Podcasts about Tooling

Amit Chita is the Field CTO at Mend.io. In this episode, he joins host Paul John Spaulding to discuss the future of AI appsec tooling, including how AI should be used as a force multiplier, not a replacement, new risks, and more. Securing The Build is brought to you by Mend.io, the leading application security solution, helping organizations reduce application risk efficiently. To learn more about our sponsor, visit https://mend.io.

Today I'm joined by Stephanie Blair, Founder of Know & Flourish (https://knowandflourish.com/), for a practical conversation on digital career growth in Customer Success. We dig into how to build a career identity (not just a title), why experimentation matters, and how to expand your lane without burning out. You'll hear a real-world example from my team of turning a scrappy spreadsheet into a lightweight web tool, and what that kind of initiative can do for your brand inside the business.We also talk about the shift in CS org design: the rise of digital program managers, AI-assisted workflows, and yes - why human, IRL moments still win renewals. If you're exploring a pivot into CS (from sales/marketing/product) or within CS (service → expansion, or IC → leader), Stephanie breaks down how to translate your skills, control your narrative, and interview like a peer.Housekeeping: I'll be co-chairing the CS Summit in Austin later this month, and the Digital CX Masterclass is coming soon join the waitlist at https://DigitalCustomerSuccess.com/Masterclass to be first in line. Support the show+++++++++++++++++Like/Subscribe/Review:If you are getting value from the show, please follow/subscribe so that you don't miss an episode and consider leaving us a review. Website:For more information about the show or to get in touch, visit DigitalCustomerSuccess.com. Buy Alex a Cup of Coffee:This show runs exclusively on caffeine - and lots of it. If you like what we're, consider supporting our habit by buying us a cup of coffee: https://bmc.link/dcspThank you for all of your support!The Digital Customer Success Podcast is hosted by Alex Turkovic

Bitcoin Core doesn't stand still even if consensus rules don't change. In this episode, Stéphan (Core Developer at Brink) explains how the Kernel and multiprocess projects are reshaping Bitcoin Core for long-term reliability. From modular validation logic to safer development workflows, this conversation shows why maintenance work matters. Hosted by Shinobi of Bitcoin Magazine.#BitcoinCore #BitcoinDevelopment #BitcoinKernel ⭐️⚔: SIGN UP WITH DUELBITS TODAY FOR A CHANCE TO WIN UP TO 2 BTC:

AI agents aren't “coming” to Ethereum—they're already here, spinning up on dedicated machines, clicking through wallets, deploying contracts, and even building apps for themselves. In this episode, Ryan and David sit down with Davide Crapis and Austin Griffith to map the emerging agent stack: ERC-8004 as a decentralized identity + reputation layer, x402 as payment rails for agent-to-agent commerce, and the real-world “Clawdbot” experiments that show what happens when an agent gets a wallet, a codebase, and a mandate. Along the way: prompt-injection risks, why agents read calldata like it's their native language, and why it may be the best time in history to be a solo builder—even as it gets harder to be a junior dev. ---

Performance creative consultant Dara Denney joins the show to break down how modern brands are approaching creative strategy in 2026. The conversation opens with the shifting role of content creators versus strategists, and why creative velocity, operations, and in-house production are increasingly shaping how brands scale.From there, they dig into how AI is actually being used inside creative workflows - where it speeds up research and briefing, and where human judgment still matters, especially around roadmapping and idea selection. The group also explores the growing convergence of organic and paid, including how organic performance signals influence paid creative, why upper-funnel content belongs in performance accounts, and when “organic-first” ideas can still drive results.The episode wraps with a candid discussion on performance measurement beyond short-term ROAS, touching on creative diversity, upper-funnel impact, and how operators think about long-term growth when building scalable content systems.If you have a question for the MOperators Hotline, click the link to be in with a chance of it being discussed on the show: https://forms.gle/1W7nKoNK5Zakm1Xv6Powered by:Motion.⁠⁠⁠https://motionapp.com/?utm_campaign=marketing-operators&utm_medium=sponsor&utm_content=motion-sign-up&utm_source=marketing-operators-podcastMotion Creative Strategy Bootcamp.https://motionapp.com/2026-creative-strategy-bootcamp-paid?utm_campaign=marketing-operators&utm_medium=sponsor&utm_content=creative-strategy-bootcamp-2026&utm_source=marketing-operators-podcastPrescient AI.https://www.prescientai.com/operatorsRichpanel.https://www.richpanel.com/?utm_source=MO&utm_medium=podcast&utm_campaign=ytdescAftersellhttps://www.aftersell.com/operatorsHaushttps://haus.io/operatorsGet the 9 Operators Newsletterhttps://9operators.com/

A working prototype does not mean your product is ready for mass production. In this episode, our host Adrian and Paul Adams, Sofeast's head of NPD, explore a real-world case where ignored DFM feedback led to predictable, preventable, and extremely costly manufacturing issues. From tooling limitations to material behavior and assembly inconsistency, this conversation explains why DFM exists, and why skipping it can cost hundreds of thousands (or even millions) later.   Episode Sections: 01:17 – Why DFM feedback gets ignored (and why it's dangerous) 01:58 – Real case: prototype worked, DFM warnings dismissed 03:19 – What prototypes are actually meant to validate 04:56 – Why prototype tolerances don't match production reality 05:00 – Material differences: same polymer, different behavior 06:08 – Tooling realities: demolding, deformation, surface damage 07:02 – How cosmetic defects become functional failures 07:32 – Assembly inconsistency, labor costs, scrap, and rework 08:21 – Transport and environmental failures after launch 09:07 – The true cost of returns, warranty, and brand damage 09:53 – The cost multiplier: pre-tooling vs post-tooling fixes 10:34 – How rushing actually delays your launch 11:50 – Investor pressure and the hidden risk it creates 13:36 – Best practices: how DFM should really be used 14:48 – Why early CM involvement matters 16:41 – The role of NPI checklists and structured processes 18:06 – Final warning: don't ignore expert manufacturing feedback   Related content… Sofeast conducts your DFM review for Manufacturing in Asia The New Product Introduction Process Guide Handover to Manufacturing: What NOT to do & Best Practices Get in touch with us Connect with us on LinkedIn Contact us via Sofeast's contact page Subscribe to our YouTube channel Prefer Facebook? Check us out on FB

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Crypto didn't remove trust — it refactored it.Which means the real question isn't whether blockchains work… it's whether the people who build them bear any responsibility for what happens next.In this episode we extend the previous conversation on crypto literacy, privacy UX, and incentive design to tackle a hard question with no clean answers:Do builders have responsibility beyond tooling?We explore the “blacksmith problem,” the myth of neutral systems, and how zero-knowledge, chain analysis, and UX choices shape outcomes — intentionally or not. This is not a price talk episode. It's about the ethics, incentives, and trade-offs embedded in decentralized infrastructure.Topics Covered • Crypto literacy and centralization of expertise • Privacy vs usability (and why it's not zero-sum) • Trust: from institutions → networks → intermediaries • The “neutral tools” dilemma in Web3 • When incentives create harm (and who owns it) • ZK systems, mixers, forensics, and emergent behavior • Builders vs system designers vs policymakersKey QuestionWhere does technical responsibility end, and ethical responsibility begin?If you're new hereThis episode continues directly from last week's cliffhanger. Go watch that one first if you want the full arc.Join the CommunityJoin the Discord for builders, OGs, privacy folks, ZK learners, and lurkers:(QR code in the video)Support the ShowLike, comment, subscribe, and clip moments that hit you. We actually watch them.For CommentersAnswer this in one word:Do builders have responsibility beyond tooling? — YES or NO?

Alex Merced talks about how his optimism about the Agentic AI tool and poses the question, if people can run as fast as they could before AI, instead of resenting them for it, ask yourself how much further you can now run with AI. Follow Alex on Social: AlexMerced.com The Data Lakehouse Community: https://www.datalakehousehub.com

In hour 3 of Steiny and Guru, the guys get further into the Warriors outlook and if trading Kuminga will bring them the right piece to help them reach a playoff berth. Plus, if they do re-tool will it be enough?

Marketing Update by KentonChad B. breaks down his new AI tooling agents that will help ship code and identify problems. A New Node Operator, DeFIRE, joins the space and talks about why he became a new Node Operator!

The ForgeCast is back! Sam is back in the host seat after nearly a year away from the internet, and he brought on a guest to help discuss why and how it all happened, as well as explore the nature of mental health and the effects smithing has on it. Carolyn Farris of Evergreen Forgeworks has dedicated her platform to journaling her experience as a smith, and also her struggles with anxiety, depression, and PTSD.

Edge AI is evolving quickly - what's changing in the tooling and frameworks that support it? And where do the biggest opportunities for improvement lie? In this episode of Edge of Tomorrow – The Edge AI Debate, host Pete Bernard (CEO, EDGE AI FOUNDATION) is joined by Elia Schoenberger (Product Marketing, AI Division at Civa) and Nathan Francis (Business Development at AIZip) for an in-depth discussion on the role of tooling and frameworks in shaping the future of Edge AI. While much of the attention in AI is placed on models and hardware, this conversation focuses on the layers in between — compilers, SDKs, deployment pipelines, and frameworks — and how they influence speed, scalability, and collaboration across the ecosystem. The discussion explores how hardware constraints, model design, and tooling choices intersect, whether the industry is moving toward standardisation or continuing to prioritise innovation, and what practical steps could help simplify Edge AI development without slowing progress. This episode offers a look at how the Edge AI stack is evolving - and what it will take to support broader, more efficient deployment in the years ahead. Chapters… 00:00 Introductions 01:40 Why tooling and frameworks matter in Edge AI 03:25 Hardware constraints, models, and deployment realities 05:23 Fragmentation vs fit-for-purpose tooling 07:59 Power, performance, and memory trade-offs 09:18 Where Edge AI sits on the maturity curve 11:32 Standardisation, innovation, and ecosystem balance 13:32 Compilers, MLIR, and unifying the toolchain 16:02 Deployment challenges and quantisation complexity 25:17 Generative models arriving at the edge 31:36 Local-first intelligence and when the cloud still matters 32:52 What would help accelerate Edge AI development 36:13 Final reflections and closing thoughts The episode is live on all major listening platforms now: https://linktr.ee/theiotpodcast Connect with our guests… Elia Schoenberger (CIVA,Inc): https://www.linkedin.com/in/eliashenberger/ Nathan Francis (AIZip): https://www.linkedin.com/in/nathanfrancis99/ About Edge of Tomorrow – The Edge AI Debate Edge of Tomorrow is our debate-led spin-off series bringing together leaders from across the Edge AI ecosystem to explore the technical, commercial, and strategic decisions shaping how intelligence moves closer to the real world. SUBSCRIBE TO THE IOT PODCAST ON YOUR FAVOURITE LISTENING PLATFORM: https://linktr.ee/theiotpodcast Sign up for exclusive email updates: https://theiotpodcast.com/get-exclusive-access/ Contact us to become a guest or partner: https://theiotpodcast.com/contact/

All but the last 20 minutes of this episode should be comprehensible to non-physicists.Steve explains where frontier AI models are in understanding frontier theoretical physics. The best analogy is to a “brilliant but unreliable genius colleague”!He describes a specific example: the use of AI in recent research in quantum field theory (Tomonaga-Schwinger integrability conditions applied to state-dependent modifications of quantum mechanics), work now accepted for publication in Physics Letters B after peer review. Remarkably, the main idea in the paper originated de novo from GPT-5.Links:X discussion - https://x.com/hsu_steve/status/1996034522308026435Companion paper: Theoretical Physics With Generative AI -  https://drive.google.com/file/d/16sxJuwsHoi-fvTFbri9Bu8B9bqA6lr1H/viewPhysics paper - https://arxiv.org/abs/2511.15935 | https://www.sciencedirect.com/science/article/pii/S0370269325008111Related discussion of AI and theoretical physics with Prof. Nirmalya Kajuri (IIT) and Prof. Jonathan Oppenheim (UCL) - https://youtu.be/BRuDd3l0e3kRelated video: AIs Win Math Olympiad Gold: Prof. Lin Yang (UCLA) – Manifold #97 - https://youtu.be/8JeRCqNg7RcChapter markers:(00:00) - Intro: AI discussion with specialized physics at the end (03:40) - The current AI landscape for science: frontier models, Co-Scientist, and recent math breakthroughs (11:01) - Why models help and why they fail: errors, deep confabulation, and the research risk (15:54) - The Generator–Verifier workflow: how chaining model inference suppresses mistakes (23:30) - Project origin: testing models on Hsu's older nonlinear QM/QFT work (30:35) - The “GPT-5 moment”: Tomonaga–Schwinger angle appears and produces the key equation (40:35) - Wild goose chases & a practical heuristic: axiomatic QFT detour; Generator-Verifier convergence (51:44) - Referee-driven test case: Kaplan–Rajendran model, past-lightcone geometry, and verification (55:55) - Tooling & outlook: automation prototype, chaining into “supermodels,” where this is headed (59:39) - Physics slides (advanced): TS integrability, microcausality, and why nonlinearity threatens locality –Steve Hsu is Professor of Theoretical Physics and of Computational Mathematics, Science, and Engineering at Michigan State University. Previously, he was Senior Vice President for Research and Innovation at MSU and Director of the Institute of Theoretical Science at the University of Oregon. Hsu is a startup founder (SuperFocus.ai, SafeWeb, Genomic Prediction, Othram) and advisor to venture capital and other investment firms. He was educated at Caltech and Berkeley, was a Harvard Junior Fellow, and has held faculty positions at Yale, the University of Oregon, and MSU. Please send any questions or suggestions to manifold1podcast@gmail.com or Steve on X @hsu_steve.

Why do so many AI rollouts stall right after the tools ship?In this episode of Alexa's Input (AI), Alexa talks with Melissa Reeve, author of the book Hyper Adaptive: Rewiring the Enterprise to Become AI Native, about what it actually takes to get AI adopted in large organizations.Melissa shares how her background in lean, Agile, and DevOps transformation shaped her view that AI adoption is less about “buying the tool” and more about rewiring how work happens. Together, they break down why many AI initiatives fail (and why ROI is slow), the FOCUS framework, the “AI time paradox,” and how support structures like AI activation hubs, social learning, and better success metrics can raise quality and accelerate impact.A must-listen for engineering leaders, product teams, and executives trying to move beyond pilots and turn AI into real operational leverage.Learn more about Melissa and Hyper Adaptive below.LinksWatch: ⁠⁠⁠https://www.youtube.com/@alexa_griffith⁠⁠⁠Read: ⁠⁠⁠⁠⁠https://alexasinput.substack.com/⁠⁠⁠⁠⁠Listen:⁠ https://creators.spotify.com/pod/profile/alexagriffith/⁠More: ⁠⁠⁠https://linktr.ee/alexagriffith⁠⁠⁠Website: ⁠⁠⁠https://alexagriffith.com/⁠⁠⁠LinkedIn: ⁠⁠⁠https://www.linkedin.com/in/alexa-griffith/⁠⁠⁠Find out more about the guest at:LinkedIn: https://www.linkedin.com/in/melissamreeve/Book: https://itrevolution.com/product/hyperadaptive/KeywordsAI adoption, enterprise transformation, Hyper Adaptive model, organizational change, DevOps, Lean, Agile, AI integration, customer-centricity, innovation accounting, social learningChapters00:00 Introduction to AI Adoption in Enterprises03:00 Melissa's Journey and the Foundation of AI Thinking06:06 The Analogy of DevOps and AI Implementation08:47 Cultural Shifts vs. Tooling in AI Adoption11:49 The Hyper Adaptive Model for AI Integration14:48 Sociology of Workflows and Organizational Change17:49 Understanding AI Initiative Failures21:00 Customer Centricity in AI Solutions23:58 The AI Time Paradox and Learning26:58 AI Activation Hubs and Their Role30:54 The Role of Human Oversight in AI Automation34:03 Incentivizing AI Engagement in Organizations35:59 Social Learning and AI: The Power of Collaboration40:57 Practical Applications of AI in Daily Life44:44 Quality vs. Productivity: The AI Dilemma46:13 The Focus Framework: Prioritizing AI Use Cases48:23 Influencing AI Adoption in Organizations51:07 The Future of Hyper Adaptive Organizations55:08 Decision-Making in the Age of AI57:37 Key Takeaways for Leaders in the AI Revolution

Hyperion Materials & Technologies reveals its latest innovation — the DZ23 carbide grade — a major leap forward for canmaking efficiency, tooling durability, and high-speed line performance.In this episode of The Metal Pack Pod, host Alex Fordham sits down with Lluís Miñarro, the Global Segment Director for Can Tooling Products and Services at Hyperion Materials & Technologies, to explore how advanced carbide grades, global supply chain strategies, and customer-driven engineering are shaping the future of metal packaging.Lluís breaks down:Why lighter carbide grades improve punch dynamicsHow tooling innovation reduces spoilage, energy use, and maintenanceThe real impact of APT / tungsten supply constraints on cost and productionHyperion's expanded global footprint — including new US manufacturing facilitiesWhat canmakers can expect from the next wave of tooling R&DIf you're in canmaking, tooling, operations, sustainability, or metal forming, this episode delivers real-world insight from one of the industry's leading experts.00:00 Intro & episode overview01:20 Industry trends: sustainability, demand rebound & regional shifts03:50 Hyperion's role in global can tooling06:00 Luis Minero's background & passion for metallurgy08:00 Why tooling innovations matter more than ever11:00 Introducing the DZ23 carbide grade13:45 Performance benefits: wear resistance, weight reduction & line efficiency17:20 Understanding APT and tungsten supply chain challenges19:55 How raw material pricing affects tooling costs20:20 Hyperion's new US production capabilities22:00 What's next for Hyperion and can tooling innovation

Some conversations feel scripted. This one… absolutely did not. Larry Robbins walked in ready to talk life, passion, family, culture, workholding, philosophy, and whatever else popped into his head — and somehow it all connected back to manufacturing. This episode of MakingChips is one of the most unhinged, hilarious, honest, and wisdom-packed conversations we've ever recorded. Larry has been in the industry for nearly 46 years, and he's collected enough stories, scars, and laughs for ten careers. From his father dragging him into the business ("long hair doesn't work here") to his famous explanation that SMW makes "magic hands," Larry blends humor and experience into lessons every shop owner needs to hear. His passion for the industry is unmatched — and his candor is even better. Throughout the episode, the crew dives into culture, leadership, lying (don't), modularity, flexibility, high-density workholding, predictable setups, financing equipment, and why you should stop crawling across a dollar to pick up a dime. Larry opens up about the future of manufacturing, warns against bad advice, and reminds everyone that machining touches every single thing in the world. If you're ready for an episode that's equal parts educational and unhinged in the best possible way, buckle up — Larry Robbins is in rare form. Segments (1:00) Larry's background, early failures, and the stories that shaped his approach to leadership (3:31) An investment in ProShop is an investment in your business (3:32) Culture, loving your work, and leadership lessons (5:07) Entering the family business, retirement humor, and long-term commitment (7:23) The reality of workplace culture, honesty, and handling difficult employees (10:02) Integrity, truth-telling, and early lessons on character (13:18) Appreciating machinists and the unseen parts of manufacturing (15:05) Workholding vs. cutting tools and why workholding matters more than people think (16:09) "Magic hands" — Larry's explanation of workholding for a 5-year-old (17:20) Workholding misconceptions and the cost of poor setups (19:00) Vendor trust, trying equipment, and choosing partnerships wisely (20:22) Setup reduction, rigidity vs. flexibility, and predictable processes (22:12) Cutting 12-hour setups and the value of internal vs. external setups (24:16) Why we love Phoenix Heat Treating for Outside Processing (25:24) Expensive machines + cheap vices = lost potential (27:26) Modular workholding, infinite adjustment, and the origins of the industry (29:18) When not to sell a customer — long-term trust over short-term gain (30:19) Why shops "don't know what they don't know" about proper workholding (31:58) Financing workholding and proving ROI to shop owners (33:09) Tooling certs and buying the solution, not just the machine (35:24) High-density workholding and maximizing machine real estate (37:12) Protecting customers from bad investments and the role of good vendors (38:01) The LEGO analogy and building reusable workholding systems (40:13) Trusting experts and using the right resources in decision-making (41:19) Grow your top and bottom line with CliftonLarsonAllen (CLA) (41:57) Buzzwords like Industry 4.0 vs. solving real problems (43:49) Competing with global labor costs and running unattended (44:19) Extending the life of old machines with better processes (46:41) Universal truth: If you're not making chips, you're not making money  Resources mentioned on this episode Connect with Larry Robbins and SMW Autoblok An investment in ProShop is an investment in your business Why we love Phoenix Heat Treating for Outside Processing Grow your top and bottom line with CliftonLarsonAllen (CLA) Smart Money Moves: Equipment Financing Tips with Ty Willis Connect With MakingChips www.MakingChips.com On Facebook On LinkedIn On Instagram On Twitter On YouTube

Adrian is joined by Sofeast Group Head of New Product Development, Paul Adams, to unpack the brutal truth behind the question: “Can you actually afford to manufacture your new product idea?” They bust some of the most dangerous myths (like “MOQ × unit price is my total cost” and “we'll fix reliability later”), then walk through Sofeast/Agilian's 6-phase NPI process for electromechanical products and show how your budget is really consumed; from feasibility and prototyping through to tooling, pilot runs, and mass production. If you're planning to launch a new product, this episode is your reality check and roadmap.   Episode Sections: 00:00 – Intro & who this episode is for  07:02 – Mythbusting: YouTube & “$10k product launch” myths  12:13 – The Sofeast/Agilian 6-phase NPI process  21:18 – How your budget is split across the phases  29:00 – What to expect in each phase & readiness checks  37:31 – Tooling, NRE, and why half a tooling budget is worse than none  43:42 – Budgeting properly and adding contingency  45:21 – Call to action & how Sofeast/Agilian can help   Related content... How to Calculate the Cash Needed to Prototype & Launch your New Product Why does new product development take so long? What is an NRE Cost (Non-Recurring Engineering)? 10 Factors Affecting Electronic Product Design Costs Costs and Milestones to go from Product Concept to Market? The New Product Development Process in Electronics New Product Development In China: 4 Tips To Go Faster Get in touch with us Connect with us on LinkedIn Contact us via Sofeast's contact page Subscribe to our YouTube channel Prefer Facebook? Check us out on FB

What drives execution velocity—better tools or better clarity? Loïc Houssier, CTO of Superhuman Mail (post-Grammarly acquisition), argues that most velocity problems stem from unclear team missions, not inadequate tooling. From steering DocuSign's French acquisition through complex carve-out negotiations to building Superhuman's offline-first architecture with a 100-millisecond interaction rule, Loïc shares hard-won lessons about engineering metrics that actually matter (PR per engineer per week trends over absolutes), when to resist microservices (until it's genuinely painful), and why promotion frameworks determine product quality. Technical leaders will learn how vertical team alignment eliminates dependencies, why guild structures maintain consistency without blocking speed, and how European safety nets create under-appreciated opportunities for technical risk-taking.

Jacob Effron of Redpoint joins Nick to discuss How Model Progress Shifts the Goalposts, Why The Death of Software Is Overstated, and How to Diligence Hypergrowth Without Getting Burned. In this episode we cover: Investing in AI and Vertical Applications Model Layer Advancements and Future Milestones Challenges and Opportunities in Agentic AI Investing in Tooling and Middleware Product Market Fit and Defensibility in AI Applications Verticals with Real Product Market Fit The Evolution of AI Investing Metrics Future Trends in AI and Robotics Guest Links: Jacob's LinkedIn Jacob's X Redpoint's LinkedIn Redpoint's Website The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

Im Binärgewitter-Talk #370 stolpern wir gemeinsam durch die glitzernde Tech-Welt – von Linux-Liebeserklärungen bis Mac-Mimimi. Unser Gast erklärt uns, warum Stromnetze spannender sind als jede Netflix-Serie, während Cloud-Dienste reihenweise „Tote der Woche“ melden. Zwischendurch philosophieren wir über Kubernetes, KI-Hacking und ob Gateway-API wirklich das neue heiße Ding ist. Zum Schluss gibt's Zukunftsvisionen zu E-Mobilität, Smart Homes und Mini-Windrädern – Tech-Chaos zum Mitlachen garantiert! Toter der Woche graveyard has a new logo Neato Cloud Services MinIO Ingress NGINX Retirement Externe Facebook “like” und “comment” buttons Exotische Debian Ports Plain HTTP in Chrome Lennarts Blog Untoter der Woche Linux-Konsole: Valve kündigt neue Steam Machine an Steam Hardware Announcement AI der Woche AI Darwin Awards Securevibes Volkwagen for Unit Tests Where’s the Shovelware? Why AI Coding Claims Don’t Add Up Anthropic: AI Espionage Researchers Question claim AI slop attacks on the curl project (video) Blog Post von Daniel Stenberg AI Song an der Spitze der Charts (in den USA) Human Music (video) Cometjacking attack Unseeable prompt injections in Comet and other AI browsers AI World Clocks News Fedora Linux 43 Meta wants to read your DMs Operaton has reached 1.0 — Camunda 7.0 CE repo has been archived FreeBSD shortly before 15.0: Trust is good, reproducibility is better FreeBSD now builds reproducibly and without root privilege PS5 Funktionierender User + Kernel Exploit Affinity's new design platform combines everything into one app Ausbruch aus Dockercontainer Themen eAuto laden und Energienetze (follow up zur FrosCon Folge) Wikipedia: Grobe Struktur eines Stromnetzes Frische News Schuko für PV Maus: Pumpspeicherwerk DLF Forschung Aktuell — Podcast: Wasserstofferzeugung Wikipedia: Hochspannungs-Gleichstrom-Übertragung Wikipedia: Karte Offshore-Windparks in der Deutschen Bucht Wikipedia: Kleinwindkraftanlage 3D-Druck der Woche I Broke the Sound Barrier with a 3D Printed Rocket! (video) C-Hook Battery Cover Mimimi der Woche Anycubic Slicer Next für Linux nur mit “execute Shellscript from internet” welches CN schriftzeichen als Meldungen ausgibt die Installationsziele auf Ubuntu Only einschränkt im Endeffekt doch nur eine Paket-Source einträgt und via apt ein Paket installiert NixOS static ip let ext-if = "et0"; external-mac = "00:11:22:33:44:55"; external-ip6 = "2a01::2342"; external-netmask6 = "64"; in { services.udev.extraRules = '' SUBSYSTEM=="net", ATTR{address}=="${external-mac}", NAME="${ext-if}" ''; networking = { enableIPv6 = true; nat.enableIPv6 = true; interfaces."${ext-if}" = { useDHCP = true; ipv6.addresses = [{ address = external-ip6; prefixLength = external-netmask6; }]; }; defaultGateway6 = { address = external-gw6; interface = ext-if; }; nameservers = [ "1.1.1.1" ]; }; } Ab-er Finger macht kein Touch Lesefoo OpenSource Alternativen zu Cloudflare Picks thingino Severance S02 Kittysplit seized.fyi Tooling https://volta.sh/ https://github.com/Schniz/fnm https://mise.jdx.dev/ Fwupd 2.0.16 Released Mit OSS Termine buchen beim Arzt Bahnstationen in 3D-Karte

Adrian and Paul break down why molding costs “balloon” (over-tight tolerances and cosmetic overkill) and then walk through three practical levers to cut costs safely: smarter tooling design & DFM (wall thickness, draft, gates, material choice), good tooling decisions (steel grades like P20 vs H13, cavity count, hot vs cold runners), and production/process tweaks (machine tonnage matching, sensible regrind use, SPC/sensors, in-tool de-gating). They finish with some tooling-costs myth-busting (cheap tools, mirror finishes, family molds).   Episode Sections: 00:00 Intro & today's topic 01:58 Why costs balloon: tolerances & cosmetics  06:52 Lever #1 — Design & DFM (wall thicknesses, material choice)  14:40 Lever #2 — Tooling decisions (steel grades, cavities)  22:44 Lever #3 — Processing & production setup  27:35 Myth-busting: cheap tools, mirror finishes, family molds  31:23 Recap & where the biggest savings really are   Related content... Product Tooling: Possible To Avoid Paying for it in Full? Common Design For Manufacture Improvements On Plastic Injection Molded Parts When To Sign Off On Injection Mold Tooling? Inside the Journey from DFM to T0→T2 [Podcast] Plastic Playbook: Choosing The Right Polymer [Podcast] Mold Tooling Ownership: The term Chinese suppliers push for will shock you! The Conundrum of Investing in Tooling Before a Final Prototype Get in touch with us Connect with us on LinkedIn Contact us via Sofeast's contact page Subscribe to our YouTube channel Prefer Facebook? Check us out on FB

Matthew Elder joins Tomi and I on the show this week. Matthew is a technician out of Texas, He is just beginning his path in the automotive diagnostic world. We'll share advice for being successful, Tooling options, & finding a good shop. Website- https://autodiagpodcast.com/Facebook Group- https://www.facebook.com/groups/223994012068320/YouTube- https://www.youtube.com/@automotivediagnosticpodcas8832Email- STmobilediag@gmail.comPlease make sure to check out our sponsors!SJ Auto Solutions- https://sjautosolutions.com/Automotive Seminars- https://automotiveseminars.com/L1 Automotive Training- https://www.l1training.com/Autorescue tools- https://autorescuetools.com/   

In this episode, Pooja Ranjan and Leo Alt discuss the innovative project powdr, which aims to enhance the developer experience in the ZK ecosystem through automatic precompilation. They explore the motivations behind the project, its economic implications, and the challenges faced in the adoption of zero-knowledge technology. The conversation also touches on community contributions, early adopters, and the future of powdr in the evolving landscape of ZK projects.

Blockiert dein Code Review gerade mal wieder den Release oder ist es der unsichtbare Klebstoff, der Wissen im Team verteilt? In dieser Episode gehen wir der Frage auf den Grund, warum Reviews weit mehr sind als ein einfaches “looks good to me” und was sie mit sozialer Interaktion, Teamdynamik und Wissensverteilung zu tun haben. Wir sprechen mit Prof. Michael Dorner, Professor für Software Engineering an der TH Nürnberg, der seit Jahren zur Rolle von Code Reviews in der Softwareentwicklung forscht: mit Code Review Daten von Microsoft, Spotify oder trivago. Überall zeigt sich: Pull Requests sind mehr als technische Checks, sie sind Kommunikationsnetzwerke. Gemeinsam beleuchten wir, warum Tooling oft zweitrangig ist, wie sich Review-Praktiken historisch entwickelt haben und was das alles mit Ownership, Architektur und sogar Steuern zu tun hat. Ein Blick auf Code Reviews, der dir definitiv eine neue Perspektive eröffnet.Bonus: Wir erklären, warum alle Informatiker Doktoren auch Philosophen sind ;)Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

TakeawaysThe importance of community in creative challenges like Arch Inktober.Using prompts can enhance creativity and push artistic boundaries.AI tools can assist in the design process but require careful curation.Sketching techniques vary and can be influenced by technology.The significance of architectural history in contemporary design.Engaging with prompts allows for experimentation and exploration.Collaboration between artists can lead to richer outcomes.Reflection on one's work is crucial for growth and improvement.The balance between traditional and digital methods in art is evolving.Encouragement to embrace challenges and not overthink the creative process.TitlesNavigating the Challenges of Live RecordingCelebrating Arch Inktober: A Creative JourneyChapters00:00 Introduction and Technical Glitches05:11 Coffee Talk and Trends in Technology09:33 The Importance of Community and Student Engagement13:52 Arch Inktober: A Creative Challenge18:41 Creative Challenges and Experimentation23:07 Engaging with Artistic Prompts25:33 Sketching Techniques and Processes37:05 AI in Art: Mid-Journey Exploration44:41 Curating Artistic Outputs52:53 Reflections on Artistic Growth and LearningSend Feedback :) Support the showBuy some Coffee! Support the Show!https://ko-fi.com/coffeesketchpodcast/shop Our Links Follow Jamie on Instagram - https://www.instagram.com/falloutstudio/ Follow Kurt on Instagram - https://www.instagram.com/kurtneiswender/ Kurt's Practice - https://www.instagram.com/urbancolabarchitecture/ Coffee Sketch on Twitter - https://twitter.com/coffeesketch Jamie on Twitter - https://twitter.com/falloutstudio Kurt on Twitter - https://twitter.com/kurtneiswender

Sign up for Alex's first live cohort, about Hierarchical Model building!Get 25% off "Building AI Applications for Data Scientists and Software Engineers"Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:Why GPs still matter: Gaussian Processes remain a go-to for function estimation, active learning, and experimental design – especially when calibrated uncertainty is non-negotiable.Scaling GP inference: Variational methods with inducing points (as in GPflow) make GPs practical on larger datasets without throwing away principled Bayes.MCMC in practice: Clever parameterizations and gradient-based samplers tighten mixing and efficiency; use MCMC when you need gold-standard posteriors.Bayesian deep learning, pragmatically: Stochastic-gradient training and approximate posteriors bring Bayesian ideas to neural networks at scale.Uncertainty that ships: Monte Carlo dropout and related tricks provide fast, usable uncertainty – even if they're approximations.Model complexity ≠ model quality: Understanding capacity, priors, and inductive bias is key to getting trustworthy predictions.Deep Gaussian Processes: Layered GPs offer flexibility for complex functions, with clear trade-offs in interpretability and compute.Generative models through a Bayesian lens: GANs and friends benefit from explicit priors and uncertainty – useful for safety and downstream decisions.Tooling that matters: Frameworks like GPflow lower the friction from idea to implementation, encouraging reproducible, well-tested modeling.Where we're headed: The future of ML is uncertainty-aware by default – integrating UQ tightly into optimization, design, and deployment.Chapters:08:44 Function Estimation and Bayesian Deep Learning10:41 Understanding Deep Gaussian Processes25:17 Choosing Between Deep GPs and Neural Networks32:01 Interpretability and Practical Tools for GPs43:52 Variational Methods in Gaussian Processes54:44 Deep Neural Networks and Bayesian Inference01:06:13 The Future of Bayesian Deep Learning01:12:28 Advice for Aspiring Researchers

Recorded live at MBA Annual25 in Las Vegas, host Rebecca Kritzman and guests Ashley Sellers, Elaina McFarland, and Bobby Deery break down what lenders are asking for right now: AI-driven workflow efficiency, expanding use of soft-pull strategies, and dual processing to analyze Vantage Score alongside existing scores. Who are the speakers?Rebecca Kritzman – SVP, Experience & Partner Marketing, EquifaxAshley Sellers – VP, Mortgage Sales, EquifaxElaina McFarland – Leader, Solution Sales Experts (Credit & Verification), EquifaxBobby Deery – SVP, Product, Credit Division, EquifaxTogether, they explore the intersection of innovation, compliance, and customer trust.What were the major insights from Day Two?AI and Automation in Workflows: Lenders are adopting AI to streamline process flows and improve efficiency from application through close.Rising Interest in Dual Processing: Many lenders are testing Vantage Score alongside existing models to compare outcomes and assess portfolio risk.Soft Pull Momentum: Equifax's soft-pull tools are helping lenders pre-qualify borrowers and protect consumers' credit scores, especially under the new trigger law.Voice of the Customer: Product teams are incorporating direct lender feedback to guide new innovations such as income qualify and telco/pay-TV/utility data integrations.Education and Clarity: With rapid industry change — from FICO model updates to 1B vs. 3B credit reporting — customers are asking for clear, data-driven guidance. What challenges did attendees highlight?Widespread uncertainty dominated discussions — from pricing implications and trigger-law timing to confusion around single- vs. tri-bureau models. Customers expressed concern about misinformation and asked for help educating both lenders and consumers on what these changes truly mean.What recommendations did Equifax leaders share?Stand up dual-score processing to compare outcomes between Vantage and FICO models.Collaborate with Equifax product teams to provide feedback that shapes future solutions.Audit your process flows to align products (credit, verification, income qualify) with milestones that deliver the most value.Prioritize education and communication — both internally and with consumers — to navigate market shifts confidently. 

Imagine a world where handoff no longer exists and designers are moving fluidly in code…[Drew Wilson](https://x.com/drewwilson) is one of the people pulling that future into the present so this week's episode is a deep dive into his vision for the new design tool [Opacity](https://opacity.app/).Some highlights:- How team structures are changing- How to stand out when everyone is a builder- What design's “Github moment” will look like- The fracturing of the market for design talent- How Drew is approaching this startup differently- Where the new technical threshold is for designers- + a lot moreDrew is also building his new IDE called Loop - https://loupe.build/

Dominic Gannaway joins us to talk about Ripple.js, a new TypeScript-first UI framework built with its own templating language and a focus on clarity and reactivity. We explore how Ripple.js handles fine-grained updates through its track and block system, why it avoids global state, and how context plays a key role. Dominic also walks us through the developer experience, from the language server and VS Code integration to syntax highlighting and the Prettier plugin, plus how the framework handles error boundaries, server-side rendering, future plans, and more. Links Twitter: https://x.com/trueadm Github: https://github.com/trueadm LinkedIn: https://www.linkedin.com/in/dominic-gannaway-414b7750 Resources RippleJS GitHub: https://ripplejs.github.io RippleJS website: https://www.ripplejs.com/ 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 00:00 – Intro & What is RippleJS 01:00 – The Origins and Naming of Ripple 02:00 – A New UI Framework Built on TypeScript 03:30 – Creating a Custom Language and Templating System 05:00 – Building Ripple's Tooling and Language Server 06:00 – The Team, Open Source Growth, and Early Feedback 07:00 – From UI Framework to Meta Framework 09:00 – Integrating AI into the Dev Server 10:30 – Handling Controversy and Changing the Status Quo 11:30 – How Ripple Was Built in a Week 13:00 – Redesigning the Reactivity System 16:00 – Why Ripple Doesn't Use Global State 19:00 – Lessons Learned from Other Frameworks 21:00 – Naming Conventions and API Design Decisions 22:30 – Error Boundaries and Async Patterns in Ripple 24:00 – Accessibility and ByteDance Native App Integration 25:00 – The Team's Workflow and Contributor Culture 27:00 – Building TypeScript-First from Scratch 29:00 – Language Server, Source Maps, and VS Code Integration 31:00 – Building in Public and Open Source Collaboration 32:30 – The Future of Frontend Frameworks 34:00 – How Ripple's Ideas Might Influence Others 35:00 – AI, Security, and the Road Ahead 36:00 – Closing Thoughts & How to Get Involved

In this episode of Engineering Enablement, Laura Tacho and Abi Noda discuss how engineering leaders can plan their 2026 AI budgets effectively amid rapid change and rising costs. Drawing on data from DX's recent poll and industry benchmarks, they explore how much organizations should expect to spend per developer, how to allocate budgets across AI tools, and how to balance innovation with cost control.Laura and Abi also share practical insights on building a multi-vendor strategy, evaluating ROI through the right metrics, and ensuring continuous measurement before and after adoption. They discuss how to communicate AI's value to executives, avoid the trap of cost-cutting narratives, and invest in enablement and training to make adoption stick.Where to find Abi Noda:• LinkedIn: https://www.linkedin.com/in/abinoda  • Substack: ​​https://substack.com/@abinoda  Where to find Laura Tacho: • LinkedIn: https://www.linkedin.com/in/lauratacho/• X: https://x.com/rhein_wein• Website: https://lauratacho.com/• Laura's course (Measuring Engineering Performance and AI Impact): https://lauratacho.com/developer-productivity-metrics-courseIn this episode, we cover:(00:00) Intro: Setting the stage for AI budgeting in 2026(01:45) Results from DX's AI spending poll and early trends(03:30) How companies are currently spending and what to watch in 2026(04:52) Why clear definitions for AI tools matter and how Laura and Abi think about them(07:12) The entry point for 2026 AI tooling budgets and emerging spending patterns(10:14) Why 2026 is the year to prove ROI on AI investments(11:10) How organizations should approach AI budgeting and allocation(15:08) Best practices for managing AI vendors and enterprise licensing(17:02) How to define and choose metrics before and after adopting AI tools(19:30) How to identify bottlenecks and AI use cases with the highest ROI(21:58) Key considerations for AI budgeting (25:10) Why AI investments are about competitiveness, not cost-cutting(27:19) How to use the right language to build trust and executive buy-in(28:18) Why training and enablement are essential parts of AI investment(31:40) How AI add-ons may increase your tool costs(32:47) Why custom and fine-tuned models aren't relevant for most companies today(34:00) The tradeoffs between stipend models and enterprise AI licensesReferenced:DX Core 4 Productivity FrameworkMeasuring AI code assistants and agents2025 State of AI Report: The Builder's PlaybookGitHub Copilot · Your AI pair programmerCursorGleanClaude CodeChatGPTWindsurfTrack Claude Code adoption, impact, and ROI, directly in DXMeasuring AI code assistants and agents with the AI Measurement FrameworkDriving enterprise-wide AI tool adoptionSentryPoolside

Anthony and Katie are joined by Andreas Møller, co-founder of Nordcraft. Nordcraft aims to bring design and development closer together, and as you can imagine Andreas has a unique perspective on design tools. What happens to "hand-off" when designers can get their ideas 90% there?Find Andreas on BlueskyHosts:Anthony Hobday, Generalist Product Designer: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/hobdaydesign⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Katie Langerman, Systems Designer: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/KatieLangerman

Elixir creator, José Valim, is throwing his hat into the coding agent ring with Tidewave –a coding agent for full-stack web development. Tidewave runs in the browser alongside your app, but it's also deeply integrated into Rails and Phoenix. On this episode, José tells us all about it. Also: his agent flow, YOLO mode, an MCP hot take, and more.

Elixir creator, José Valim, is throwing his hat into the coding agent ring with Tidewave –a coding agent for full-stack web development. Tidewave runs in the browser alongside your app, but it's also deeply integrated into Rails and Phoenix. On this episode, José tells us all about it. Also: his agent flow, YOLO mode, an MCP hot take, and more.

Andreas Rossberg unpacks WASM 3.0, covering new capabilities like garbage collection, exception handling, tail calls, and support for 64-bit addressing with multiple memories. The discussion explores deterministic profiles following relaxed sim, WebAssembly's capability-based security model, and advances in sandboxing and module design. Andreas connects these features to practical use cases in JavaScript engines and applications like Google Sheets, then looks ahead to experimental work on threading, stack switching, and async programming models shaping the next phase of the WebAssembly ecosystem. Links Website: https://people.mpi-sws.org/~rossberg GitHub: https://github.com/rossberg Resources WASM 3.0 Completed: https://webassembly.org/news/2025-09-17-wasm-3.0 Chapters 00:00 Intro – Andreas Rossberg and the WebAssembly 3.0 Update 01:05 The State of WebAssembly Today 02:15 Why WebAssembly Exists Beyond the Web 03:20 From WebAssembly 2.0 to 3.0 – What's Actually New 04:30 Garbage Collection: A Game-Changer for Managed Languages 06:00 The Vision of WebAssembly as a Universal Compilation Target 07:40 How GC Support Unlocks Java, Kotlin, and Dart on WASM 09:10 Expanding to 64-bit Memory – Performance and Limits 10:40 WebAssembly for Databases, AI, and LLMs 12:00 Sandboxing and Security by Design 13:10 How Capabilities and Static Analysis Keep WASM Safe 14:30 Multi-Memory Support and Real-World Use Cases 16:00 Developer Ergonomics vs. Specification Purity 17:20 Tail Calls and Functional Programming Benefits 18:40 Function Tables and Secure Indirection 20:00 Exception Handling Finally Arrives 21:10 Determinism, Efficiency, and Why It Matters for Blockchain 22:30 SIMD and Hardware Divergence Across Platforms 24:00 Balancing Portability with Performance 25:20 The Design Philosophy Behind WebAssembly 26:30 Why WASM Rejects Language-Specific Features 27:40 Proposal Process: Who Decides What Gets In 29:00 Browser Vendors and Implementation Challenges 30:10 Early Deployments: GC, Tooling, and Adoption Stories 31:30 Threads, Stack Switching, and the Future of Concurrency 33:00 Async/Await and Coroutines on WebAssembly 34:30 What's Coming Next for WASM Developers 35:40 How to Get Involved – Working Groups and Proposals 37:00 Closing Thoughts and Thanks 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 elizabet.becz@logrocket.com (mailto:elizabeth.becz@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). 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)

Hi, Spring fans! In this installment we talk to Spring tooling legend Dr. Kris De Volder

Charlie Marsh built Ruff (an extremely fast Python linter written in Rust) and uv (an extremely fast Python package manager written in Rust) because he believes great tools can have an outsized impact. He believes it so much, in fact, that he started an entire company that builds next-gen Python tooling. On this episode, Charlie joins us to tell us all about it: why Python, why Rust, how they make everything so fast, how they're starting to make money, what other products he's dreaming up, and more.

This week on The Data Stack Show, Alexander Patrushev joins John to share his journey from working on mainframes at IBM to leading AI infrastructure innovation at Nebius, with stops at VMware and AWS along the way. The discussion explores the evolution of AI and cloud infrastructure, the five pillars of successful machine learning projects, and the unique challenges of building and operating modern AI data centers—including energy consumption, cooling, and networking. Alexander also delves into the practicalities of infrastructure as code, the importance of data quality, and offers actionable advice for those looking to break into the AI field. Key takeaways include the need for strong data foundations, thoughtful project selection, and the value of leveraging existing skills and tools to succeed in the rapidly evolving AI landscape. Don't miss this great conversation.Highlights from this week's conversation include:Alexander's Background and Early Career at IBM (1:06)Moving From Mainframes to Virtualization at VMware (4:09)Transitioning to AWS and Machine Learning Projects (8:22)What Was Missed From Mainframes and the Rise of Public Cloud (9:03)Security, Performance, and Economics in Cloud Infrastructure (12:40)The Five Pillars of Successful Machine Learning Projects (15:02)Choosing the Right ML Project: Data, Impact, and Existing Solutions (18:01)Real-World AI and ML Use Cases Across Industries (19:42)Building Specialized AI Clouds Versus Hyperscalers (22:08)Performance, Scalability, and Reliability in AI Infrastructure (25:18)Data Center Energy Consumption and Power Challenges (28:41)Cooling, Networking, and Supporting Systems in AI Data Centers (30:06)Infrastructure as Code and Tooling in AI (31:50)Lowering Complexity for AI Developers and the Role of Abstraction (34:08)Startup Opportunities in the AI Stack (38:53)When to Fine-Tune or Post-Train Foundation Models (43:41)Comparing and Testing Models With Tool Use (47:49)Skills and Advice for Entering the AI Field (49:18)Final Thoughts and Encouragement for AI Newcomers (52:31)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.

Charlie Marsh built Ruff (an extremely fast Python linter written in Rust) and uv (an extremely fast Python package manager written in Rust) because he believes great tools can have an outsized impact. He believes it so much, in fact, that he started an entire company that builds next-gen Python tooling. On this episode, Charlie joins us to tell us all about it: why Python, why Rust, how they make everything so fast, how they're starting to make money, what other products he's dreaming up, and more.

Quinn Slack (CEO) and Thorsten Ball (Amp Dictator) from SourceGraph join the show to talk about Amp Code, how they ship 15x/day with no code reviews, and why subagents and prompt optimizers aren't a promising direction for coding agents. Amp Code: https://ampcode.com/ Latent Space: https://latent.space/ 00:00 Introduction 00:41 Transition from Cody to Amp 03:18 The Importance of Building the Best Coding Agent 06:43 Adapting to a Rapidly Evolving AI Tooling Landscape 09:36 Dogfooding at Sourcegraph 12:35 CLI vs. VS Code Extension 21:08 Positioning Amp in Coding Agent Market 24:10 The Diminishing Importance of Model Selectors 32:39 Tooling vs. Harness 37:19 Common Failure Modes of Coding Agents 47:33 Agent-Friendly Logging and Tooling 52:31 Are Subagents Real? 56:52 New Frameworks and Agent-Integrated Developer Tools 1:00:25 How Agents Are Encouraging Codebase and Workflow Changes 1:03:13 Evolving Outer Loop Tasks 1:07:09 Version Control and Merge Conflicts in an AI-First World 1:10:36 Rise of User-Generated Enterprise Software 1:14:39 Empowering Technical Leaders with AI 1:17:11 Evaluating Product Without Traditional Evals 1:20:58 Hiring

Quinn Slack (CEO) and Thorsten Ball (Amp Dictator) from SourceGraph join the show to talk about Amp Code, how they ship 15x/day with no code reviews, and why subagents and prompt optimizers aren't a promising direction for coding agents.Amp Code: https://ampcode.com/Latent Space: https://latent.space/Full Video EpisodeTimestamps00:00 Introduction00:41 Transition from Cody to Amp03:18 The Importance of Building the Best Coding Agent06:43 Adapting to a Rapidly Evolving AI Tooling Landscape09:36 Dogfooding at Sourcegraph12:35 CLI vs. VS Code Extension21:08 Positioning Amp in Coding Agent Market24:10 The Diminishing Importance of Model Selectors32:39 Tooling vs. Harness37:19 Common Failure Modes of Coding Agents47:33 Agent-Friendly Logging and Tooling52:31 Are Subagents Real?56:52 New Frameworks and Agent-Integrated Developer Tools1:00:25 How Agents Are Encouraging Codebase and Workflow Changes1:03:13 Evolving Outer Loop Tasks1:07:09 Version Control and Merge Conflicts in an AI-First World1:10:36 Rise of User-Generated Enterprise Software1:14:39 Empowering Technical Leaders with AI1:17:11 Evaluating Product Without Traditional Evals1:20:58 Hiring Get full access to Latent.Space at www.latent.space/subscribe

Topics covered in this episode: * pandas is getting pd.col expressions* * Cline, At-Cost Agentic IDE Tooling* * uv cheatsheet* Ducky Network UI Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: pandas is getting pd.col expressions Marco Gorelli Next release of Pandas will have pd.col(), inspired by some of the other frameworks I'm guessing Pandas 2.3.3? or 2.4.0? or 3.0.0? (depending on which version they bump?) “The output of pd.col is called an expression. You can think of it as a delayed column - it only produces a result once it's evaluated inside a dataframe context.” It replaces many contexts where lambda expressions were used Michael #2: Cline, At-Cost Agentic IDE Tooling Free and open-source Probably supports your IDE (if your IDE isn't a terminal) VS Code VS Code Insiders Cursor Windsurf JetBrains IDEs (including PyCharm) You pick plan or act (very important) It shows you the price as the AI works, per request, right in the UI Brian #3: uv cheatsheet Rodgrigo at mathspp.com Nice compact cheat sheet of commands for Creating projects Managing dependencies Lifecycle stuff like build, publish, bumping version uv tool (uvx) commands working with scripts Installing and updating Python versions plus venv, pip, format, help and update Michael #4: Ducky Network UI Ducky is a powerful, open-source, all-in-one desktop application built with Python and PySide6. It is designed to be the perfect companion for network engineers, students, and tech enthusiasts, combining several essential utilities into a single, intuitive graphical interface. Features Multi-Protocol Terminal: Connect via SSH, Telnet, and Serial (COM) in a modern, tabbed interface. SNMP Topology Mapper: Automatically discover your network with a ping and SNMP sweep. See a graphical map of your devices, color-coded by type, and click to view detailed information. Network Diagnostics: A full suite of tools including a Subnet Calculator, Network Monitor (Ping, Traceroute), and a multi-threaded Port Scanner. Security Toolkit: Look up CVEs from the NIST database, check password strength, and calculate file hashes (MD5, SHA1, SHA256, SHA512). Rich-Text Notepad: Keep notes and reminders in a dockable widget with formatting tools and auto-save. Customizable UI: Switch between a sleek dark theme and a clean light theme. Customize terminal colors and fonts to your liking. Extras Brian: Where are the cool kids hosting static sites these days? Moving from Netlify to Cloudflare Pages - Will Vincent from Feb 2024 Traffic is a concern now for even low-ish traffic sites since so many bots are out there Netlify free plan is less than 30 GB/mo allowed (grandfathered plans are 100 GB/mo) GH Pages have a soft limit of 100 GB/mo Cloudflare pages says unlimited Michael: PyCon Brazil needs some help with reduced funding from the PSF Get a ticket to donate for a student to attend (at the button of the buy ticket checkout dialog) I upgraded to macOS Tahoe Loving it so far. Only issue I've seen so far has been with alt-tab for macOS Joke: Hiring in 2025 vs 2021 2021: “Do you have an in-house kombucha sommelier?” “Let's talk about pets, are you donkey-friendly?”, “Oh you think this is a joke?” 2025: “Round 8/7” “Out of 12,000 resumes, the AI picked yours” “Binary tree? Build me a foundational model!” “Healthcare? What, you want to live forever?”

Creating 3D assets can be daunting, but does it have to be? Mahima and Rakesh are on a quest to democratize 3D content creation with AssetGen, a foundation model for 3D. They discuss the challenges of training such a model given the scarcity of available data and how large language models have unlocked key solutions. As if that weren't enough, they're also tackling the ambitious goal of generating entire worlds from a simple prompt. Tune in to learn more! Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don't forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_, @passy.bsky.social). Fancy working with us? Check out https://www.metacareers.com/. Links Horizon Worlds Desktop Editor: https://developers.meta.com/horizon-worlds/advanced-tools  Horizon Worlds Studio: https://developers.meta.com/horizon-worlds/studio/application Meta Ray-Ban Display: https://www.meta.com/gb/ai-glasses/meta-ray-ban-display/  MTP 77 - How to build a human-computer interface for everyone: https://engineering.fb.com/2025/08/04/virtual-reality/building-a-human-computer-interface-for-everyone-meta-tech-podcast/  Timestamps Intro 0:06 Introduction Mahima 1:39 Introduction Rakesh 2:57 Team mission 3:26 Why is 3D content hard to create? 5:15 The Metaverse 7:49 Tooling vision in Horizon Worlds 10:31 AssetGen Architecture 15:27 Consolidating models 18:25 From assets to worlds 19:22 Time to generate 24:46 Feedback loop 26:41 What's the market for AssetGen 29:49 What's available today? 31:26 What's next? 32:11 Outro 35:24

Razor Tooling is evolving! Carl and Richard talk to David Wengier about the changes coming for Razor Pages in the next version of Visual Studio. David talks about the realization that much of the new work in Razor ties closely to Roslyn, which has resulted in a new co-hosting model that means higher performance and reliability for your web pages! The conversation delves into how capabilities in Visual Studio Code are shared with Visual Studio and vice versa, as well as the role of the Language Service Protocol in making it easier to bring more powerful tools to you.

Alexander Lichter joins the podcast to talk about Rolldown, a bundler built in Rust by Void Zero that aims to replace Rollup and ESBuild with faster builds and better enterprise scalability. He dives into the power of OXC and Oxlint, the push toward a unified JavaScript toolchain, and previews what to expect at ViteConf 2024. Links X: https://x.com/TheAlexLichter Website: https://www.lichter.io Mastodon: https://hachyderm.io/@manniL GitHub: https://github.com/manniL YouTube: https://www.youtube.com/@TheAlexLichter Twitch: https://www.twitch.tv/TheAlexLichter LinkedIn: https://www.linkedin.com/in/alexanderlichter Resources Rolldown: How Vite Bundles at the Speed of Rust: https://squiggleconf.com/2025/sessions#rolldown-how-vite-bundles-at-the-speed-of-rust Rolldown: https://rolldown.rs Rolldown-vite migration: https://vite.dev/guide/rolldown Oxlint Type Aware linting (preview) announcement: https://oxc.rs/blog/2025-08-17-oxlint-type-aware.html ViteConf: https://viteconf.amsterda Benchmarks: Minifier: https://github.com/privatenumber/minification-benchmarks Linter: https://github.com/oxc-project/bench-javascript-linter Parser: https://github.com/oxc-project/bench-javascript-parser-written-in-rust Transformer: https://github.com/oxc-project/bench-transformer/ Bundler: https://github.com/rolldown/benchmarks Chapters 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)! Let us know by sending an email to our producer, Em, at emily.kochanek@logrocket.com (mailto:emily.kochanek@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). 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) Special Guest: Alexander Lichter.

Willard and Dibs continue to debate if the 49ers are closer to a Super Bowl or to a complete re-tooling and discuss where Brock Purdy fits into this whole equation.

Web development is constantly evolving, and so are the tools we use to build. In this episode, Amy and Brad chat with the organizers of Squiggle Conf about the future of web dev tooling, how conferences shape the developer experience, and why community matters just as much as code.Chapters0:00 - Intro0:34 - Meet the Guests: Squiggle Conf OrganizersSquiggle Conf1:19 - What Makes Squiggle Conf Unique3:19 - Tooling and Developer Experience3:30 - Penguins, IMAX, and the Conference Venue4:18 - Who Should Attend Squiggle Conf5:31 - How Talks Are Selected and Curated6:51 - Social and Community Aspects of the Conference12:19 - Behind the Scenes of Organizing a Conference17:46 - Lessons Learned from Running Events23:30 - The Role of Tooling in Modern Development27:21 - Browser-Based Tools and Their Impact28:51 - Shoutout to Astro and Other FrameworksAstroStarlight - Astro's template for documentation33:51 - Comparing Different Conference Experiences38:55 - Building Momentum in the Developer Community40:45 - Looking Ahead: The Future of Squiggle Conf42:02 - Final Thoughts from the Organizers43:43 - Picks and PlugsAre the Types Wrong? — a package & CLI tool by Andrew Branch from the TypeScript teamThe Harry Potter movie seriesCloudflareOne Switch - Mac Menu Bar AppRedwoodSDK

Inventory and materials management may not sound glamorous, but for us—and for any thriving shop—it's the difference between healthy cashflow and a financial chokehold. In this Machine Shop MBA conversation, we break down how smart inventory practices—both physical and digital—can free up space, cut costs, and improve delivery performance. From raw materials and finished goods to WIP and cutting tools, we share the financial, operational, and workflow implications of what you keep on the shelf (and what you shouldn't). You'll hear real-world examples of vendor-managed material programs, strategies for keeping traceability without burying yourself in admin work, and ways we've turned “dead” stock into real cash. We also dig into why inventory accuracy matters beyond just making parts—touching on tax implications, property valuations, and how inventory missteps can kill the value of your business in a sale. And if you've ever lost hours hunting for the right cutter or fixture, our storage and tracking advice might change the way you think about tooling forever. This episode isn't about counting nuts and bolts—it's about building an inventory strategy that supports your cashflow, your team's efficiency, and your long-term profitability. Segments (0:24) Paperless Parts: Quoting made simple, profitable, and powerful (3:09) Why inventory is “sneaky important” for cashflow, workflow, and profitability (4:00) Common categories: raw materials, finished goods, consumables, and workholding (6:30) “Part stock” vs. catalogued vs hybrid strategies (7:58) Calculating the real cost of capital when buying material in bulk (10:45) Consolidating material sizes to reduce stock complexity (13:07) Physical storage, traceability, and avoiding costly scrap from lost certs (15:07) Labeling and marking best practices—from PO numbers to color codes (19:05) Storage layouts that save space and speed up retrieval (22:28) FIFO, LIFO, and how inventory accounting can impact your taxes (24:07) Why you need to check out the SMW Autoblok Catalogue  (24:50) Why WIP can matter for accurate financials and business valuation (29:24) Cycle counting vs. painful year-end full inventory counts (33:26) Real-world wins from knowing exactly what's on your shelves (36:10) Avoiding the trap of overbuilding and obsolete finished goods (39:09) Using contracts and order commitments to protect yourself from rev changes (42:02) Inventory strategies for cutting tools—your most critical shop consumable (45:11) The value of having the right tool at the right time vs. lowest cost (49:45) Why random storage beats “organized” by type for cutting tools (52:19) Fixture storage, location tracking, and purging rarely used setups (54:39) How reviewing inventory can generate sales and free up cash (57:35) Key takeaways for building a smart, profitable inventory strategy  (58:42) Grow your top and bottom line with CLA Resources mentioned on this episode Tooling and the Demon of Chaos Unlocking Tax Savings: Essential Strategies You Can Implement Immediately Paperless Parts: Quoting made simple, profitable, and powerful Why you need to check out the SMW Autoblok Catalogue  Grow your top and bottom line with CLA Connect With MakingChips www.MakingChips.com On Facebook On LinkedIn On Instagram On Twitter On YouTube

AI coding agents are getting wild. Scott and Wes break down the latest tools that run in the background, write code across multiple steps, and charge you $200 a month to do it. From CLI-based primitives to full-on copilots, this episode covers the next wave of dev tools and what it takes to use them effectively. Show Notes 00:00 Welcome to Syntax! 03:13 Background Agents. 04:26 Appropriate tasks for background agents. 12:46 CLI tooling. 14:17 Claude Code Pricing. 18:20 Approaches to get the most from these tools. 19:56 PRD Documents. Atlasian What's a PRD Document. 20:50 Claude Taskmaster. Langflow. 25:29 Sick Picks & Shameless Plugs. Sick Picks Scott: RingConn. Wes: Dell Projector Shameless Plugs Scott: Syntax on YouTube. Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads