszy polski), a GPT-5 prowadzi główną logikę. GPT-5 mini sprawdza maile - “tani i wystarczający.” Drugi agent obsługuje sprzedaż szkoleń: dostaje webhook z EasyCart i automatycznie zakłada wydarzenie w kalendarzu, dodaje uczestników. Szymon: “To był killer feature.” Kluczowa lekcja? “Agenty stosujemy tam, gdzie na wejściu mamy gołego teksta lub bloba.” Przewidywalne rzeczy to zwykły kod - webhooks, crony, API. Event-driven architecture, gdzie “LLM nie czeka proaktywnie” - wzbudza go cron w czwartki o 18:00. Czy Twój stack publikacji też wymaga Human Touch, żeby nie brzmiało jak korpo? Sprawdź, zanim MCP wygeneruje Ci tęczowy marketing.

Episode 312 - Power BI November 2025 Feature Summary by John White & Jason Himmelstein

Ian and Aaron discuss how Aaron's orchestrating fly.io boxes for Database School, why sometimes you need to use AI to help AI, and why Costco is truly a great place.  Plus an all-time Ian resume rant and so much more.Sponsored by Bento, Flare, Ittybit, tldraw, OG Kit, Tighten, and NusiiInterested in sponsoring Mostly Technical?  Head to https://mostlytechnical.com/sponsor to learn more.(00:00) - Classic Little Kid Disease (04:14) - Weekend Update (18:29) - Ian's Resume Rant (33:57) - Advent of SQL (46:50) - Using AI to Help AI Links:Google ClassroomNorthPark CenterDanbury Railway MuseumMelissa & DougThomas & FriendsAdvent of SQL on Database SchoolCodeRabbitStratechery

Dans cet épisode, on découvre Nicolas, ex-développeur Java et SQL, qui tombe sur Bubble presque par hasard… et voit tout son rapport au développement basculer.Il réalise qu'avec le No-Code, il peut enfin créer un front sans réinventer la roue, glisser une authentification en deux clics, tester plus vite, et surtout… s'amuser.C'est aussi lui qui a fait parler de lui dans la communauté en créant Snake dans Notion, une prouesse aussi absurde que géniale qui l'a rendu immédiatement reconnaissable.Aujourd'hui, Nicolas partage son temps entre du support technique et de l'animation de communauté pour le bootcamp de Vincent de Krea.city, du vibe coding avec Claude Code, et l'exploration d'un futur plus hybride où No-Code, logique JS et agents IA se rencontrent.Un épisode drôle, vivant et terriblement attachant.https://www.linkedin.com/in/nicolas-mothiron

In this episode of The Effortless Podcast, Amit Prakash and Dheeraj Pandey dive deep into one of the most important shifts happening in AI today: the convergence of structured and unstructured data, interfaces, and systems.Together, they unpack how conversations—not CRM fields—hold the real ground truth; why schemas still matter in an AI-driven world; and how agents can evolve into true managers, coaches, and chiefs of staff for revenue teams. They explore the cognitive science behind visual vs conversational UI, the future of dynamically generated interfaces, and the product depth required to build enduring AI-native software.Amit and Dheeraj break down the tension between deterministic and probabilistic systems, the limits of prompt-driven workflows, and why the future of enterprise AI is “both-and” rather than “either-or.” It's a masterclass in modern product, data design, and the psychology of building intelligent tools.Key Topics & Timestamps 00:00 – Introduction02:00 – Why conversations—not CRM fields—hold real ground truth05:00 – Reps as labelers and the parallels with AI training pipelines08:00 – Business logic vs world models: defining meaning inside enterprises11:00 – Prompts flatten nuance; schemas restore structure14:00 – SQL schemas as the true model of a business17:00 – CRM overload and the friction of rigid data entry20:00 – AI agents that debrief and infer fields dynamically23:00 – Capturing qualitative signals: champions, pain, intent26:00 – Multi-source context: transcripts, email threads, Slack29:00 – Why structure is required for math, aggregation, forecasting32:00 – Aggregating unstructured data to reveal organizational issues35:00 – Labels, classification, and the limits of LLM-only workflows38:00 – Deterministic (SQL/Python) vs probabilistic (LLMs) systems41:00 – Transitional workflows: humans + AI field entry44:00 – Trust issues and the confusion of the early AI market47:00 – Avoiding “Clippy moments” in agent design50:00 – Latency, voice UX, and expectations for responsiveness53:00 – Human-machine interface for SDRs vs senior reps56:00 – Structured vs unstructured UI: cognitive science insights59:00 – Charts vs paragraphs: parallel vs sequential processing1:02:00 – The “Indian thali” dashboard problem and dynamic UI1:05:00 – Exploration modes, drill-downs, and empty prompts1:08:00 – Dynamic leaves, static trunk: designing hierarchy1:11:00 – Both-and thinking: voice + visual, structured + unstructured1:14:00 – Why “good enough” AI fails without deep product1:17:00 – PLG, SLG, data access, and trust barriers1:20:00 – Closing reflections and the future of AI-native softwareHosts: Amit Prakash – CEO and Founder at AmpUp, former engineer at Google AdSense and Microsoft Bing, with extensive expertise in distributed systems and machine learningDheeraj Pandey – Co-founder and CEO at DevRev, former Co-founder & CEO of Nutanix. A tech visionary with a deep interest in AI, systems, and the future of work.Follow the Hosts:Amit PrakashLinkedIn – Amit Prakash I LinkedInTwitter/X – https://x.com/amitp42Dheeraj PandeyLinkedIn –Dheeraj Pandey | LinkedIn Twitter/X – https://x.com/dheerajShare your thoughts : Have questions, comments, or ideas for future episodes?Email us at EffortlessPodcastHQ@gmail.comDon't forget to Like, Comment, and Subscribe for more conversations at the intersection of AI, technology, and innovation.

Bentornati e bentornate su Azure Italia Podcast, il podcast in italiano su Microsoft Azure!Per non perderti nessun nuovo episodio clicca sul tasto FOLLOW del tuo player

Journalist Lee Sanders is back with exclusive predictions and breakdowns for WWE Saturday Night's Main Event — December 13, 2025! Tonight isn't just any SNME — it's the emotional farewell of one of the greatest in WWE history: John Cena. After more than 20 years at the top, Cena wrestles one last time against Gunther in what's being billed as his final WWE match ever.

In this bonus episode of Banking on Fraudology, powered by Safeguard , Hailey Windham talks with Ben Graf, a self-taught AI expert in the neobank space. Ben embodies the spirit of curiosity and courage driving the next wave of fraud-fighting transformation.The conversation dives into what it really looks like to learn AI from the ground up, emphasizing that the future of fraud prevention isn't about replacing people, but empowering them through technology.Key Takeaways: AI, Innovation, and Fraud-Fighting EmpowermentUsing AI to Learn AI: Ben explains how he used varying LLM chats (like ChatGPT, Claude, and Gemini) as a coach or mentor, experimenting for hours to understand their capabilities, consistency, and how to effectively prompt them.This approach helped him translate technical language and practices (like data analysis, SQL, and JavaScript) into actionable knowledge for his team, breaking down communication barriers.The hardest part was knowing where to start, but the key was realizing that "something is better than nothing" and compounding knowledge quickly breaks down barriers.Practical AI Applications for Eliminating Busy Work: AI should be used to make teams more efficient and help professionals focus strategically.Automating Document Verification: AI can use OCR to pull data, flag inconsistencies, and serve up summaries for identity, business, and income documents, which are often the most time-consuming parts of a review.Data Retrieval and System Silos: AI can help team members write their own SQL queries to retrieve data from data warehouses, dramatically reducing requests to the data team.Product and Feature Proposals: AI tools can mock up full dashboard concepts and even provide code snippets to give engineers a visual and break down communication barriers between fraud and technical teams.The Power of Empowerment and Buy-In: Leadership should create a culture where fraud fighters are empowered to explore and innovate.The magic of time savings lies in filling the time freed from "busy work" (like false positives) with new, high-impact tasks, whether that's cost savings in fraud loss or better customer retention.Teams are advised to keep proprietary or PII information out of the loop and find safe spaces to explore, remembering that everyone is still figuring out what AI can do.Get in the mood of being grateful for the fraud-fighting community, and be reminded of how strong the fraud-fighting community truly is. About Hailey Windham:As a 2023 CU Rockstar Recipient, Hailey Windham, CFCS (Certified Financial Crimes Specialist) demonstrated unbounding passion for educating her community, organization and credit union membership on scams in the market and best practices to avoid them. She has implemented several programs within her previous organizations that aim at holistically learning about how to prevent and detect fraud targeted at membership and employees. Windham's initiatives to build strong relationships and partnerships throughout the credit union community and industry experts have led to countless success stories. Her applied knowledge of payments system programs combined with her experience in fraud investigations offers practical concepts that are transferable, no matter the organization's size. Connect with Hailey on LinkedIn: https://www.linkedin.com/in/hailey-windham/

“Billions of Agents - każdy z nas będzie miał minimum 10 agentów.” Łukasz cytuje oficjalny przekaz AWS re:Invent 2025, ale prawdziwy przekaz konferencji jest głębszy: hyperscalerzy mają realną przewagę w dostępie do GPU i infrastruktury do trenowania modeli. AWS Clean Rooms, Nova Forge, AI Factory - to ekosystem do łatwego fine-tuningu bez konieczności budowania własnej farmy GPU. A adopcja własnych modeli AWS? Wszyscy używają Anthropic Claude na Bedrocku, nikt Amazon Nova. Szymon wybiera Nova Act jako najlepsze ogłoszenie: “Najciekawsze podejście z całej konferencji” - RPA z agentami AI do automatyzacji starych systemów przez przeglądarkę. AWS Transform? “Eksplozje, wybuchy, beżowe pecety z lat 90. I disclaimer: AWS realnie nie wykorzystuje materiałów wybuchowych.” Modernizacja COBOL-a, mainframe'ów, webforms do Blazora (“Ktoś poza Microsoftem używa słowa Blazor”), aktualizacja SDK, Terraform, CloudFormation. Lambda na EC2 to gwoździem do trumny: “Pamiętasz migrację Prime'a z Lambdy na EC2, bo koszty były za duże? Już by nie musieli.” 97 newsów, w tym Bedrock z 18 modelami open source, wektory w S3, EKS z Argo CD, Kiro jako kolejny fork VS Code. 97 newsów z AWS re:Invent - ale czy któryś naprawdę zmieni coś w Twojej pracy?

Journalist Lee Sanders is back talking WWE RAW 12/8/25 full show review, results, highlights as we break down tonight's episode live from the T-Mobile Center. RAW 12/8/25 Lineup: AJ Styles & Dragon Lee (c) vs. The War Raiders — WWE World Tag Team Championship Match Rey Mysterio vs. Finn Bálor Lyra Valkyria vs. Roxanne Perez Live appearance from Stephanie Vaquer Promo segment from GUNTHER following his tournament win as he faces John Cena in Cena's final match this Saturday December 13th in Washington, D.C. at SATURDAY NIGHT'S MAIN EVENT Prayers up to CM Punk and AJ Lee as their dog Larry passed away Lee reflects on the passing of his dog Maggie over a year ago and the best piece of advice for first time pet owners Prayers up for a friend of the family who's about to lose his battle to cancer in the coming days.——————————————————————

The 'D' Got Deleted: How VC Funding Broke the Innovation EcosystemLast week's whitepaper isn't production-ready. But someone's already pitching it to your board. Kence Anderson has deployed 100+ autonomous AI systems for Fortune 500 companies—and watched venture capital create a research-to-PR pipeline that skips development entirely. The 'D' in R&D got deleted. Hype cycles got amplified.Rule-based AI—systems encoding expertise as decision logic—was the 1980s breakthrough. Overhyped, then abandoned when it couldn't do everything. But engineers kept deploying it where codified rules excel: industrial controls, diagnostics, compliance. It's running critical infrastructure today. Every AI wave follows this arc. For leaders, the lesson: stop asking which technology wins. Ask what each does well—and build modular systems that match capabilities to tasks. The fix: if AI can learn, someone should teach it the right way. Machine teaching—goals, scenarios, strategies—creates modular agents that compound capability through orchestration.Paradigm Shifts:

This Podcast is sponsored by Team Simmer.Go to TeamSimmer and use the coupon code DEVIATE for 10% on individual course purchases.The Technical Marketing Handbook provides a comprehensive journey through technical marketing principles.Sign up to the Simmer Newsletter for the latest news in Technical Marketing.Latest content from Simo AhavaRun Server-side Google Tag Manager On Localhost Article Latest content from Juliana JacksonThe sin, the oil, the crack and the crisis ArticleSign up for a the very first Google x Jellyfish Cloud Talks event, 15th of January, Copenhagen - The very first event focused on the use of Google Cloud Technology & AI for Marketing.Huge thanks to TRKKN & Analytics Summit for having us over to do this in front of a fantastic audience, we had an amazing time.TRKKNAnalytics Summit This podcast is brought to you by Juliana Jackson and Simo Ahava.

Welcome to AI Unraveled (December 09, 2025): Your daily strategic briefing on the business impact of AI.1. OpenAI's ‘State of Enterprise AI' Report OpenAI released insights from over 1 million workplace accounts, revealing a massive "productivity gap."The Gains: 75% of workers say AI improved speed/quality; another 75% can now handle tasks they previously couldn't (e.g., marketers writing SQL).Time Saved: Average users save 40–60 mins/day. Power users save 10+ hours/week.Top Performers: The top 5% of users send 6x more messages than the median; top coders show a 17x volume difference.2. Google Returns to Smart Glasses (2026) Google is re-entering the wearables market to challenge Meta.Partners: Hardware by Samsung; design by Warby Parker (backed by a $150M deal) and Gentle Monster.The Tech: Two styles—audio-only (hands-free Gemini) and display versions (in-lens nav/translation). Processing offloads to smartphones to keep frames light.3. Trump's "Chip Tax": H200 Sales to China President Trump approved Nvidia to ship high-grade H200 chips to China, with a catch: the US government takes a 25% cut.The Shift: This reverses previous bans on high-end exports.Expansion: Trump claims Xi Jinping reacted positively; the deal may extend to AMD and Intel.4. Anthropic brings Claude Code to Slack Anthropic launched a beta integration turning Slack into a coding workflow.How it works: Tag @Claude in a thread. It analyzes context (bug reports), selects the right repo, writes code, and posts pull requests—all without leaving Slack.5. Regulatory Wars: EU vs. Google & Trump vs. StatesEU Probe: The EU is investigating if Google abuses dominance by scraping publisher content for AI without paying, forcing an "all-or-nothing" choice on creators.US Preemption: Trump plans a "one rule" executive order to kill state-level AI laws (like California's), arguing 50 different rulebooks would "destroy AI in its infancy."6. Market Watch: Bubbles & AdsValuations: 2-month-old startup Unconventional AI raised $475M at a $4.5B valuation (121x the median seed). Mira Murati's Thinking Machines hit $12B pre-product.Ads: Google denies reports of imminent ads in Gemini, but pressure to monetize the massive AI infrastructure spend is rising.KeywordsOpenAI Enterprise Report, Google Smart Glasses, Nvidia H200, Chip Tax, Claude Code, Slack Integration, AI Antitrust, Federal Preemption, AI Bubble, Unconventional AI, Etienne Noumen, Corporate Podcasting

In this week's Security Sprint, Dave and Andy covered the following topics:Warm Open:• TribalHub Magazine, Winter 2025: A Publication For Technology Minded Professionals In Tribal Government Tribal Health, Tribal-Gaming And Non-Gaming Tribal Enterprises. Includes Tribal-ISAC happenings!• React2Shell: Risky Bulletin: APTs go after the React2Shell vulnerability within hours & Critical Security Vulnerability in React Server Components • We discussed our daily SUN and Weekly Ransomware & Data Breach Digest available via Gate 15's GRIP: Join the GRIP! Gate 15's Resilience and Intelligence Portal (GRIP) utilizes the robust capabilities available in Cyware's Collaborate platform to provide the community with technology-enhanced, human-driven analysis products. Further, our team supports the implementation and use of Cyware Collaborate at the Enterprise level. Main Topics:FinCEN Issues Financial Trend Analysis on Ransomware. The U.S. Department of the Treasury's Financial Crimes Enforcement Network (FinCEN) is issuing a Financial Trend Analysis on ransomware incidents in Bank Secrecy Act (BSA) data between 2022 and 2024, which totaled more than $2.1 billion in ransomware payments… Previous FinCEN Financial Trend Analyses have focused on reported ransomware payments and incidents by the date the activity was filed with FinCEN. Today's report shifts the focus to the incident date of each ransomware attack and offers greater visibility into the activities conducted by ransomware actors.• Reported Ransomware Incidents and Payments Reach All-Time High in 2023• FinCEN Data Shows Ransomware Payments Top $2.1B in Just Three Years• Financial Services, Manufacturing, and Healthcare were the Most Impacted Industries• The Onion Router (TOR) was the Most Common Communication Method Reported• ALPHV/BlackCat was the Most Prevalent Ransomware Variant Between 2022 and 2024• FinCEN analysis shows scope of ransomware problemFive-page draft Trump administration cyber strategy targeted for January release; The six-pillar document covers a lot of ground in a short space, and could be followed by an executive order implementing it, according to sources familiar with the draft. America 250: Presidential Message on the Anniversary of the Monroe Doctrine• Here's what the new National Security Strategy says about threats to critical infrastructure• New US National Security Strategy reveals Trump administration's latest stance on TaiwanFBI PSA: Criminals Using Altered Proof-of-Life Media to Extort Victims in Virtual Kidnapping for Ransom Scams. The Federal Bureau of Investigation (FBI) warns the public about criminals altering photos found on social media or other publicly available sites to use as fake proof of life photos in virtual kidnapping for ransom scams. The criminal actors pose as kidnappers and provide seemingly real photos or videos of victims along with demands for ransom payments… Criminal actors typically will contact their victims through text message claiming they have kidnapped their loved one and demand a ransom be paid for their release. Oftentimes, the criminal actor will express significant claims of violence towards the loved one if the ransom is not paid immediately. The criminal actor will then send what appears to be a genuine photo or video of the victim's loved one, which upon close inspection often reveals inaccuracies when compared to confirmed photos of the loved one. Examples of these inaccuracies include missing tattoos or scars and inaccurate body proportions. Criminal actors will sometimes purposefully send these photos using timed message features to limit the amount of time victims have to analyze the images.Quick Hits:• US leader of global neo-Nazi terrorist group signals retribution for arrests• ASD: Information stealers are on the rise, are you at risk? • UK NCSC: Prompt injection is not SQL injection (it may be worse)

Jason Ash, Chief of Data at Symetra, joins the show to unpack how a mid sized insurer is rebuilding its data stack and culture so business and technology actually pull in the same direction. He shares how his team brings actuaries, product leaders, and engineers into one data platform, and why opening that platform to non technical contributors has been a turning point. If you work in a regulated industry and are trying to move faster with data, this conversation gives you a very practical view of what it takes.Key takeaways• Business and tech only work when they share context and trustJason has sat in both seats, first as an actuary and now as a data and engineering leader. That dual background helps him translate between risk, regulation, and modern data practices, and it shapes how he frames projects around shared business outcomes rather than tools.• Put data leaders inside business line leadership, not on the outsideSeveral of Jason's managers sit on the leadership teams for Symetra's life, retirement, and group benefits divisions. They hear priorities and constraints at the same time as product and distribution leaders, which lets them frame data as a value add for new products instead of a back office cost.• Treat the warehouse as a shared product and measure contributors, not just tablesSymetra's dbt based warehouse started with about five contributors. Over three years they grew that to more than sixty, and half of those people sit outside the core data team. Business users learn to contribute SQL, documentation, and domain knowledge directly into the repo, which spreads ownership and reduces bottlenecks.• Shift stakeholders away from big bang launches to steady deliveryJason pushes his teams to think like software engineers. Rather than promising a perfect data product on a single date, they deliver an early slice of data, have partners use it right away, collect feedback, and improve every month. That builds trust and avoids the usual disappointment that comes with one big release.• Use maturity as a guide for where to investEarly on, his group picked a few strong champions who were willing to accept slower delivery in exchange for building real infrastructure. Now that the platform and practices are in place, the focus is on scale, reuse, and getting more people to build on the same foundation, including as AI capabilities start to reshape the work.Timestamped highlights00:53 Jason explains what Symetra actually does and how their product mix makes data work more complex than the company size might suggest02:19 From actuary to Chief of Data, and what sitting on both sides of the fence taught him about business and technology expectations08:08 Why mixing data engineers, data scientists, actuaries, and analysts on the same problems leads to stronger solutions than any single discipline alone13:44 How embedding data leaders into each business division's leadership group changed when and how data enters product discussions16:38 The dbt story at Symetra, and how more than sixty people across the company now contribute directly to the shared data warehouse26:22 Moving away from big bang data launches and setting expectations around early value, continuous feedback, and ongoing quality improvements32:06 The tension between safety and speed as AI advances, and what Jason worries about most for established insurers that move too slowlyPractical moves you can steal• Put data leaders on business line leadership teams so they hear priorities and constraints in real time, not after the roadmap is set• Track how many unique people contribute to your data warehouse and make that a visible success metric across the companyStay connectedIf this episode helped you think differently about data leadership in regulated industries, share it with a colleague who owns product, data, or actuarial work.

Lee & Tammy Sanders are back! The holidays roll on and on this episode of WRESTLING with the TOPICS, the gang talk holiday shopping stress, gift ideas, and the growing popularity of Ancestry DNA kits—including what people really need to think about before gifting personal genetic data in 2025.From there, we shift into D.C. Mayor Muriel Bowser officially stepping down, the early media framing surrounding her exit, and what this moment means for the city going forward. Tams also sounds off on her Washington Commanders, the season so far, and the emotional rollercoaster that continues to define the franchise.Then we move into the viral side of the internet with reactions to the latest public freakout dubbed Cinnabon Karen, and why these moments continue to dominate social media culture. We also discuss a disturbing national headline involving a Kansas teacher accused of misconduct with a student, and the ongoing concerns about accountability, safety, and systemic failures that keep showing up in stories like this.From real-world chaos to wrestling business moves, we break down TNA WRESTLING officially landing a major television deal with AMC, what it means for live programming, production upgrades, long-term growth, and how the WWE–TNA relationship factors into this next chapter. We react to TNA President Carlos Silva's detailed comments on audience expectations, creative integration, and how AMC plans to embed itself into the product.We also tackle the developing controversy surrounding **Sarah Stock's public accusations against AEW, including claims of corruption, unsafe priorities, and talent neglect, along with the sharply divided reactions from wrestlers and fans as AEW remains silent.On the media business side, we dive into Netflix announcing plans to acquire Warner's premium studio assets, including HBO and Warner Bros. Studios, while spinning off the traditional cable networks into a separate publicly traded company pending regulatory approval—and what that means for wrestling, sports, and entertainment distribution.From boardrooms to the ring, **John Cena reveals his original retirement vision was a massive 220-date farewell tour, before WWE scaled it down to just 36 appearances. We also break down the **new federal lawsuit involving WWE, TKO, and John Cena** over the long-standing “The Time Is Now” theme song, with claims of unlicensed sampling and copyright infringement.As always, it's an unfiltered mix of wrestling, media, controversy, and cultural conversation—all in one place.——————————————————————

Matan Yungman is our special host for today, who came especially to talk about his special project called "Rapido", which is capable of automatically tuning SQL queries at scale. Perhaps there is some inspiration in it for us? Relevant links: Matan Yungman | LinkedIn Matan Yungman (@MatanYungman) / X SQL Server 2025 is Now Generally Available | Microsoft Community Hub Intelligent Query Processing - SQL Server | Microsoft Learn  

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

Every once in awhile we release a new episode free for all to see, and today is that day! Please enjoy this episode, and if you find this interesting you may want to consider a subscription https://www.pointfree.co/pricing. --- We give a tour of our SQLiteData library, a fast and lightweight alternative to SwiftData. We'll set up a fresh project with the package, define models and configure the database, and even write SQL migrations with the help of Xcode's Coding Assistant.

Podcasting 2.0 December 5th 2025 Episode 243: "Nuts & Logs" Adam & Dave poddy training, junie, major dev talk and more! ShowNotes We are LIT NYC? Alby Hub? AI stats analysis Alt Enclosure Video New aggregatory open build GitHub - Podcastindex-org/feedparser: The XML parser that converts saved podcast feeds into intermediary files for SQL ingestion. TTS Podcasts on OP3 Cloudflare Outage Decentralization Transcript Search What is Value4Value? - Read all about it at Value4Value.info V4V Stats Last Modified 12/05/2025 14:32:55 by Freedom Controller

Nik and Michael discuss max_connections, especially in the context of increasing it to solve problems like migrations intermittently failing(!) Here are some links to things they mentioned: max_connections https://www.postgresql.org/docs/current/runtime-config-connection.html#GUC-MAX-CONNECTIONSTweet about deployments vs connections issue https://x.com/brankopetric00/status/1991394329886077090Nik tweet in response https://x.com/samokhvalov/status/1991465573684027443Analyzing the Limits of Connection Scalability in Postgres (blog post by Andres Freund) https://www.citusdata.com/blog/2020/10/08/analyzing-connection-scalability/Exponential Backoff And Jitter (blog post by Marc Brooker) https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

Podcasting 2.0 December 5th 2025 Episode 243: "Nuts & Logs" Adam & Dave poddy training, junie, major dev talk and more! ShowNotes We are LIT NYC? Alby Hub? AI stats analysis Alt Enclosure Video New aggregatory open build GitHub - Podcastindex-org/feedparser: The XML parser that converts saved podcast feeds into intermediary files for SQL ingestion. TTS Podcasts on OP3 Cloudflare Outage Decentralization Transcript Search What is Value4Value? - Read all about it at Value4Value.info V4V Stats Last Modified 12/05/2025 14:32:55 by Freedom Controller

Journalist Lee Sanders is back with your WWE RAW 12/1/25 Review, results, and full fallout from WWE Survivor Series: WarGames 2025!We are 48 hours removed from an explosive Survivor Series, and Monday Night RAW is bringing the heat with championship action, tournament semifinals, and major storyline developments — including CM Punk DEMANDING answers about the mysterious masked attacker! Plus, what's NEXT for THE VISION after their huge Survivor Series moment? We're breaking everything down with analysis, reactions, and honest insight you can only get from THE RCWR SHOW.

Zapier's first PM and now VP of Product Chris Geoghegan joins us to discuss the relationship between deterministic and LLM-powered automations, scaling a transparent and fully-remote company from millions in revenue to hundreds of millions, whether PM roles are becoming more or less important today, disrupting yourself before anybody else does, and the value of knowing SQL. Chris Geoghegan on LinkedIn Cursor for PMs course from Tal Raviv Have feedback for the show? Send an email or message to Allen any time. It Shipped That Way is supported by Steamclock Software and Forestwalk Labs.

In this episode, Cliff Crosland, CEO & co-founder of Scanner.dev, shares his candid journey of trying (and initially failing) to build an in-house security data lake to replace an expensive traditional SIEM.Cliff explains the economic breaking point where scaling a SIEM became "more expensive than the entire budget for the engineering team". He details the technical challenges of moving terabytes of logs to S3 and the painful realization that querying them with Amazon Athena was slow and costly for security use cases .This episode is a deep dive into the evolution of logging architecture, from SQL-based legacy tools to the modern "messy" data lake that embraces full-text search on unstructured data. We discuss the "data engineering lift" required to build your own, the promise (and limitations) of Amazon Security Lake, and how AI agents are starting to automate detection engineering and schema management.Guest Socials -⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cliff's Linkedin Podcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠If you are interested in AI Cybersecurity, you can check out our sister podcast -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AI Security Podcast⁠Questions asked:(00:00) Introduction(02:25) Who is Cliff Crosford?(03:00) Why Teams Are Switching from SIEMs to Data Lakes(06:00) The "Black Hole" of S3 Logs: Cliff's First Failed Data Lake(07:30) The Engineering Lift: Do You Need a Data Engineer to Build a Lake?(11:00) Why Amazon Athena Failed for Security Investigations(14:20) The Danger of Dropping Logs to Save Costs(17:00) Misconceptions About Building Your Own Data Lake(19:00) The Evolution of Logging: From SQL to Full-Text Search(21:30) Is Amazon Security Lake the Answer? (OCSF & Custom Logs)(24:40) The Nightmare of Log Normalization & Custom Schemas(28:00) Why Future Tools Must Embrace "Messy" Logs(29:55) How AI Agents Are Automating Detection Engineering(35:45) Using AI to Monitor Schema Changes at Scale(39:45) Build vs. Buy: Does Your Security Team Need Data Engineers?(43:15) Fun Questions: Physics Simulations & Pumpkin Pie

This is episode 311 recorded on November 25th, 2025, where John & Jason talk with Stephanie Bruno, Data Platform MVP & Data Witch, about the news coming out of Microsoft Ignite. For show notes please visit www.bifocal.show

Destaney talks with Gibby, BTR Media's Head of DSP, to break down how he uses AMC, DSP, and AI tools like ChatGPT to build custom reports and audiences that actually prove incremental value. Gibby shares how he went from zero coding experience to writing SQL for AMC, how to turn black box data into actionable insights, and why strong prompts and strategy matter more than ever in Amazon Ads.Connect with Gibby on Linkedin: linkedin.com/in/gibby-h-2132b71a4Connect with Destaney on Linkedin: linkedin.com/in/destaney-wishonSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

After a brief hiatus, we are back to discuss the evolution of a modern trading workflow. In this episode, we cover the transition from standard spreadsheets to custom, AI-built Python tools—including a new voice-to-text trade logger and qualitative scanners based on "Rule Breaker" investing principles.We also dive deep into current market mechanics, blending old-school sentiment analysis with new-school data. We break down the "Investor Day" top in Nvidia, why the disappearance of the MicroStrategy (MSTR) premium removes a critical bid for Bitcoin, and why China and commodities might be the next contrarian play.Key Topics:Workflow Evolution: leveraging Claude to build SQL databases and voice-logging tools.Market Psychology: How "Investor Days" and retail euphoria signal tops (The NVDA example).The Crypto Thesis: Why MSTR losing its ability to issue equity at a premium signals a potential drop for Bitcoin to the $50k–$60k range.Global Macro: A contrarian look at China and commodities amidst the AI arms race.

Journalist Lee Sanders is back with your WWE Survivor Series 2025 POST SHOW & REVIEW! We're breaking down all the big moments from San Diego including John Cena defending the Intercontinental Championship, the All-Star Men's War Games match, and the stacked Women's War Games showdown. Full results, reactions, analysis, and standout performances from tonight's premium live event. Plus backstage notes, crowd reactions, and the full fallout heading into RAW and SmackDown.WWE Survivor Series 2025 — Match Card-Men's WarGames Match: Cody Rhodes, CM Punk, Roman Reigns, Jey Uso & Jimmy Uso vs. Brock Lesnar, Drew McIntyre, Logan Paul, Bron Breakker & Bronson Reed-Women's WarGames Match: AJ Lee, Alexa Bliss, Charlotte Flair, IYO SKY & Rhea Ripley vs. Becky Lynch, Asuka, Kairi Sane, Nia Jax & Lash Legend-Intercontinental Championship: John Cena (c) vs. Dominik Mysterio-Women's World Championship: Stephanie Vaquer (c) vs. Nikki Bella

Happy Thanksgiving week friends! Today we're celebrating a turkey and pie overload by sharing another fun tale of pentest pwnage! It involves using pygpoabuse to hijack a GPO and turn it into our pentesting puppet!  Muahahahahaah!!!!  Also: This week over at 7MinSec.club we looked at how to defend against some common SQL attacks We're very close to offering our brand new LPLITE:GOAD 3-day pentest course (likely in mid-January). It will get announced on 7MinSec.club first, so please make sure you're subscribed there (it's free!) Did you miss our talk called Should You Hire AI Run Your Next Pentest?  Check it out on YouTube!

At Qdrant Conference, builders, researchers, and industry practitioners shared how vector search, retrieval infrastructure, and LLM-driven workflows are evolving across developer tooling, AI platforms, analytics teams, and modern search research.Andrey Vasnetsov (Qdrant) explained how Qdrant was born from the need to combine database-style querying with vector similarity search—something he first built during the COVID lockdowns. He highlighted how vector search has shifted from an ML specialty to a standard developer tool and why hosting an in-person conference matters for gathering honest, real-time feedback from the growing community.Slava Dubrov (HubSpot) described how his team uses Qdrant to power AI Signals, a platform for embeddings, similarity search, and contextual recommendations that support HubSpot's AI agents. He shared practical use cases like look-alike company search, reflected on evaluating agentic frameworks, and offered career advice for engineers moving toward technical leadership.Marina Ariamnova (SumUp) presented her internally built LLM analytics assistant that turns natural-language questions into SQL, executes queries, and returns clean summaries—cutting request times from days to minutes. She discussed balancing analytics and engineering work, learning through real projects, and how LLM tools help analysts scale routine workflows without replacing human expertise.Evgeniya (Jenny) Sukhodolskaya (Qdrant) discussed the multi-disciplinary nature of DevRel and her focus on retrieval research. She shared her work on sparse neural retrieval, relevance feedback, and hybrid search models that blend lexical precision with semantic understanding—contributing methods like Mini-COIL and shaping Qdrant's search quality roadmap through end-to-end experimentation and community education.SpeakersAndrey VasnetsovCo-founder & CTO of Qdrant, leading the engineering and platform vision behind a developer-focused vector database and vector-native infrastructure.Connect: https://www.linkedin.com/in/andrey-vasnetsov-75268897/Slava DubrovTechnical Lead at HubSpot working on AI Signals—embedding models, similarity search, and context systems for AI agents.Connect: https://www.linkedin.com/in/slavadubrov/Marina AriamnovaData Lead at SumUp, managing analytics and financial data workflows while prototyping LLM tools that automate routine analysis.Connect: https://www.linkedin.com/in/marina-ariamnova/Evgeniya (Jenny) SukhodolskayaDeveloper Relations Engineer at Qdrant specializing in retrieval research, sparse neural methods, and educational ML content.Connect: https://www.linkedin.com/in/evgeniya-sukhodolskaya/

John and Bobby broke down how RAG actually works and why the real battle isn't the LLM, it's the chaos sitting in PDFs, Excel files, post-job reports, random folder structures, and handwritten scans. They showed how extraction, chunking, and embeddings fall apart when data is messy, and why clean structure, good metadata, and consistent organization matter way more than people want to admit. They also hit on how tools like MCP and text-to-SQL let AI pull from WellView, production systems, and databases in one place, instead of everyone living in 20 different apps. The takeaway was simple: AI gets powerful fast when the data is ready, but if the inputs are junk, you'll just get faster junk back.Click here to watch a video of this episode.Join the conversation shaping the future of energy.Collide is the community where oil & gas professionals connect, share insights, and solve real-world problems together. No noise. No fluff. Just the discussions that move our industry forward.Apply today at collide.ioClick here to view the episode transcript. https://twitter.com/collide_iohttps://www.tiktok.com/@collide.iohttps://www.facebook.com/collide.iohttps://www.instagram.com/collide.iohttps://www.youtube.com/@collide_iohttps://bsky.app/profile/digitalwildcatters.bsky.socialhttps://www.linkedin.com/company/collide-digital-wildcatters

Journalist Lee Sanders is back with his WWE RAW November 24th, 2025 results and post-show review, live from Oklahoma City as we head into Survivor Series: WarGames (2025). Tonight's show features:-Roman Reigns opening the program ahead of War Games. -The quarterfinal matches of the “Last Time Is Now” tournament:-Gunther vs. Carmelo Hayes -Penta vs. Solo Sikoa-Rey Mysterio vs. JD McDonagh — another announced match added for tonight. -A segment where Dominik Mysterio will send a direct message to John Cena ahead of their showdown. -Becky Lynch appears to address her controversial loss and what's next for her. Plus, the headline round-up:-Lee gives his rating & ranking for AEW Full Gear-Thoughts on Tony Khan's follow-up interview with Ariel Helwani-A quick wrap on the referenced weekend joint event between WWE & AAA (Alianza)-What's happening with the Washington Commanders: injuries, coaching changes, and next steps-The entertainment update: how the movie Wicked is doing at the box office

Over his 15-year journey through healthcare and financial services security, Ken Bowles, now Director of Security Operations at GreenSky, has collected a plethora of practical strategies for prioritizing crown jewels, managing cloud over-permissions, and building SOCs that scale effectively. He reflects on transforming security operations through AI and intelligent automation and discusses how AI is reducing analyst investigation time dramatically. Ken also asserts the importance of auditing security controls before they silently fail. The conversation touches on the evolving role of the MITRE framework, the concept of signaling versus alerting, and why embracing AI might be the best career move for security professionals navigating rapid technological change in cloud environments. Topics discussed: Building security operations programs around crown jewels and scaling outward to manage the most critical assets first. Managing over-permissions in cloud environments that have snowballed across multiple administrators without proper governance. Using AI to reduce analyst investigation time from 30 minutes to seconds through intelligent data enrichment and context. Creating true single-pane-of-glass visibility by connecting security tools and data sources for more effective threat detection. Training new security analysts with AI assistance to bridge knowledge gaps in SQL, SOAR platforms, and log analysis. Documenting institutional knowledge while encouraging analysts to trust their intuition when something doesn't look right. Understanding the limitations of impossible travel alerts and using AI to establish user behavior baselines for accurate detection. Applying the MITRE framework as a guideline rather than gospel, adapting detection strategies to specific organizational needs. Implementing signaling approaches that label security-relevant events without creating alert fatigue for security operations teams. Auditing security controls regularly to catch configuration drift and ensure protective measures remain effective over time.  Listen to more episodes:  Apple  Spotify  YouTube Website

This is episode 310 recorded on November 21st, 2025, where John & Jason talk about the Power BI & Fabric Feature Summaries from October 2025 in preparation for the big news releases from Ignite in November.

“Journalist Lee Sanders is back on this special 14th Anniversary edition of THE RCWR SHOW as he celebrates 14 years of the podcast — laughs, fun stories, and deep dives included!Tonight's SMACKDOWN 11/21/25 card discussed:-First-Round Match – First half of the “Last Time Is Now” tournament: Penta vs. Finn Bálor-First-Round Match – Other half: Bronson Reed vs. Carmelo Hayes. -Tag Team Match: Fraxiom (Nathan Frazer & Axiom) vs. #DIY (Tommaso Ciampa & Johnny Gargano). -Celebration Segment: Chelsea Green's Women's United States Championship celebration.Latest in headlines including:-Headlines: including former superstar AJ Lee speaking out against a creepy fan who used AI to simulate them kissing — a wild digital-era story.-AEW Full Gear 2025 preview-Fun stories from over the years along with laughs and nothing but good vibes!BROUGHT TO YOU IN PART BY IWantToLearnSQL.com — your hands-on gateway to mastering SQL. Whether you're starting from scratch or upgrading your data skills, IWantToLearnSQL.com puts structured lessons, real-world exercises, and clear explanations at your fingertips. From querying databases to building reports, they make learning SQL practical, approachable, and actually fun. If you're ready to level up your data game, visit IWantToLearnSQL.com and start getting confident with SQL today — your next pivot in tech begins with a solid query.BROUGHT TO YOU IN PART BY

Journalist Lee Sanders is back with his WWE RAW 11/17/25 full show review and results as John Cena appears at New York's Madison Square Garden one final time before retiring in December! The Last Time is Now Tournament continues!-John Cena makes his final appearance on RAW at Madison Square Garden — the end of an era. -Women's Intercontinental Championship: Becky Lynch (c) vs. Maxxine Dupri — Dupri looks to overcome Lynch for the title. -The tournament “Last Time is Now” continues: Gunther vs. Je'Von Evans and Solo Sikoa vs. a mystery opponent. -Plus: Nikki Bella addresses her shocking attack on Stephanie Vaquer in a segment to be featured tonight.

Nik and Michael discuss the various changes to EXPLAIN that arrived in Postgres 18. Here are some links to things they mentioned: EXPLAIN (official docs) https://www.postgresql.org/docs/current/sql-explain.htmlUsing EXPLAIN (official docs) https://www.postgresql.org/docs/current/using-explain.html EXPLAIN glossary (pgMustard site) https://www.pgmustard.com/docs/explainPostgres 18 release notes https://www.postgresql.org/docs/release/18.0/Enable BUFFERS with EXPLAIN ANALYZE by default (commit) https://git.postgresql.org/gitweb/?p=postgresql.git;a=commit;h=c2a4078ebOur (first) BUFFERS by default episode https://postgres.fm/episodes/buffers-by-default Show index search count in EXPLAIN ANALYZE (commit) https://git.postgresql.org/gitweb/?p=postgresql.git;a=commitdiff;h=0fbceae841cb5a31b13d3f284ac8fdd19822ecebOur episode on Skip scan with Peter Geoghegan https://postgres.fm/episodes/skip-scanWhat do the new Index Searches lines in EXPLAIN mean? https://www.pgmustard.com/blog/what-do-index-searches-in-explain-meanpg_stat_plans presentation by Lukas Fittl https://www.youtube.com/watch?v=26coQV3f-wkImprove EXPLAIN's display of window functions (commit) https://git.postgresql.org/gitweb/?p=postgresql.git;a=commit;h=8b1b34254Show Parallel Bitmap Heap Scan worker stats in EXPLAIN ANALYZE (commit) https://git.postgresql.org/gitweb/?p=postgresql.git;a=commit;h=5a1e6df3bAdd information about WAL buffers being full (commit) https://git.postgresql.org/gitweb/?p=postgresql.git;a=commit;h=320545bfc ~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

Wendell joins the show with a literal fire background (the “this is fine” meme), which he admits he can’t use anymore because of company backgrounds. But it’s an accurate representation of daily developer life, and we can all relate. Teaching PHP Six Months After Learning It At 16 years old, working in a small-town Brazilian school teaching Word and Excel, Wendell took a PHP course. Five or six months later, the teacher left and they asked Wendell to take over—teaching PHP to 13 and 14-year-olds when he was barely older himself. Students would ask questions he didn’t know the answer to, forcing him to say “give me a minute” while frantically searching the documentation. But that pressure? It taught him the most valuable developer skill: knowing how to find answers to things you don’t know. No Computer at Home Here’s the kicker: Wendell didn’t even have a computer at home during all this. He could only use the computers at work, so he’d finish lunch in 15 minutes just to get back to his desk and keep learning PHP. The obsession was real, and it paid off. PHP Documentation: The Unsung Hero Everyone agrees—PHP’s documentation is insanely good. You can find almost anything without even hitting Stack Overflow. Comments from 15-20 years ago still work today because PHP maintains backwards compatibility like no other language. Those old comments aren’t just relics; they’re still valid, working code that new developers can learn from. Try that in JavaScript land. Rector: The Migration Miracle Moving legacy code to modern PHP used to be a nightmare. Now? Install Rector and watch it automatically migrate your codebase to use new features. Wendell highlights this as one of PHP’s secret weapons—the community builds tools that make everyone’s life easier. When AI Becomes Part of Your Workflow some literally can’t work without Claude, Cursor, and PHPStorm anymore. Not because he needs AI for everything, but because the anxiety of “what if I need to ask something?” kicks in if it’s not there. It’s wild how quickly we adapt to new tools—especially considering 25 years ago we barely had IDEs. We had Notepad. If we were lucky. The Imposter Syndrome Reality Check Everyone Googles stuff. Every. Single. Person. It doesn’t matter how experienced you are or how many packages you’ve written—at some point, you’re searching for answers. The skill isn’t memorizing everything; it’s knowing where to look and how to find the right answer. Mike and Chris both admit they struggle with imposter syndrome constantly. You’re not alone. PHP Can Do Everything Now CLI apps? Easy. Web apps? Obviously. Desktop applications? Yep. Mobile applications with PHP? Absolutely—and Wendell admits he never thought that would be possible. With AI advancements and tools like the new official MCP SDK for PHP, the possibilities keep expanding. JavaScript might get there first, but PHP always catches up. New Security Challenges: Prompt Injection Frameworks already protect us from SQL injection and script injection. But now with MCP (Model Context Protocol) and AI integration, we have a new threat: prompt injection. How will PHP frameworks adapt? How do we secure AI-powered applications? These are the new challenges keeping the community on its toes. Teaser: Laravel Service Container Deep Dive Wendell drops a teaser—he’s publishing his longest blog post yet about how Laravel’s service container works. By the time this episode goes live, it’ll probably already be out. Worth the read. Listen to hear why the PHP community attracts experts from other languages, and why everyone keeps confusing their show schedule with the video game Fortnite. Links From The Show: Wendell’s blog: https://wendelladriel.com/blog Inside The Service Container: https://wendelladriel.com/blog/inside-the-laravel-service-container Laravel Queues Under The Hood: https://wendelladriel.com/blog/laravel-queues-under-the-hood Laravel Actions As A Service: https://wendelladriel.com/blog/laravel-aaas-actions-as-a-service Best Practices For Laravel Applications: https://wendelladriel.com/best-practices-for-laravel-enterprise-applications PHP Architect Social Media: X: https://x.com/phparch Mastodon: https://phparch.social/@phparch Bluesky: https://bsky.app/profile/phparch.com Discord: https://discord.phparch.com Subscribe to our magazine: https://www.phparch.com/subscribe/ Streams: Youtube Channel Twitch Partner This podcast is made a little better thanks to our partners Displace Infrastructure Management, Simplified Automate Kubernetes deployments across any cloud provider or bare metal with a single command. Deploy, manage, and scale your infrastructure with ease. https://displace.tech/ PHPScore Put Your Technical Debt on Autopay with PHPScore Honeybadger.io Honeybadger helps you deploy with confidence and be your team's DevOps hero by combining error, uptime, and performance monitoring in one simple platform. Check it out at honeybadger.io Music Provided by Epidemic Sound https://www.epidemicsound.com/ The post PHP Alive And Kicking – Episode 16 – Wendell Adriel appeared first on PHP Architect.

Discover Firebase Data Connect with Tyler Crowe! Dive into SQL, GraphQL, AI, and live demos to supercharge your app's data. Share your thoughts below!https://codingcat.dev/podcast/firebase-sql-with-data-connect00:00 Data Connect Overview04:29 AI Features & Vertex13:13 SQL Views & Raw SQL15:45 Downloading SDKs24:37 Full Text Search30:32 Vector Search Explained38:20 GraphQL Insights47:43 Firestore vs Data Connect48:32 Conclusion

Jack Herrington talks with Will Madden about how Prisma ORM is evolving in v7, including the transition away from Rust toward TypeScript, less magic, and a new Prisma config file for more predictable good DX. They dig into Prisma Postgres, improvements to Prisma Studio, better support for serverless environments, and how JavaScript ORM tools like Prisma as an object relational mapper will fit into future agentic coding workflows powered by LLMs. Links LinkedIn: https://www.linkedin.com/in/willmadden Resources ORM: https://www.prisma.io/blog/orm-6-12-0-esm-compatible-generator-in-preview-and-new-options-for-prisma-config https://www.prisma.io/blog/why-prisma-orm-generates-code-into-node-modules-and-why-it-ll-change https://www.prisma.io/blog/from-rust-to-typescript-a-new-chapter-for-prisma-orm https://www.prisma.io/blog/try-the-new-rust-free-version-of-prisma-orm-early-access https://www.prisma.io/blog/rust-free-prisma-orm-is-ready-for-production Prisma Postgres: prisma.io/postgres We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Fill out our listener survey (https://t.co/oKVAEXipxu)! https://t.co/oKVAEXipxu Let us know by sending an email to our producer, Elizabeth, at elizabeth.becz@logrocket.com (mailto:elizabeth.becz@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Check out our newsletter (https://blog.logrocket.com/the-replay-newsletter/)! https://blog.logrocket.com/the-replay-newsletter/ Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understanding where your users are struggling by trying it for free at LogRocket.com. Try LogRocket for free today. (https://logrocket.com/signup/?pdr) Chapters

This episode is a re-air of one of our most popular conversations from this year, featuring insights worth revisiting. Thank you for being part of the Data Stack community. Stay up to date with the latest episodes at datastackshow.com. This week on The Data Stack Show, John chats with Paul Blankley, Founder and CTO of Zenlytic, live from Denver! Paul and John discuss the rapid evolution of AI in business intelligence, highlighting how AI is transforming data analysis and decision-making. Paul also explores the potential of AI as an "employee" that can handle complex analytical tasks, from unstructured data processing to proactive monitoring. Key insights include the increasing capabilities of AI in symbolic tasks like coding, the importance of providing business context to AI models, and the future of BI tools that can flexibly interact with both structured and unstructured data. Paul emphasizes that the next generation of AI tools will move beyond traditional dashboards, offering more intelligent, context-aware insights that can help businesses make more informed decisions. It's an exciting conversation you won't want to miss.Highlights from this week's conversation include:Welcoming Paul Back and Industry Changes (1:03)AI Model Progress and Superhuman Domains (2:01)AI as an Employee: Context and Capabilities (4:04)Model Selection and User Experience (7:37)AI as a McKinsey Consultant: Decision-Making (10:18)Structured vs. Unstructured Data Platforms (12:55)MCP Servers and the Future of BI Interfaces (16:00)Value of UI and Multimodal BI Experiences (18:38)Pitfalls of DIY Data Pipelines and Governance (22:14)Text-to-SQL, Semantic Layers, and Trust (28:10)Democratizing Semantic Models and Personalization (33:22)Inefficiency in Analytics and Analyst Workflows (35:07)Reasoning and Intelligence in Monitoring (37:20)Roadmap: Proactive AI by 2026 (39:53)Limitations of BI Incumbents, Future Outlooks and Parting Thoughts (41:15)The Data Stack Show is a weekly podcast powered by RudderStack, customer data infrastructure that enables you to deliver real-time customer event data everywhere it's needed to power smarter decisions and better customer experiences. Each week, we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us a textIn this episode of The AI Advantage, Matt Brown sits down with Michele (Majka) Salerno, Chief Growth Officer at Celerant Technology, to explore how AI is transforming real-world retail.Michele breaks down how Celerant is helping independent and mid-market retailers compete with big-box giants through practical AI tools that actually save time and drive sales. From an AI-powered “Talk to SQL” agent that lets retailers query their data in seconds, to predictive product recommendations, SEO-trained content suites, and automated review responses, Celerant is redefining what efficiency and personalization look like on the sales floor and online.They also discuss how Google's new AI-driven search is reshaping discoverability, why “context is the new content,” and what the rise of AI means for the future of retail jobs and marketing.Support the show

Lee & Tammy Sanders are back with another edition of WRESTLING with the TOPICS (November 16, 2025). This week the gang sounds off on:Weekend vibes so far as Lee does not miss working late nightsLee follows up on an interesting AI Deepfake story he's been working onThe process of working with a newspaper first impressionsGovernment Shutdown is over but at what costs?Trump Administration forcing folks to re-sign for SNAP benefitsTammy sounds off on Undertaker live podcast prices for D.C. showTammy gives her thoughts on the Tegan Nox / AEW walkout news going aroundSpeaking of women...what's up with the selfies in the bathrooms???What the Hell is going on with Wendy's Fast Food????BROUGHT TO YOU IN PART BY IWantToLearnSQL.com — your hands-on gateway to mastering SQL. Whether you're starting from scratch or upgrading your data skills, IWantToLearnSQL.com puts structured lessons, real-world exercises, and clear explanations at your fingertips. From querying databases to building reports, they make learning SQL practical, approachable, and actually fun. If you're ready to level up your data game, visit IWantToLearnSQL.com and start getting confident with SQL today — your next pivot in tech begins with a solid query.BROUGHT TO YOU IN PART BY

It's a loaded edition of The RCWR Show with Lee Sanders breaking down all the action from tonight's WWE SmackDown (11/14/25) — including the continuation of the John Cena “Last Time” Tour Tournament and the latest matches that push this storyline forward. We'll be talking results, surprises, standout performances, and all the fallout heading into Survivor Series Perth!Tonight's SmackDown coverage includes:✔️ Updates on the Cena “Last Time” Tournament✔️ Who advanced and who got eliminated✔️ Match-by-match breakdown✔️ Notable backstage segments & direction moving forwardPLUS a stacked lineup of wrestling headlines:✔️ Undertaker: One Deadman Show ticket info released for Washington, D.C.✔️ Nixon Newell (FKA Tegan Nox) responds to claims she refused an AEW finish✔️ Thoughts on WWE doing away with Vince McMahon's old PPV philosophy✔️ Is the “fewer PLEs” model actually better for WWE's product?✔️ Additional breaking news from WWE, AEW, and beyond✔️ Live fan reactions and Q&A throughout the streamWhether you're a WWE fan, AEW fan, or just love deep-dive wrestling analysis, this is where you want to be — honest takes, no fluff, all substance.PROGRAMMING NOTES: JOIN LEE LIVE ON YOUTUBE, FACEBOOK, TWITTER ON FRIDAY NOVEMBER 21ST 8PM ET AS HE CELEBRATES 14 YEARS OF THE RCWR SHOW!BROUGHT TO YOU IN PART BY TerraPaulPremium.com Wake up your senses with bold flavor and smooth vibes! Terra Paul Premium brings you top-tier coffee and teas crafted for people who love quality, energy, and good taste. From rich blends to chill herbal sips, they've got your daily fuel covered — check them out today!BROUGHT TO YOU IN PART BY IWantToLearnSQL.com — your hands-on gateway to mastering SQL. Whether you're starting from scratch or upgrading your data skills, IWantToLearnSQL.com puts structured lessons, real-world exercises, and clear explanations at your fingertips. From querying databases to building reports, they make learning SQL practical, approachable, and actually fun. If you're ready to level up your data game, visit IWantToLearnSQL.com and start getting confident with SQL today — your next pivot in tech begins with a solid query.BROUGHT TO YOU IN PART BY

In this Technology Reseller News, Podcast, Doug Green interviews Don Boxley, CEO and Co-Founder of DH2i, for a deep dive into one of the biggest challenges facing IT teams today: the migration gap between legacy Windows-based SQL Server deployments and the containerized, Linux-driven future that modern applications increasingly require. DH2i, a long-time Microsoft and Red Hat partner, delivers high availability, secure communication, and cross-platform mobility for SQL Server, Oracle, and MySQL environments. Their flagship platform, DX Enterprise, enables customers to run the same production-grade SQL instance across Windows, Linux, and Kubernetes — and move between them with seamless failover. As Boxley explains, this eliminates the traditional roadblocks that keep enterprises locked into aging infrastructure. With SQL Server 2025 bringing new support for AI-driven applications, Microsoft tapped DH2i to deliver mission-critical HA capabilities for these next-generation workloads. The company also introduced a hands-on, step-by-step Minikube tutorial, allowing DBAs and MSPs to experiment safely with Kubernetes-based SQL deployments on their own PCs before ever touching production. “Most teams think they're stuck on Windows — they're not. With DX Enterprise, you can move SQL Server to Linux or containers without disruption, and your customers won't even know the difference,” Boxley notes. DH2i's developer edition is available as a free download, complete with 30-day support, giving IT teams a no-risk path to testing, learning, and modernizing their database infrastructure. Learn more at https://dh2i.com/. Software Mind Telco Days 2025: On-demand online conference Engaging Customers, Harnessing Data

Nik talks Michael through a recent benchmark he worked with Maxim Boguk on, to see how quickly they could provision a replica. Here are some links to things they mentioned:Ultra-fast replica creation with pgBackRest (blog post by Maxim Boguk and Nik) https://postgres.ai/blog/20251105-postgres-marathon-2-012-ultra-fast-replica-creation-pgbackrestCopying a database episode https://postgres.fm/episodes/copying-a-databaseAdd snapshot backup support for PostgreSQL in wal-g (draft PR by Andrey Borodin) https://github.com/wal-g/wal-g/pull/2101Multi-threaded pg_basebackup discussion 1: https://www.postgresql.org/message-id/flat/CAEHH7R4%3D_GN%2BLSsj0YZOXZ13yc%3DGk9umJOLNopjS%3DimK0c1mWA%40mail.gmail.comMulti-threaded pg_basebackup discussion 2: https://www.postgresql.org/message-id/flat/io_method https://www.postgresql.org/docs/current/runtime-config-resource.html#GUC-IO-METHOD pgBackRest https://github.com/pgbackrest/pgbackrestAdd sequence synchronization for logical replication (commit) https://git.postgresql.org/gitweb/?p=postgresql.git;a=commit;h=5509055d6956745532e65ab218e15b99d87d66ce Allow process priority to be set (pgBackRest feature added by David Steele) https://github.com/pgbackrest/pgbackrest/pull/2693 Hard limit on process-max (pgBackRest issue from 2019) https://github.com/pgbackrest/pgbackrest/issues/696 ~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

In this episode of Crazy Wisdom, host Stewart Alsop talks with Jessica Talisman, founder of Contextually and creator of the Ontology Pipeline, about the deep connections between knowledge management, library science, and the emerging world of AI systems. Together they explore how controlled vocabularies, ontologies, and metadata shape meaning for both humans and machines, why librarianship has lessons for modern tech, and how cultural context influences what we call “knowledge.” Jessica also discusses the rise of AI librarians, the problem of “AI slop,” and the need for collaborative, human-centered knowledge ecosystems. You can learn more about her work at Ontology Pipeline and find her writing and talks on LinkedIn.Check out this GPT we trained on the conversationTimestamps00:00 Stewart Alsop welcomes Jessica Talisman to discuss Contextually, ontologies, and how controlled vocabularies ground scalable systems.05:00 They compare philosophy's ontology with information science, linking meaning, categorization, and sense-making for humans and machines.10:00 Jessica explains why SQL and Postgres can't capture knowledge complexity and how neuro-symbolic systems add context and interoperability.15:00 The talk turns to library science's split from big data in the 1990s, metadata schemas, and the FAIR principles of findability and reuse.20:00 They discuss neutrality, bias in corporate vocabularies, and why “touching grass” matters for reconciling internal and external meanings.25:00 Conversation shifts to interpretability, cultural context, and how Western categorical thinking differs from China's contextual knowledge.30:00 Jessica introduces process knowledge, documentation habits, and the danger of outsourcing how-to understanding.35:00 They explore knowledge as habit, the tension between break-things culture and library design thinking, and early AI experiments.40:00 Libraries' strategic use of AI, metadata precision, and the emerging role of AI librarians take focus.45:00 Stewart connects data labeling, Surge AI, and the economics of good data with Jessica's call for better knowledge architectures.50:00 They unpack content lifecycle, provenance, and user context as the backbone of knowledge ecosystems.55:00 The talk closes on automation limits, human-in-the-loop design, and Jessica's vision for collaborative consulting through Contextually.Key InsightsOntology is about meaning, not just data structure. Jessica Talisman reframes ontology from a philosophical abstraction into a practical tool for knowledge management—defining how things relate and what they mean within systems. She explains that without clear categories and shared definitions, organizations can't scale or communicate effectively, either with people or with machines.Controlled vocabularies are the foundation of AI literacy. Jessica emphasizes that building a controlled vocabulary is the simplest and most powerful way to disambiguate meaning for AI. Machines, like people, need context to interpret language, and consistent terminology prevents the “hallucinations” that occur when systems lack semantic grounding.Library science predicted today's knowledge crisis. Stewart and Jessica trace how, in the 1990s, tech went down the path of “big data” while librarians quietly built systems of metadata, ontologies, and standards like schema.org. Today's AI challenges—interoperability, reliability, and information overload—mirror problems library science has been solving for decades.Knowledge is culturally shaped. Drawing from Patrick Lambe's work, Jessica notes that Western knowledge systems are category-driven, while Chinese systems emphasize context. This cultural distinction explains why global AI models often miss nuance or moral voice when trained on limited datasets.Process knowledge is disappearing. The West has outsourced its “how-to” knowledge—what Jessica calls process knowledge—to other countries. Without documentation habits, we risk losing the embodied know-how that underpins manufacturing, engineering, and even creative work.Automation cannot replace critical thinking. Jessica warns against treating AI as “room service.” Automation can support, but not substitute, human judgment. Her own experience with a contract error generated by an AI tool underscores the importance of review, reflection, and accountability in human–machine collaboration.Collaborative consulting builds knowledge resilience. Through her consultancy, Contextually, Jessica advocates for “teaching through doing”—helping teams build their own ontologies and vocabularies rather than outsourcing them. Sustainable knowledge systems, she argues, depend on shared understanding, not just good technology.