Podcasts about Technical

Episode 183 of the Award Travel 101 podcast, hosted by Angie Sparks and Cameron Laufer, covers the latest points and miles news, personal card updates, and practical award travel strategies. The hosts discuss current promotions, including back-to-school airline shopping portal bonuses, Citi's 20% transfer bonus to Flying Blue, and Chase Freedom Flex's upcoming removal of foreign transaction fees. They also highlight a concerning change from Singapore Airlines, which appears to require members to have KrisFlyer miles in their accounts before they can search award availability, making trip planning more difficult. Angie and Cameron also share their recent credit card activity, including meeting spending requirements, closing cards with high annual fees, and adjusting travel plans after flight cancellations.The main topic focuses on how to stretch 100,000 American Express Membership Rewards points into a vacation for two, using a budget of 100,000 points plus up to $1,000 out of pocket. Angie shares examples for Toronto, Denver, and San Juan, combining airline transfer partners like Aeroplan, Delta, JetBlue, and Hilton to maximize value, while Cameron presents sample itineraries to Park City, Orlando, and Madrid using transfer partners, Hilton points, and Amex Travel benefits. The episode emphasizes that flexibility with destinations and travel dates is often the key to finding great award availability. The tip of the week encourages listeners not to hesitate to close credit cards that no longer provide value, especially when the annual fee outweighs the benefits.Episode Links: Back to School OffersCiti to Flying Blue Transfer BonusFreedom Flex no Foreign Transaction FeeSingapore Search RestrictionsWhere to Find UsThe Award Travel 101 Facebook Community.To book time with our team, check out Award Travel 1-on-1.You can also email us at 101@award.travelBuy your Award Travel 101 Merch hereReserve tickets to our Late Summer 2026 Meetup in Milwaukee now. award.travel/mke2026Our partner CardPointers helps us get the most from our cards. Signup today at https://cardpointers.com/at101 for a 30% discount on annual and lifetime subscriptions! Lastly, we appreciate your support of the AT101 Podcast/Community when you signup for your next card!Technical note: Some user experience difficulty streaming the podcast while connected to a VPN. If you have difficulty, disconnect from your VPN.  

We're back home and semi-rested after one of if not the best Terminus Festivals yet. Four days of legendary acts delivering, bands just entering their heyday making excellent showings, and a handful of unexpected surprises from hitherto unknown to us acts still has us buzzing, so join us on our day-by-day recap on this week's podcast. 

For decades, startup success followed a familiar path: build a prototype, raise venture capital, hire a team, develop a product, and hope to reach market before the money runs out. Artificial intelligence is rewriting that playbook. An effective AI capital strategy now requires founders to think beyond fundraising and focus on building systems that create value long before investors write a check. In Part 2 of our conversation with Danny Carpio, we explored how AI is reshaping venture capital, startup economics, and software development. The discussion wasn't about replacing investors — it focused on a much larger shift: AI is lowering the cost of building products while raising the importance of strategic execution. As development gets cheaper, founders have to prove they can build sustainable businesses, not just impressive technology. About Danny Carpio Danny Carpio is an organizational architect, systems builder, and the author of The Unfirm: The New Unit of Scale Is You. Over the past 13+ years, he has designed operating models, governance structures, and investment architectures for venture-backed startups, decentralized organizations, and multi-entity networks. His work has helped organizations raise and manage eight-figure capital pools, incubate new businesses, and build scalable systems where no established blueprint existed. A licensed attorney, Danny also brings legal and governance expertise to selected clients, integrating operational strategy with practical business execution. Learn more about Danny and his work on his LinkedIn profile: https://www.linkedin.com/in/danny-carpio-9703a043/. AI Capital Strategy Changes the Role of Venture Capital Traditionally, venture capital solved one primary problem: it gave startups enough money to build products that would otherwise be too expensive to create. That equation is changing. Modern AI tools let small teams prototype applications, create marketing assets, automate operations, and validate ideas at a fraction of the historical cost. That means founders can test assumptions before they ever seek outside funding. Danny described this shift as moving structural barriers farther downstream. Instead of requiring significant investment just to get started, entrepreneurs can now build meaningful proof before approaching investors. That doesn't eliminate venture capital — it changes its purpose. Rather than financing basic product development, investors increasingly accelerate companies that have already shown traction, market understanding, and operational discipline. Capital is becoming an accelerator instead of the starting line. AI Capital Strategy Rewards Builders Who Reduce Risk Investors have always looked for promising ideas. Today, they're also looking for founders who understand uncertainty. Throughout the discussion, Danny emphasized that markets are changing so fast that no one has a complete blueprint. Because of that, founders need to demonstrate adaptability rather than certainty. Successful entrepreneurs are no longer expected to predict the future perfectly — they're expected to: Test assumptions quickly Learn from customer feedback Adjust direction intentionally Repeat the process continuously An effective AI capital strategy demonstrates learning velocity. If a startup can validate assumptions every few weeks instead of every six months, it becomes far easier for investors to evaluate both the product and the leadership team. AI Capital Strategy Depends on Cross-Functional Thinking One of the strongest themes from the conversation was that technical excellence alone is no longer enough. Developers remain essential. Business leaders remain essential. Product thinkers remain essential. But AI lets each discipline contribute earlier than ever before. Danny encouraged developers to partner with business-minded collaborators much earlier in the development cycle, instead of waiting until the software is nearly complete. Likewise, founders should involve technical experts before making major strategic commitments. This collaborative approach cuts expensive rework and improves product-market alignment. In practical terms, modern startups benefit from combining: Technical expertise Customer understanding Business strategy Legal guidance Product design AI accelerates each discipline individually. Systems thinking is what connects them into a competitive advantage. The strongest startups don't build faster because of AI — they make better decisions because the right people collaborate sooner. AI Capital Strategy Requires Better Feedback Loops One recurring idea throughout the interview was the importance of continuous feedback. AI dramatically shortens development cycles — but it also shortens the time it takes to make expensive mistakes. As founders produce prototypes faster, they have to evaluate them faster too. Danny described this as building feedback loops that operate at every level of the business, from daily work to long-term strategy. That philosophy applies across an organization: Review customer feedback frequently Measure product adoption consistently Revisit strategic assumptions regularly Validate technical decisions continuously Without these feedback mechanisms, AI just lets organizations scale poor decisions more efficiently. Businesses with disciplined review processes, on the other hand, gain the confidence to move quickly because they know problems will surface early. AI Capital Strategy Is Really About Execution One of the most valuable insights from the conversation challenged a common startup assumption. Many founders believe funding creates success. In reality, funding amplifies execution. Money can't: Compensate for unclear priorities. Replace customer understanding. Fix poor communication between technical and business teams. Instead, investment magnifies whatever already exists inside an organization. The same principle applies to AI. Founders who understand their customers, document their processes, and iterate intentionally get tremendous leverage from modern AI tools. Meanwhile, organizations chasing technology without operational discipline often produce more activity than meaningful progress. AI makes it easier to build products. It does not make it easier to build successful businesses. Conclusion Artificial intelligence is transforming far more than software development. It's redefining how startups are funded, how products are built, and how competitive advantages are created. An effective AI capital strategy recognizes that funding alone is no longer the differentiator it once was. Today's founders have unprecedented opportunities to validate ideas, build early traction, and demonstrate execution before approaching investors. Those who combine technical expertise with strategic thinking and continuous learning will stand out in an increasingly crowded marketplace. The future belongs to organizations that treat AI as a force multiplier for disciplined systems — not as a shortcut around them. Stay Connected: Join the Developreneur Community

Today's Topics:1. Sound Signature Review 6.232 – T&K Vorix 30 Ti on .308 and 300 BLK bolt-action rifles. Multi-cartridge testing for this lightweight and compact bolt-action rifle silencer, to fully characterize its behavior. Technical discussion of last week's report (00:07:22)a. Intro and recap – hunting silencer? (00:08:52)b. Vorix 30 Ti general overview (00:11:55)c. Vorix 30 Ti silencer design and functional physics (00:16:18)d. Hazard Map Brief 8.1.29 (00:24:07)e. Vorix 30 Ti silencer performance with .308 and 300 BLK (00:33:18)f. Performance Comparisons and Overall thoughts (01:01:54)2. Sound Signature Review 6.233 – Otter Creek Labs Infinity 556K on the MK18 with three different end caps. Bonus silencer tone study for PEW Science Members. How does the OCL Infinity technology behave when it has a more dedicated bore for the 5.56 cartridge? Any improvements over the larger 30 caliber Infinity? Introductory discussion for today's big report on this variable back pressure hard use silencer with an advanced analysis of “tone” physics that are always included in the Suppression Rating. (01:08:13)Sponsored by  Legion Athletics and the PEW Science Laboratory!Legion Athletics: use code pewscience for BOGO off your entire first order and 20% cash back always!

Imagine being able to dig through Shakespeare's manuscripts and ask him about his writing process. Did King Lear survive in the first draft? What if Hamlet originally said, “To live or not to live?” While we can only dream about that opportunity, scholar and Everyday Shakespeare host Caroline Bicks experienced something close to it when she gained unprecedented access to the archives of another famous author: Stephen King. The Bard of Avon and the King of Horror have more in common than you might think. Both are popular and prolific authors who have been praised and derided for writing for the masses. But both also pay close attention to the sounds of words, the flow of names, and the rhythms of sentences. And sometimes, King's work even takes inspiration from Shakespeare himself. In this episode, Bicks draws fascinating parallels between Shakespeare and King and shares how she became the first scholar permitted to explore King's personal papers. Her book, Monsters in the Archives: My Year of Fear with Stephen King recounts her chance to live every scholar's dream—while surrounded by the stuff of nightmares. From the Shakespeare Unlimited podcast. Published July 28, 2026. © Folger Shakespeare Library. All rights reserved. This episode was produced by Matt Frassica. Garland Scott is the executive producer. It was edited by Gail Kern Paster. Technical support was provided by Voice Trax West in Studio City, California. Web production was handled by Megan Fraedrich. Transcripts are edited by Leonor Fernandez. Final mixing services provided by Clean Cuts at Three Seas, Inc.

Technical difficulties live on air this morning, so here's what ya missed!See omnystudio.com/listener for privacy information.

If you think brewing sake in your brewery is out of reach, think again.Special Guests: Chijindu Onwuchekwa and Scott Lafontaine.

Dianne Penn is Head of Product for Anthropic's AI Research and Labs teams. She joined in 2023 as Anthropic's first technical product manager, when the entire product team was five engineers, and has since helped ship every model from Claude 2 through Fable, and helped incubate Claude Code, MCP, Skills, computer use, tool use, and reasoning. Before Anthropic, she helped build Alexa's AI at Amazon and, before that, traded high-yield bonds at JP Morgan Chase.In our in-depth conversation, we discuss:1. What Anthropic's early days were like2. The inflection points that turned Anthropic from an underdog into the fastest-growing company in history3. How exactly Claude got so good at coding4. The eval-driven development loop her team is pioneering5. How to find joy in AI when everything is moving this fast6. Why Claude's willingness to push back is key to its success7. Where human judgment remains irreplaceable—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and moreMercury—Radically different banking, now with Command—Episode transcript: https://www.lennysnewsletter.com/p/anthropics-first-technical-pm-on—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Dianne Penn:• LinkedIn: linkedin.com/in/dianne-na-penn—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction(02:31) Early Anthropic days(08:55) Big milestones(13:50) Inside the exponential(20:02) Token maxing(23:30) Anthropic Labs and the incubation model(27:30) How the research role works(31:35) How to become a top researcher(35:18) Frontier model safeguards(39:38) Hiring in the AI era(44:16) Building an eval set(47:48) Evals vs PRDs(49:55) The importance of hands-on leadership(52:46) Finding joy in AI(58:10) How Dianne uses Claude(01:01:05) Avoiding overreliance on AI(01:03:50) The constitution that makes Claude better(01:07:11) AI writing and verification(01:11:40) Where human brains will continue to be valuable(01:14:10) Navigating AI with kids(01:16:26) Alignment, the future of the PM role, and burnout(01:21:54) Lightning round and final thoughts—Referenced:• Anthropic: https://www.anthropic.com• Golden Gate Claude: https://www.anthropic.com/news/golden-gate-claude• Dario Amodei's website: https://darioamodei.com• Scaling Laws and Interpretability of Learning from Repeated Data: https://www.anthropic.com/research/scaling-laws-and-interpretability-of-learning-from-repeated-data• Tokenmaxxing: How Top Builders Use AI To Do The Work Of 400 Engineers: https://www.ycombinator.com/library/Pa-tokenmaxxing-how-top-builders-use-ai-to-do-the-work-of-400-engineers• Garry Tan on X: https://x.com/garrytan• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Introducing Labs: https://www.anthropic.com/news/introducing-anthropic-labs• Louis CK | about airplane Wi Fi: https://www.youtube.com/watch?v=me4BZBsHwZs• What happens after coding is solved? | Fiona Fung (Manager of the Claude Code and Cowork Teams): https://www.lennysnewsletter.com/p/building-the-most-ai-pilled-engineering• The Anthropic Hive Mind: https://steve-yegge.medium.com/the-anthropic-hive-mind-d01f768f3d7b• How to build a company that withstands any era | Eric Ries, Lean Startup author: https://www.lennysnewsletter.com/p/how-to-build-a-company-that-withstands• Fallout on Prime Video: https://www.amazon.com/dp/B0CN4GGGQ2• Fallout (video game): https://fallout.bethesda.net• Claude Tag: https://www.anthropic.com/news/introducing-claude-tag—Recommended books:• Crucial Conversations: Tools for Talking When Stakes Are High: https://www.amazon.com/dp/0071771328• How to Raise an Adult: Break Free of the Overparenting Trap and Prepare Your Kid for Success: https://www.amazon.com/How-Raise-Adult-Overparenting-Prepare/dp/1627791779• Incorruptible: Why Good Companies Go Bad... and How Great Companies Stay Great: https://www.amazon.com/dp/B0FWZZBPZB—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

This week, we cover how Starship Flight 13 finally prepares to launch amid a legal battle over SpaceX's proposed land swap at Starbase, plus a Chinese Long March 3B rocket gets struck by lightning during liftoff, yet still delivers its satellite safely. Then, guests Dr. Pascal Lee and astrobiologist Dr. Penny Boston join the show to mark the 50th anniversary of Viking 1's landing on Mars and revisit the mission's groundbreaking life-detection experiments and the decades-long controversy over what they actually found. The conversation traces Mars exploration from the earliest Mariner flybys through Viking's ambiguous, still-debated results—later explained by perchlorates in the Martian soil—and the fierce scientific rivalry the findings sparked. Join us! Headlines: SpaceX Starship Flight 13 faces engine and weather delays ahead of launch SpaceX land swap proposal sparks conservation group lawsuit over Rio Grande Valley wildlife preserve Chinese Long March rocket survives dramatic lightning strike during launch Main Topic: 50th Anniversary of Viking Mars Landers—Search for Life on Mars The evolution of Mars exploration from telescopes to Viking lander Early Mars missions: Mariner flybys, Soviet attempts, and breakthroughs in orbital imaging Viking 1 and 2: Ambitious design, life-detection experiments, and landing impact Mixed public and scientific reactions to Viking's first iconic Mars surface images Technical overview of the Viking biology experiments and their controversial results The unresolved debate: Did Viking detect life or chemical reactions on Mars? Personal accounts of key scientists, scientific disputes, and the "Wolf Trap" experiment that never flew Lessons from Viking: Limitations of technology, extremophile discoveries, and shifting strategies for detecting life The scientific case for seeking life in Martian caves and subsurface environments Critique of current and future Mars missions: Perseverance rover findings and value of Mars Sample Return Exploring planetary protection, contamination risks, and the challenges of certifying Martian samples= Key takeaways for future missions—bold searches, new technologies, and the ongoing quest for answers Hosts: Rod Pyle and Tariq Malik Guests: Pascal Lee and Dr. Penelope Boston Download or subscribe to This Week in Space at https://twit.tv/shows/this-week-in-space. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsor: rippling.ai/twis

Alf Dobbert-Baums: The Too-Technical PO and the One Who Was Willing to Experiment In this episode, we refer to Shift: From Product to People and the value of keeping the PO–developer conversation at the goal level. The Great Product Owner: The PO Who Was Willing to Drop the Spec and Trust the Developers Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "Let's ditch the technical part, and let's see what happens." - Alf Dobbert-Baums   The Great PO, in Alf's experience, is willing to experiment with letting go. She stopped writing detailed technical specifications and started writing plain user stories. Then — and this is the harder move — she stopped throwing them over the fence and walked into the developers' space to have the conversation. Alf had coached her toward it, and he watched the trust compound. Because she trusted the developers on the how, she had less work to do (the developers were closer to the system anyway) and the developers had room to make real decisions. The conversation stayed where it belonged: on the goal. Alf names the pattern this great PO embodied — open to experiments, willing to say "let's see what happens," and quietly resisting the seductive pull of getting technical because it feels safer. The Scrum Master's job is partly to make that letting-go feel safe enough to try.   Self-reflection Question: Where is your PO still writing the "how" — and what would it take for them to trust the developers enough to write only the "why" and the "what"? The Bad Product Owner: The PO Who Thinks They Know More Than the Developers Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "He said: 'developers can retrieve the information from the archive database.' The developer said: 'the information is not in the archive database.'" - Alf Dobbert-Baums   The anti-pattern is the PO who is too technical — the one who writes specs full of implementation detail and treats the developers as executors. Alf calls him John. John wrote a user story that told the developers exactly where to fetch the data from: the archive database. Then he tried to hand the story to Alf to present, the way a memo gets handed across a desk. Alf refused. He insisted John present it to the developers himself. John did. The first developer to speak said the information wasn't in the archive database. Alf hopes that moment humbled John a little. The point isn't whether John was right about the database — the point is the dynamic. When the PO writes the technical answer into the story, the developers stop being collaborators and become receivers. The translation work that creates real value — between user goal and technical option — never happens. The PO ends up with more work, less ownership from the team, and worse outcomes.   In this segment, we refer to Shift: From Product to People and the idea that great POs facilitate the conversation between user goal and team, rather than dictating it.   Self-reflection Question: When was the last time your PO wrote a technical detail into a story and the developers had to walk it back — and what would change if the PO trusted them to design the "how"?   [The Scrum Master Toolbox Podcast Recommends]

Episode 182 of the Award Travel 101 podcast opens with a spotlight on member Alison's incredible points-funded safari to Kenya, a reminder that award travel can unlock experiences far beyond flights and hotel chains. By leveraging a Virgin Red redemption, an Amex transfer bonus, and Alaska miles for long-haul flights, she and her travel partner enjoyed five nights at an all-inclusive safari lodge with twice-daily game drives for the equivalent of just over 80,000 points per night. The hosts also covered several noteworthy developments in the points world, including the opening of the new Chase Sapphire Lounge at Dallas/Fort Worth, the new Air Canada and Hyatt partnership, a lucrative Capital One Spark Cash Plus offer, and Rove adding Qantas as a transfer partner with a limited-time bonus.The hosts also shared personal travel updates and a useful booking lesson. Cameron discussed having a Qatar Airways flight to Thailand unexpectedly canceled without notice, ultimately reworking the itinerary through Chicago and securing a backup Starlux business class award. He also discovered that a Hyatt Place booking in Louisville appeared nonrefundable online but actually carried a 60-day cancellation policy after messaging Hyatt—a good reminder to verify cancellation terms instead of relying solely on what a website displays.The main discussion focused on the non-award tools that make the hobby easier. Angie and Cameron highlighted their favorite award search platforms, including Seats.aero, AwardWallet, MaxMyPoint, FlightConnections, and Google Flights, before expanding into budgeting software, credit card benefit tracking, and trip planning. AwardWallet and CardPointers were praised for keeping track of points, free night certificates, credits, and card offers, while Google Sheets, Google Maps, Facebook travel groups, TripIt, and ChatGPT have become essential planning tools for organizing itineraries, researching destinations, and building customized travel plans. The episode emphasized that while earning points is important, having the right collection of tools can save time, prevent costly mistakes, and make planning award travel far less stressful.Episode Links:Chase Lounge DFWCapital One Spark CashHyatt/ Air Canada partnershipRove adds QantasWhere to Find UsThe Award Travel 101 Facebook Community.To book time with our team, check out Award Travel 1-on-1.You can also email us at 101@award.travelBuy your Award Travel 101 Merch hereReserve tickets to our Late Summer 2026 Meetup in Milwaukee now. award.travel/mke2026Our partner CardPointers helps us get the most from our cards. Signup today at https://cardpointers.com/at101 for a 30% discount on annual and lifetime subscriptions! Lastly, we appreciate your support of the AT101 Podcast/Community when you signup for your next card!Technical note: Some user experience difficulty streaming the podcast while connected to a VPN. If you have difficulty, disconnect from your VPN.  

This week, we cover how Starship Flight 13 finally prepares to launch amid a legal battle over SpaceX's proposed land swap at Starbase, plus a Chinese Long March 3B rocket gets struck by lightning during liftoff, yet still delivers its satellite safely. Then, guests Dr. Pascal Lee and astrobiologist Dr. Penny Boston join the show to mark the 50th anniversary of Viking 1's landing on Mars and revisit the mission's groundbreaking life-detection experiments and the decades-long controversy over what they actually found. The conversation traces Mars exploration from the earliest Mariner flybys through Viking's ambiguous, still-debated results—later explained by perchlorates in the Martian soil—and the fierce scientific rivalry the findings sparked. Join us! Headlines: SpaceX Starship Flight 13 faces engine and weather delays ahead of launch SpaceX land swap proposal sparks conservation group lawsuit over Rio Grande Valley wildlife preserve Chinese Long March rocket survives dramatic lightning strike during launch Main Topic: 50th Anniversary of Viking Mars Landers—Search for Life on Mars The evolution of Mars exploration from telescopes to Viking lander Early Mars missions: Mariner flybys, Soviet attempts, and breakthroughs in orbital imaging Viking 1 and 2: Ambitious design, life-detection experiments, and landing impact Mixed public and scientific reactions to Viking's first iconic Mars surface images Technical overview of the Viking biology experiments and their controversial results The unresolved debate: Did Viking detect life or chemical reactions on Mars? Personal accounts of key scientists, scientific disputes, and the "Wolf Trap" experiment that never flew Lessons from Viking: Limitations of technology, extremophile discoveries, and shifting strategies for detecting life The scientific case for seeking life in Martian caves and subsurface environments Critique of current and future Mars missions: Perseverance rover findings and value of Mars Sample Return Exploring planetary protection, contamination risks, and the challenges of certifying Martian samples= Key takeaways for future missions—bold searches, new technologies, and the ongoing quest for answers Hosts: Rod Pyle and Tariq Malik Guests: Pascal Lee and Dr. Penelope Boston Download or subscribe to This Week in Space at https://twit.tv/shows/this-week-in-space. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsor: rippling.ai/twis

Best Practices for Explaining a Technical Concept Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. In pitching investors, founders must explain how their product works. For those with highly technical products, here are some best practices for explaining it to others. Start with what the audience knows. Bridge the gap between their current knowledge and the topic under discussion. Avoid acronyms and jargon that require expertise in the space. Use a concept the audience already knows. Create an analogy that describes the technical concept of what is known. For example, the medical device acts like a blender that mixes the fluids. Focus on the core technology and avoid ancillary information as it complicates things. Break the technical concept down into a three-step process. This can help describe a technical concept as it shows how it works in a simplified manner. Throughout the process, check for understanding. Fill in the audience gaps of understanding. Adjust your presentation for the technical level of the audience. Consider these points for explaining technical concepts. Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let's go startup something today. _________________________________________________________ For more episodes from Investor Connect, please visit the site at: http://investorconnect.org Check out our other podcasts here: https://investorconnect.org/ For Investors check out: https://tencapital.group/investor-landing/ For Startups check out: https://tencapital.group/company-landing/ For eGuides check out: https://tencapital.group/education/ For upcoming Events, check out https://tencapital.group/events/ For Feedback please contact info@tencapital.group Please follow, share, and leave a review. Music courtesy of Bensound.

With one foot out the door for Calgary and Terminus Festival, we're offering up a fairly light and breezy Pick Five episode focusing on sentimental songs. What in particular do we mean by that? Nostalgic? Melancholy? A little cheesy? Personally resonant? Listen and find out.

Today's Topics:1. Sound Signature Review 6.231 – LayerX Strake 9 MP5 testing. It's been about 3 months since you've seen the MP5! Welcome back, subgun friends. This is the relatively light and compact Strake 9. Hybrid designs and low back pressure – what happens when the silencer is small? Can this beat the HUXWRX Cash 9 at its own game? Technical deep dive for the report published last week. (00:10:12)a. Intro and recap – what is this silencer for? (00:11:59)b. Strake 9 general overview (00:14:50)c. Strake 9 silencer design and functional physics (00:17:49)d. Hazard Map Brief 8.1.28 (00:24:39)e. Strake 9 silencer performance (00:30:58)f. Performance Comparisons and Overall thoughts (00:40:46)2. Sound Signature Review 6.232 – T&K Vorix 30 Ti on .308 and 300 BLK bolt-action rifles. Multi-cartridge testing for this lightweight and compact bolt-action rifle silencer, to fully characterize its behavior. A little under 1.5-in diameter, and less than 8 inches long… yet bringing the performance? Pleasant surprises seem to becoming more commonplace in today's silencer market, which is great! Let's take a look at these interesting physics in this introduction to the report published today. (00:46:16)Sponsored by  Legion Athletics and the PEW Science Laboratory!Legion Athletics: use code pewscience for BOGO off your entire first order and 20% cash back always!

Oliver Meinhold takes us back to the basics of cleaning & sanitation in the brewery.Special Guest: Oliver Meinhold.

Do you need to understand code before you can build a technology company or lead a team of developers? Five years after our previous conversation, I welcome Sophia Matveeva back to the podcast. Sophia is the founder of Tech for Non-Techies, where she helps founders and business professionals understand how technology products are created, tested, managed and turned into commercial ventures. A great deal has changed since we last spoke. Generative AI tools can now turn a written description into a working prototype within hours. For someone who has spent years believing a lack of coding experience disqualified them from building a technology business, that removes a significant barrier. Sophia believes this is the best time yet to be a non-technical founder, although her reasoning goes beyond AI-assisted coding. Research into billion-dollar technology companies shows that non-technical founders now make up a much larger share of founding teams than they did a decade ago. Many of these businesses sell technology to other companies, where commercial knowledge, customer relationships and an understanding of industry problems matter enormously. We discuss where AI belongs in the founder journey. Sophia recommends using tools such as Lovable or Replit to create a simple test product, show it to potential customers and learn whether people would use or pay for the idea. This allows founders to test their assumptions before committing substantial money to development. The boundary appears when that prototype becomes a real product. Once software stores customer information, processes payments or supports a commercial service, security and technical architecture cannot be treated as optional details. Sophia argues that professional developers are still needed to inspect the code, prepare the product for production and address problems a non-technical founder may not know exist. Her point is simple. AI can help a founder reach the testing stage sooner and at a lower cost. It cannot tell someone with no engineering experience whether the generated code is safe, maintainable or ready to support paying customers. Sophia also shares what she learned from managing her first development team. After raising investment, she attempted to compensate for her technical insecurity by taking a coding course and becoming involved in work she did not fully understand. The result was micromanagement, constant interruptions and frustrated developers. A better approach begins with business priorities. Founders should explain what customers want, ask developers about effort and tradeoffs, agree on what will be delivered during the next work cycle, then give the team the space required to complete it. They should also allow time for technical debt, the less visible maintenance work that prevents hurried development from creating larger problems later. We finish with advice for any business leader who wants greater technology fluency. Sophia recommends joining product meetings, contributing customer knowledge and building relationships with technical colleagues who want to understand the commercial side of the company. Neither side needs to become the other. They need enough shared language to make better decisions together. If AI has removed the cost of testing many technology ideas, what is stopping you from finding out whether yours could work? Listen to the episode, try Sophia's exercise and share your experience with me.

Don’t Fade and Die in AI Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX: https://theultimatepartner.com/experience/ Matt Yanchyshyn, VP AWS Marketplace, Rekha Thangelapalita, Elastic GSI Leaders; Allison McFadden, Accenture AWS Leader; and James Kang of Nvidia join Ultimate Partner. In this panel discussion, leaders from Elastic, Accenture, Nvidia, and AWS dissect the urgent shifts in the ecosystem, emphasizing that partners must adapt to AI and agentic co-selling or risk fading away completely. The conversation explores the necessity of deep co-engineering, the power of multi-product solutions in the AWS marketplace, and how automated agents are now replacing traditional human sales pipeline progression. By embracing data readiness and strategic collaboration, organizations can survive the “token maxing” era, effectively scale their enterprise opportunities, and align with NVIDIA’s five-layer strategy to dominate the new cloud landscape. https://youtu.be/zUkL4Wqsa68 Key Takeaways AI agents will automate the majority of AWS partner co-selling attachments and opportunity progressions this year. Partners who fail to embrace agentic workflows and automated governance face the existential risk of fading into obsolescence. Successful multi-product offerings require a “blood to all organs” approach that benefits the client, the ISV, the GSI, and the hyperscaler simultaneously. Nvidia’s “five-layer cake” model emphasizes that successful outcomes at the application layer automatically drive growth for all underlying infrastructure. The “token maxing” phenomenon is forcing enterprises to seek cost-effective, open-model alternatives to scale their generative AI securely. Integrating GSIs and ISVs on the AWS marketplace significantly increases enterprise deal sizes and long-term customer renewal rates. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags strategic collaboration agreement, data readiness engine, agentic co-sell, semantic layer, token maxing, five layer cake, accelerated computing platform, open models, cloud consumption, multi-product solutions, partner central agents, propensity data, automated opportunity progression, generative AI governance Transcript Matt Y and Panel Audio Podcast [00:00:00] Vince Menzione: You have a choice. You can embrace them and figure it out and get governance and, and make your data available. Um, use the partner, central agent, move to Agen Co-sell, or you can fade and die. [00:00:11] Vince Menzione: You can feel it happening. The ecosystem is shifting beneath us, the way Hyperscalers are partnering, how AI is remaking the channel and what it means to win in 2026. [00:00:22] Vince Menzione: Welcome to the Ultimate Partner Podcast. I’m Vince Menzi. Own your host. And each week I sit down with leaders at the intersection of technology, partnerships and outcomes. The voices shaping how ecosystems actually work. We talk about what’s real, what’s changing, and what it takes to lead in this era where the partner channel isn’t just part of the strategy. [00:00:44] Vince Menzione: It is the strategy because [00:00:46] Vince Menzione: being in the room changes everything. Let’s start. [00:00:51] Vince Menzione: We’ve got some amazing leaders joining us. So I think probably for a little bit of context, maybe just start with Rika. You can introduce yourself, your role and, uh, what, what you’ve been doing at Elastic. Yeah. [00:01:03] Rekha Thangellapalli: Yeah, sounds great. [00:01:04] Rekha Thangellapalli: Hi everyone. I’m Reka and I lead GSI Alliances at Elastic. Um, for the past 14 years, I’ve had the pleasure of building different kinds of partner ecosystems across companies such as SAP. MuleSoft, Salesforce, Coupa, and now Elastic. Um, I wanna thank Ultimate partner and Vince for having us here today. Thank you and the panel of these incredible speakers for joining me on stage. [00:01:31] Rekha Thangellapalli: Um, very excited for the conversation today. [00:01:33] Vince Menzione: We love Elastic, and you’ve had some of your other leaders on stage at other events. As such, the quality of your leadership team is amazing. Thank you. [00:01:42] Rekha Thangellapalli: I wholeheartedly agree. [00:01:45] Allison McFadden: Excellent. Um, hello everyone. Allison McFadden. I lead our North America AWS practice at Accenture. [00:01:52] Allison McFadden: Uh, I’ve been there for five years, and truth be told, it was my first partnership role, my first formal partnership role. Uh, so I can take some tips from all of you in the room here today. Prior to that, I was 21 years with IBM, and I got into partnerships because my last role at IBM was actually trying to build. [00:02:14] Allison McFadden: Linux business on the mainframe, and I had to have partners. I had to have partners to help me with workloads to run there. So I kind of learned, uh, trial by fire. But I’m excited for the conversation today. Excited to be in this room and excited to talk about what we’re doing with, uh, elastic. Thank you. [00:02:34] James Kang: Uh, my name is James Kang. Nice to see and meet everyone here. Vince, thank you for the opportunity. Thank you [00:02:38] Vince Menzione: for being here. [00:02:39] James Kang: Um, I’m with Nvidia, so I help manage the AWS partnership at Nvidia all up. Um, I guess fun fact, I’m former AWS and so I see a lot of very familiar faces here in the front row. Uh, former colleagues and then current friends. [00:02:56] James Kang: And so, uh, looking forward to the conversation. [00:02:59] Vince Menzione: Great. Well, we’ll start with an easy tia. Matt. This is not directed to you, directed to the others. So what does a successful AWS partnership look like from your C? So we’ll start with Eureka. [00:03:09] Rekha Thangellapalli: Sure. So from an ISV perspective, I think we really are looking at three things. [00:03:15] Rekha Thangellapalli: Uh, mutual investment building together. And scaling together. So when we talk about mutual investment, elastic recently signed a five-year SCA or strategic collaboration agreement with AWS. And while that is a significant milestone in our partnership, for us, what matters more is what it represents, and that is really a long-term commitment from both companies. [00:03:39] Rekha Thangellapalli: Towards product engineering, um, and joint go to market initiatives to deliver value to customers over time. And that’s what we see is that the best partnerships really compound and they build upon each other every year. Um, they don’t necessarily kind of reset every year. Um, next we talk about building together. [00:03:59] Rekha Thangellapalli: So, um. When we talk about joint solutions, we want to deliver solutions that are better together and the customers have to see us that way. And so whether it’s search, observability, or security, we’re looking at taking to market solutions that we can’t or necessarily don’t wanna take on our own. And finally we talk about scaling together. [00:04:22] Rekha Thangellapalli: And this is where marketplace, for instance, plays a big role, um, when customers can draw down on their cloud commitments, transact online and go from, you know, pilot to enterprise scale adoption in hours, not days. Um, this is when really everyone wins. Um, and this is also where partners like Accenture play a critical role. [00:04:47] Rekha Thangellapalli: Um, you know, the incredible amount of expertise that they bring, uh, the managed services capabilities and, um, their data assets actually play a huge role in having our customers realize that value faster. And, um, like Vince mentioned, at the end of the day, best partnerships are all all about creating kind of that. [00:05:07] Rekha Thangellapalli: Self-sustaining flywheel. And so it starts with investing together, building something unique, and having the customers realize that success faster because that success is really the only thing that’s gonna keep that flywheel going for everyone involved. I [00:05:26] Vince Menzione: absolutely. [00:05:26] Allison McFadden: Okay, amazing. I’m gonna riff off a few things Ika said, but from a GSI perspective. [00:05:32] Allison McFadden: A relationship with a WSA successful relationship with AWS looks slightly different. Um, so I think the first thing that we think of in the GSI Community common thread is that the client outcome and delivering value for clients is what we, what we’re striving for. Um, and so the partnership with AWS in that case, um, um, it has to, it has to. [00:06:01] Allison McFadden: Look like one team in front of our clients. So we have to show up indistinguishable, and that’s with AWS and with an ISV partner, it has to look like one solution in front of the client, especially moments that matter. So board meetings, um, you know, the time we’re gonna sign a deal, like we have to look like one team, uh, and keep our our client outcome, um, first and foremost in mind. [00:06:24] Allison McFadden: The second thing, and this is I think where the magic of all the people in this room comes into play. We can have as many discussions at a CEO level as we want. And if our client teams on the ground are not working together, it falls apart. Falls apart directly in front of the client. Yes. And that is a really hard thing to do. [00:06:45] Allison McFadden: So I’m passionate about the alliance work because that that work is what makes it happen at the corporate level. [00:06:53] James Kang: Cool. Um. I’ll start here. So in Nvidia is a accelerated computing platform company. Um, if you asked. Anyone on the, on the street about a year ago, what is ai? A lot of times they would say AI is, is open ai, or it’s philanthropic. [00:07:12] James Kang: Um, Jensen and I’ll, I’ll reference Jensen a lot today, um, because he is our leader, um, but he also sets the strategy in the direction for Nvidia. He talks a lot about AI in the metaphor of a five layer cake. And in terms of the five layer cake, you start off with the foundational bottom layer being power and energy, which sustains. [00:07:32] James Kang: All of our data centers, you move up the stack in terms of chips. So things think of Foxconn, think of TSMC. Next you have the infrastructure layer. So obvious choice is AWS, and then you get to the models where you do have the philanthropics and the open ais. But finally in at the precipice, you have the application layer. [00:07:53] James Kang: Ultimately, the reason why I mentioned all different stacks of the layers, the five layer cake, is the fact that the application layer is the most important. And so when you think about. Partners like Elastic or ServiceNow Trend, ai, CrowdStrike. Every time you pull from the application layer and you see a success, it pulls all five different components of that layer up. [00:08:13] James Kang: And so ultimately, as I think about success, it’s it’s being able to develop these co-sell wins at the application layer and really demonstrating that through extreme co-engineering and co-design with all the different application. Infrastructure, power and energy layers in mind. Um, Jensen also likes to think of himself not only as the CEO and founder, but also as the, the chief Marketing Officer. [00:08:35] James Kang: We are a very event driven company, and so at our big events like GTC or at big industry events like CES or Computex, he likes to show up on the biggest stage, biggest stages and showcase the partnerships with not only ISVs and GSIs, but also with end customers. And so that’s what I think about when I think of SA success. [00:08:56] Vince Menzione: That’s a really good point. You talked about, Allison, you talked about having an alliance strategy, or at least you teed it up, so I thought maybe we would go there for a second. Right? Like, what does a great alliance strategy look like and why is it important to the success of the partnership? [00:09:11] Allison McFadden: Man, I, uh, I have so many opinions on this. [00:09:13] Allison McFadden: We could probably be up here all day. That’s [00:09:15] Vince Menzione: okay. [00:09:16] Allison McFadden: Um, no, I think. Uh, there, there are a couple things, and the first one that comes to mind is focus. We cannot be all things to all people. Um, so when it comes to think about some of the, the work we’re doing with Elastic, we have a very, very clear point of view on what client problem we’re solving, what clients we want to talk to. [00:09:38] Allison McFadden: It helps if, um, from an ISV perspective, if there’s a very clear fit in. The Accenture portfolio or whatever, you know, SI consulting partner. You’re working with a very clear fit in the portfolio and we know what we’re not gonna go after, what we’re not gonna spend our time on because we have, we have this tendency, there’s millions of people. [00:10:00] Allison McFadden: The ecosystem chart that, you know, Vince, you showed up there, there’s so many connections. There’s probably more connections there than there are atoms in the universe, right? So, um. Defining what we do together and what we don’t do together is the first thing that pops to my mind. [00:10:19] Vince Menzione: Reka, do you have a perspective on it since we’re gonna, we’re gonna talk next about what you’ve done together, but, and I also wanna get mass perspective as a hyperscaler partner here as well. [00:10:29] Rekha Thangellapalli: Yeah, I mean from my perspective, I, I’m gonna, you know, kinda echo what Allison said is to be just maniacally focused. Yep. Um, because, especially from my perspective, so Elastic has three different solutions, right? We’ve got search, we’ve got observability, we’ve got security that map to completely different business units within Accenture. [00:10:47] Rekha Thangellapalli: And of course Accenture does a lot of things. And so, you know, when we first came together it was like. Okay, what are we gonna focus on? What industries are we gonna go after? Which segments are we gonna go after? Which customers, you know, um, outcomes are we trying to solve? And I think that sort of maniacal focus is the number one contributing factor to, to the fact that I’m like, up here on stage today. [00:11:12] Rekha Thangellapalli: Great. [00:11:14] Vince Menzione: Matt? Perspective? [00:11:16] Matt Yanchyshyn: Yeah, I, I, I guess I was trying to. To add something, uh, additional from an AWS perspective, uh, when it comes to, you know, what does a great alliance look like? Uh, AWS is obsessed with data, you know, in data we trust. And, and so the best, um, and, and this goes sales business problem, and it’s not just the engineering teams. [00:11:34] Matt Yanchyshyn: And so, uh, you know, Accenture does a good job of this elastic, definitely. And if you can come to the table with, um, quantifiable proof of the value of customer outcomes and partnerships. Um, you’ll win all the time and it’ll be a durable relationship with AWS ’cause we really are this data obsessed company and, and even the most senior sales leaders. [00:11:54] Matt Yanchyshyn: Uh, and so what I mean by that specifically is like if you, if you can show like your a RR to land an a RR conversion ratio, like in in numerical format, it’ll light up our sales leaders and, and they’ll be all, and they will co-sell with you all day long. If you can show the, I mentioned this earlier, like the AWS service, uh, whether you’re consulting company or, um, elastic and, and how the shape of customer accounts change positively when we work together. [00:12:15] Matt Yanchyshyn: That type of sort of quantifiable data works particularly well from an alliance perspective. With AWS as a partner, we, we really are like this data in sort of results out company. Um, so I, yeah, that’s just adding to the great points that were already made. I would say specific to AWS that that’s key. [00:12:30] Matt Yanchyshyn: Yeah. And I’m gonna bring up one more thing. I want to dive in on the, the joint value proposition, but you mentioned something that made a lot of sense and resonated to me about the organizations once you get out of partner, the partner world that we all know and love. Mm-hmm. Once you get down into a field organization or account management organization. [00:12:49] Matt Yanchyshyn: Not as much understanding and really organizations do a bad job here, honestly, in terms of enabling the field organizations. Do you agree? [00:12:58] Allison McFadden: I agree because I, I agree. And, um, you know, I think that’s one of the things, and, and I, I, when I joined Accenture, what we had was a lot of wicked smart architects delivering programs to clients in the field. [00:13:15] Allison McFadden: Very smart, very deep in AWS knowledge. Um, and that was awesome for the 10 clients they were staffed on and to get that understanding of how AWS works and I dream about lar, right? Like, this is a good, you know, but that takes real effort and real work. Yeah. And it’s, it’s um, almost like being a language translator. [00:13:37] Allison McFadden: Yes. For me. Yeah. So, you know, I had to deeply learn AWS so that I could. [00:13:42] Rekha Thangellapalli: Sure. [00:13:42] Allison McFadden: Teach my account teams. My account teams are really smart. They know who they’re selling to. They know their customers. They know what their customers need. They do not know what AWS has to offer always because they’ve got 20 partners lining up to try to tell their stories. [00:13:57] Allison McFadden: Um, they don’t know how to ask of the AWS team or the elastic team or the Nvidia team. Yeah. What they need [00:14:02] Vince Menzione: this co-selling piece. Yeah. [00:14:04] Allison McFadden: And so that is where, um. We had to build that muscle even around our AWS practice, which was a huge practice at Accenture, but we didn’t necessarily surround it with that kind of enablement and um, almost deal coaching layer. [00:14:21] Vince Menzione: So Elastic and Accenture came together. I dunno which one of you wants to lead this part of the conversation, but you will, right? Yeah. So tell us about the genesis of this and why. And a lot of people dunno what Elastic does, but you do some really incredible work. Like I, somebody told me one day was like, oh, you know, Uber, like, that’s elastic, powering all that. [00:14:41] Vince Menzione: Like, we don’t think about that. That the engines that you have and the, the backend to the customers, huge customers. [00:14:48] Rekha Thangellapalli: Yeah, absolutely. Um, so when AWS launched this feature last, um, reinvent where basically it allowed, you know, channel partners such as Accenture to be able to bundle up their services, their data assets with an ISV solution and put it on marketplace, um, you know, Accenture and Elastic immediately saw an opportunity. [00:15:09] Rekha Thangellapalli: Um, at the time most customers were doing gen ai. But they were running into the same challenge, which was that their data just was not ready. And by the way, this is a problem we were solving. Outside of marketplace. I think the, the feature that you guys launched just gave us a way to package it up and to be able to create this repeatable solution, which we call data readiness engine for gen ai and put it on marketplace. [00:15:40] Rekha Thangellapalli: And, um, this to me was a success because. Each company had a clear reason to invest. Um, so for Accenture, they were able to, you know, create a very differentiated services led offering. Uh, for Elastic, we were able to expand on our AI story. And for AWS, um, you know, it drives marketplace adoption, increases cloud consumption, all of that great stuff. [00:16:07] Rekha Thangellapalli: And customers, of course get. A solution to a very real problem that, that they were having. Um, and you know, the surprising part for me going through that journey was that, um. The pitching, the idea, getting the budget, getting the executive sponsorship was actually the easy part. The hard part was getting all three companies to come together, uh, to go from idea to launch in a very ambitious timeline of six weeks. [00:16:37] Rekha Thangellapalli: Nice. And so, you know, this was very much like. Doesn’t matter your title. We’re rolling up our sleeves and we are on this outcome together. Um, and so we literally built a RACI matrix, a project plan, and you know, we had daily standup calls for six weeks where literally. At least one person from each three of these companies called in, you know, got rid of any blockers and we made sure we were on target for that timeline. [00:17:07] Rekha Thangellapalli: Um, and you know, at the end we had a successful launch. But I think my favorite part about the story is the impact that we’re having and, um. My favorite story comes from a global pharmaceutical company that, you know, had basically nine petabytes of data spread across six different continents. Wow. And by working with Accenture and Elastic, they were able to build that trusted foundation that their AI and their agents can, you know, kind of safely tap into and be accessible at scale. [00:17:41] Rekha Thangellapalli: Um, so that’s my version. Allison. [00:17:44] Allison McFadden: Yeah. Well, I don’t have a lot to add. I just, I would say this is a good example of a couple of principles, right? One is having a forcing function is never a bad idea. Sign up for a big event, sign up. I’m like, I’m here with my, you know, Nvidia guys saying, sign up for the event. [00:17:58] Allison McFadden: It’ll make you move quick, right? [00:18:00] Audience Member: Yes. [00:18:00] Allison McFadden: Um, so that is one, but two, one of my mentors once told me, when you’re designing any kind of, you know, offering go to market motion, it has to get blood to all organs. If it does not get blood to all organs, it does not go [00:18:14] Vince Menzione: nice. [00:18:14] Allison McFadden: Um, [00:18:14] Vince Menzione: I love that analogy. [00:18:15] Allison McFadden: Oh, I love it. And I can talk all day. [00:18:17] Allison McFadden: That guy was brilliant. I love him. But, um, no, and, and so Elastic did a really nice job of bringing the tech to the table. Um, our team has to trust in that technology and its ability to scale, right? Um, because at Accenture we have to be able to deploy across 700,000 consultants. Um. And yeah, so I think those are the two, two things that really worked well here is we had, uh, trust in the technology solved a customer need. [00:18:50] Allison McFadden: Um, it drives, we don’t even talk about, like, yes, it drives marketplace revenue, but it unlocks work that we do that drives even more revenue to our AWS Friends. Right. So this is a, this is a, um, product that’s getting your data ready for AG agentic. It’s a messy problem that everyone’s dealing with, and it removes blockers for clients and it unlocks more, you know, ag agentic work on top of that. [00:19:15] Allison McFadden: So, blood to all organs. [00:19:17] Vince Menzione: So, was that the proposal going forward to say we need to have, we need to have trust in the solution. We need to drive significant revenue. It needs to be something all of our, you know, seven, 700,000 people. Can be a part of and help drive? Is that how you think about? [00:19:32] Allison McFadden: Yeah, and for us right now, um, it’s an interesting time for Accenture. [00:19:36] Allison McFadden: Our clients are asking a lot of us, and what it does is it having some of these accelerators helps us deliver cheaper, better, faster to our clients, which is what they’re demanding of us right now. Um, so it’s an accelerator to client outcomes. [00:19:55] Vince Menzione: James, what is NVIDIA’s role and how do, how do you enter the equation here? [00:20:00] James Kang: Yeah, it’s, um, it’s a good question. Um, I, I would say that Nvidia is probably one of the most misunderstood organizations in the world. Um, despite the, uh, the market capitalization in the valuation of the company, we have a very tiny organization. Um, what I mean by that is, um, if you think about. [00:20:20] James Kang: Salesforces and field sales organizations. Um, we’ll take Salesforce as the account or the customer. As an example, we have one account manager at NVIDIA that no, not only covers and is responsible for the relationship with Salesforce, um, but also manages. Automation Anywhere as well as DocuSign. Whereas at AWS, in contrast, like there are full armies and teams Yeah. [00:20:45] James Kang: That are supporting the Salesforce relationship. And so as you think about partnering and working with Nvidia, the focus has to be on really. Extreme co-design, but also being very prescriptive in terms of what are the very specific customer outcomes that we are solving for. And the guidance that I would give is bring in Nvidia into that equation and that conversation as early as possible because that [00:21:10] James Kang: co-engineering and co-design needs to be part of the foundational building blocks in order for you to come out with a end solution that checks all those different requirements. [00:21:20] James Kang: And so I think. Again, like going back to Nvidia, um, we like to talk about two different types of brains. A brain one and a brain two. Uh, brain One you think about the next quarter and making sure that you’re hitting the revenue targets for the next quarter. Brain two, you think about a long-term goals and potentials looking around corners and being very strategic. [00:21:41] James Kang: The saying internally is without Brain one, there is no oxygen, but without brain two, there is no future. And everyone at NVIDIA is trained to think in that brain two mentality. [00:21:52] Vince Menzione: Wow, Matt. [00:21:54] Matt Yanchyshyn: Yeah, I, I was just thinking I love the blood doll organs. Uh, and so just on, on that note, um, and, and, you know, the multi-product solutions that, that you, you built together, uh, that is a really good example of blood do organs because like we all know, that’s how customers buy. [00:22:07] Matt Yanchyshyn: They, they buy solutions and increasingly they’re looking for combinations of ISV, sometimes multiple products from multiple ISVs with services. Uh, often they’re buying it through a resell motion. You know, and they, and, and so that from a customer perspective, they want a single place to go. And so that’s the multi-product solution. [00:22:24] Matt Yanchyshyn: They wanna find everything they need, they need Accenture, they need Elastic to solve a specific solution. And I think where that’s headed is even more specific listings, like with AI powered listing experience, like, you know, elastic Plus Accenture for, I’ll make something up like a manufacturing workload. [00:22:37] Matt Yanchyshyn: And so this solution based. Uh, sort of buying is, is very customer centric. It’s what customers want. We all know that. But that’s, that’s the customer sort of organ, I guess. Um, but then, you know, you all have SCAs and those SCAs have marketplace commits. It helps if that gets transacted through marketplace helps the AWS relationship, you know that that’s an organ. [00:22:55] Matt Yanchyshyn: It’s the relationship. It’s, it’s the commercial construct and that you have, uh, that that’s another organ. You’re marketing people. They, that’s another organ. They don’t wanna land, uh, leads on a static marketing page. They wanna land a lead on a, a storefront with a multi-product solution that can actually convert and that you can actually buy it through that. [00:23:12] Matt Yanchyshyn: So the marketing person’s happy because they, they have less churn. Uh, and then, you know, our reps are happy ’cause guess how they get paid? They retire quota when they sell Marketplace. And they, we also, Jay McMain will tell you, that’s another organ called Jay or on, on you now. Um, [00:23:27] Matt Yanchyshyn: he’ll like that. I’ll call him up and tell him that. [00:23:29] Matt Yanchyshyn: Yeah, [00:23:30] Matt Yanchyshyn: but he, he’ll tell you, you know, don’t believe me. Obviously, never believe Matt, believe, believe the, the data and, and his data shows that. Those deals will close faster and larger if you use marketplace. So that’s, that’s a lot of organs. That’s the whole body. Um, but you know, when you have your customer happy ’cause that’s how they wanna buy your field happy. [00:23:45] Matt Yanchyshyn: Um, and, you know, the relationship happy and you know, your marketing team happy. Uh, and, and Jay happy. Um, and, and you know, I think that multi-product construct and, and the way you kind of use it to model a partnership and the way buyers ultimately wanna buy is, is really powerful. And so I, I think it’s, you know, it’s really a manifestation of how. [00:24:04] Matt Yanchyshyn: We kind of intend and to go to market anyway. Uh, so I think, you know, and thanks for leading the way, by the way. You’re, you’re amongst the very first, so that’s great to see. [00:24:11] Matt Yanchyshyn: So these storefronts are really helping this drive, drive this. Well, [00:24:13] Matt Yanchyshyn: that’s the next evolution. Like we’re talking about the multiproduct solution. [00:24:16] Allison McFadden: I’m JJ Accenture storefront. [00:24:17] Vince Menzione: Yeah. Oh, there you go. I mean, j and j Accenture storefront. [00:24:20] Allison McFadden: We’re gonna talk about that. [00:24:20] Matt Yanchyshyn: Yeah. I mean, [00:24:21] Matt Yanchyshyn: Accenture also leading the way yet again with storefronts. And so I think the combination of. You know, again, I was talking a lot about conversion. Yeah. And you know, buyers know sometimes they know what they wanna buy and, but if you really wanna convert that lead, you wanna land them again, something that combines, you know, elastic Accenture’s services plus software, but in a storefront that is, you know, surrounding with just the solutions they want so they don’t need to kind of go searching. [00:24:42] Matt Yanchyshyn: So, you know, ultimately reducing that time to close, I guess, really ’cause meeting the customer where they are with what they need. [00:24:51] Matt Yanchyshyn: So we talk about co-selling a little bit. We, Jay and I talk about this all the time. We gotta keep looping Jay in here, even though he is not even in town this week, but Reko, um, what does co-sell look like inside Elastic? [00:25:02] Matt Yanchyshyn: You’ve got, we talked about an incredible leadership team. I’ve gotten meet some of your leaders. Seems like you drive, you do a good job internally driving that. Let’s talk a little bit about it. [00:25:11] Rekha Thangellapalli: Yeah, and this is something I’m, I’m personally very passionate about. Um, co-sell is. Very much a journey, not a destination. [00:25:20] Rekha Thangellapalli: And I think step one for us is recognizing the different partner types that we have. Because at Elastic we work with, you know, OEMs, MSPs, resale distributors, GSIs, um, and they all bring something very unique. To the customer lifecycle and they all contribute very differently within, you know, our own sales cycle and sales process. [00:25:45] Rekha Thangellapalli: And so, you know, figuring out what is the unique benefit they bring, how do we enable them? So training and enablement is a huge piece of it, and so is making sure we’ve got the right metrics to measure success. Um, I know a lot of companies look at partner sourced as the north star, and that’s great, right? [00:26:06] Rekha Thangellapalli: Because that is undeniable. You can say, Hey, that would not exist if it wasn’t for my partner team. Um, but we’ve also noticed that when we bring in GSIs, it actually increases renewal rates. It significantly increases. Um, a RR over time. Um, it expands deal sizes and so these are very real metrics that we can point to, um, beyond just the co-sell and the partner sourced number. [00:26:32] Rekha Thangellapalli: Um, so for us it’s looking at it from a very holistic perspective, but also catering it towards that unique partner and making sure we’re doing everything we can to set them up for success and setting up the partnership for success. [00:26:47] Vince Menzione: So clo close win ratios, deal size and renewal rates? [00:26:52] Rekha Thangellapalli: Yes. For specifically for geos size. [00:26:54] Rekha Thangellapalli: Yeah. [00:26:55] Vince Menzione: Very interesting. Allison, uh, what had to change internally to produce these co-selling? We talked a little bit about the field organization and enabling a, a group of, and, you know, account sellers that are very customer focused and enabling them on the co-sell side. What had to change internally to drive that? [00:27:13] Vince Menzione: Yeah. [00:27:14] Allison McFadden: I, I might have already alluded to this a little bit in a previous answer, but, um, creating the capacity to develop, build, and sell these solutions, um, inside of a large GSI, where billable hours is kind of the number one metric on the table. Um. Is part of the investment that we had to make within Accenture to get this done? [00:27:36] Audience Member: Yeah, [00:27:36] Allison McFadden: so expert technology time. So we have technologists that understand the elastic technology. We do similar with Nvidia, by the way, we. We released some of their time to go co-develop the solution because it has to hold technical water, right? It can’t just be a marketing pitch. It can’t just be, it has to be a real, um, what’s the there, there. [00:27:59] Allison McFadden: So in order to actually do proper co-sell, we had to release some of that time. Um, to invest in those partnerships. Um, we’ve also done similar with some industry aligned business development leaders recently, so we have freed their time up to go. Uh. Open new conversations, educate client, account teams, go to clients, have conversations. [00:28:26] Allison McFadden: Um, so that, that’s a new motion that we, uh, have just kind of recently made, um, to allow them, I love this brain one, brain two also, right? So to allow them to focus on brain two, because a lot of our time. Typically spent delivery issues, you know, getting my hours, where am I charging my time? And so just freeing up a little of that capacity to do this work, um, helps get us in this brain two mode where we’re not just living to survive. [00:28:56] Vince Menzione: I. So, Matt, you’ve removed a lot. I mean, one of the things I admire, I admire AWS for being first to market and removing the most friction in marketplace of any of the vendors. Really, truly that. You talked about some of the announcements. How does some of, how does some of this tie PC central agents propensity sales plays, MCP, how does some of this tie to how, how you’re thinking about the future? [00:29:18] Vince Menzione: And how to enable more motions like this. [00:29:20] Matt Yanchyshyn: Yeah. Well, I, I think if you know my boss, UBA Borno, uh, you’ll know that she has a maniacal focus on automation. Yeah. Um, and, uh, co-sell is increasingly automated. You know, you were asking earlier about propensity data. You can get that propensity data in addition to sales plays and, uh, opportunity scores through the partner central agents. [00:29:38] Matt Yanchyshyn: So things that used to require multiple calls to A PDM, if you’re lucky to have one. Yeah. Or a p sm. Uh, you, you can now get through, through these agents, you know, uh, tech Systems, TGS, they, they manage what, over 5,500 customer opportunities with agents that they built on top of our partner Central APIs. [00:29:55] Matt Yanchyshyn: Um, and work Span has built a whole product and business that’s right on leveraging, uh, our APIs, our capabilities to sort of tie into your CRM. So, majority of all opportunities will be progressed and managed by agents. This year at AWS, we already have a majority of all customer opportunities, all app have a partner attached and I, I took a personal goal for a majority of those partner attachments, not to happen from a human. [00:30:22] Matt Yanchyshyn: But from our solution matching engine. And how do you get recommended by that solution? Matching engine, having a healthy ACE pipeline, thanks to partner central agents and the integrations you’re doing. And in addition to being the specializations and doing things like multi-product solutions and ultimately closing opportunities, you dream of LAR and so LAR will help that. [00:30:40] Allison McFadden: It’s more like a nightmare. [00:30:41] Vince Menzione: And so, you know, [00:30:42] Allison McFadden: it’s more like a nightmare, but [00:30:44] Vince Menzione: nightmare. Well, it’s, it’s, yeah. Nightmare of Laura and, and. Nice dreams of PRM, but the, um, but that’s the loop, right? I, I think, uh, increasingly co-sell for us, and in my mind, is largely a hundred percent automated. Yeah. Except for what matters most, those most largest, most strategic, most complex deals. [00:31:01] Vince Menzione: Where our highly paid and very skilled salespeople are most effectively used. [00:31:05] Vince Menzione: Yeah. [00:31:05] Vince Menzione: You know, the days of, you know, this person with 20 years experience selling, clicking, progressing opportunities through a pipeline, uh, should be over. Uh, and, and we need those people out, out selling and, and co-selling. And so that for me. [00:31:19] Vince Menzione: Yeah. That, you know, we talk a lot about co-sell, but I, I’m obsessed with automating as much of the co-sell as possible. [00:31:24] Vince Menzione: I remember going back to the ex Excel spreadsheets and, and that, that seems to be be Viva became spreadsheet jockeys. [00:31:31] Vince Menzione: Yeah. [00:31:32] Vince Menzione: And, and they stopped selling. They forgot how to sell. [00:31:34] Vince Menzione: Yeah. And people spend all this time doing lunch and learns and things like that. [00:31:36] Vince Menzione: And then, you know. Then the salespeople rotate out after 18 months and, and it, that’s, that’s the old days. Uh, you know, the new days are, are AI powered matching algorithms, uh, ag agentic co-sell, using the partner essential agents to get your data and, and putting that data to use automatically and, and what sounded like magic. [00:31:51] Vince Menzione: 12 months ago is being done, you know, by partners at massive scale across thousands of opportunities. You can do it today. And you know, I, there’s a guy named another Mike, right? Mike another Mike who they have, there’s like a guy who’s doing all this and I’m picking on Mike ’cause I, I know their system really well and I know the guy Mike grew easily built it for them. [00:32:08] Vince Menzione: Um, but, you know, I think, yeah, again, in the days of having 10 people sort of doing lunch and learn could be replaced by one or two people, building agents, uh, managing a massive pipeline. And, and that’s the future. [00:32:18] Vince Menzione: Exactly. James, your perspective on what breaks with co-selling? [00:32:22] James Kang: Oh, what breaks co-sell? Um, I would say. [00:32:25] James Kang: It, it starts and finishes with just misalignment and a loss of trust with the customer, especially when you have multiple partners or stakeholders involved. If you’re trying to do a three-way deal with a end customer and you’re not on the same page, you’re not gonna get to a successful outcome on, on the backend. [00:32:44] James Kang: Uh, the fix is a much more complicated story. I would say that to take a step back, um. We’ve talked about the five layer cake. We’ve talked about where NVIDIA kind of fits within the equation. We are invested in the ecosystem and so as different players and application organizations win and see these outcomes for end customers, we celebrate that success. [00:33:07] James Kang: Um, and as part of that kind of ethos of where NVIDIA fits within the ecosystem, we wanna make sure that not only. Our customers, but our partners like ISVs and GSIs are set up for success. Um, we do not as Nvidia sell hardware or GPUs directly to customers We use. Hyperscalers like AWS as kind of our force multiplier. [00:33:31] James Kang: And similarly we think of ISVs and GSIs as the force multipliers in terms of our extensions of how we, we kind of leverage the relationships and build the trust with our end customers. And so going back to kind of the question, Vince, I would say that it all comes back to trust and being able to build that mutual trust. [00:33:48] James Kang: Um, a lot of what we do when we co-sell with AWS is really on the software layer. Um, we actually have more software engineers at NVIDIA than we have hardware engineers, which is a weird thing to say, um, because everyone knows us for our GPUs. But because of that fact, we are heavily invested in Cuda and making sure that Cuda becomes the foundational layer for how not only our ISVs and GSIs, but also our end customers are building. [00:34:12] Vince Menzione: Very cool. So Reiki, you and James together on this production. Versus pilot with the Gentech ai. Tell us a little bit more about that. Where, where are you in the process? [00:34:24] Rekha Thangellapalli: Yeah. So I mean, in general, what we’re seeing out in the market in, in relation to sort of AI and, and customer’s journeys is that, um, at least from an elastic perspective, um, we’re seeing people very much in production when it comes to, you know, kind of AI assistant co-pilot use cases. [00:34:42] Rekha Thangellapalli: So, you know, things like, um, software development, customer support is a big one. Um, any sort of employee productivity use cases where there’s. Still a human in the loop somewhere. Um, and there’s a very like, clear path to value. And so we see the customers being in production excelling there. Um, no problem. [00:35:01] Rekha Thangellapalli: Where we’re seeing people still kind of in the pilot phase is those fully autonomous workflows where there is no human involved. The agent is reasoning on its own. Um, accessing multiple systems and taking an action on the user’s behalf. And what we’re seeing is that it’s not the intelligence of the agent that’s holding it back. [00:35:26] Rekha Thangellapalli: It’s more about giving the right context to the agent and having the right. Security kind of governance controls in place for the company to feel comfortable in putting these fully autonomous workflows into production. And that’s really the conversation we’re having is all right, what are the controls you need in place? [00:35:47] Rekha Thangellapalli: For you to release this to your business unit. Um, and what is the context that the agent is needed before we can comfortably let the agent make the decision on the user’s behalf? Um, James, I’d be interested to hear what you’re, what you’re seeing in the market [00:36:03] James Kang: plus one on all things context. I, I would even go so far as to say, um. [00:36:09] James Kang: H how many folks in the audience have heard of token maxing? Like this new term? [00:36:13] Rekha Thangellapalli: Yeah. Yeah. [00:36:14] James Kang: Um, I’ll, I’ll give a very specific example of, of Uber that went public. With the example of Claude, like they allowed all of their employees to use as many tokens as possible, and within the span of four months, they exhausted their full budget for the year, and so they had to pull back, and now there’s a cap on every employee. [00:36:33] James Kang: I think the number that’s circulating is $1,500 per month per employee, and so I think that is at least. In this multi-phase evolution of where we’re going to be and where we’re today, cost has become kind of the prohibitive force in terms of agentic AI at scale. Um, I think we are working on some very creative solutions in-house and Nvidia. [00:36:55] James Kang: Um. And we saw some really dynamic announcements this week when it comes to all things agent core, um, where we want to focus on very nimble ways for customers to be able to execute and go to market. And one extreme example of that is our investment within our open model strategy. So Nvidia, not only, again, providing GPUs, we actually offer our own op open models, which we call our Nitron models. [00:37:21] James Kang: And through our Nitron models, we are allowing customers to really develop and fine tune their own proprietary models in a cost effective manner. So right alongside the frontier models like OpenAI and Anthropic. It’s not a if then, it’s not an either or statement. It’s a, it’s a permutation, it’s an and So we’re giving you a cost effective alternative to not only bring your AgTech applications at scale by training on Nibo tron, which is open source, but then once you’ve kind of finished and fine tuned that specific training job to be able to. [00:37:53] James Kang: Go ahead and utilize your frontier models, whether it be OpenAI or Claude. And I know there’s other partners here that are providing those kind of different model capabilities. And so I think for us it’s, it’s a matter of choice. We know that this market is dynamic. It’s gonna be evolving over the next coming months as well as the next coming years. [00:38:10] James Kang: Uh, but we believe that we are positioned for a really unique dynamic expansion of AgTech use cases over the, at least the next three to six months. [00:38:20] Vince Menzione: Allison, for the partners in the room who are glazed over right now going, what do I, what do I do over the next 12 months? [00:38:26] Allison McFadden: Should I wake everybody up by saying, yeah, please. [00:38:27] Allison McFadden: Say go hurricanes. [00:38:28] Vince Menzione: Yes. [00:38:29] Allison McFadden: Is there anyone, anybody? Everyone’s like, boo. I get to leave the parade today to go home to parade. I live in Raleigh, so we’ve got our parade on Saturday. Nice. [00:38:39] Vince Menzione: Nice. [00:38:40] Allison McFadden: All right. Wake up. Um, all right. So for the $50 million partners in the room, um. $50 million is not small. You have something that works. [00:38:50] Allison McFadden: Right. This is great. What I would be thinking about is, you know, we’ve talked about focus before, but really doubling down on, you know, what is, what is your industry, what is your client like, ideal client that you serve. And build, um, almost that kind of community. You know, the, the clients we have move from firm to firm to firm. [00:39:17] Allison McFadden: And if you’ve done good work at one, you’re gonna follow ’em to the next. Um, so build that client demand in a specific place or specific client profile that is just like really knocking it out out of the park for you. Um. Scale with marketplace, right? So if you, I, I love some of the data that you were sharing in your talk earlier, um, because it’s like no overhead scaling mechanism. [00:39:45] Allison McFadden: I mean, it’s, it’s fantastic. Um, Accenture, other GSIs like us, we are investing in marketplace. So we’re investing in resources, um, to help us. Use marketplace more with our clients and we’re gonna capture, right, those storefronts. And if you’re present on marketplace, you’re gonna be able to catch, uh, yourself in that wheel. [00:40:09] Allison McFadden: So I think those are the, the kind of couple of things I would say is focus, focus, focus to drive that client demand and use scaling mechanisms like marketplace to really kind of, uh, accelerate. [00:40:24] Vince Menzione: Matt, anything to add there on the. [00:40:26] Vince Menzione: Well just, you know, Ja, James, you, I love the token maxing reference in Uber and it reminds me, you remember when cloud came out and everyone was like, oh, all these people are, are gonna use the cloud and costs are outta control and. [00:40:39] Vince Menzione: Um, a lot of people pulled back from the cloud and, and a lot of those companies no longer exist. And it’s similar with, with, uh, token maxing, like, oh, these agents are outta control. You have a choice. You can embrace them and figure it out and get governance and, and make your data available. Um, use the partner, central agent, move to agent to co-sell, or you can fade and die. [00:40:58] Vince Menzione: And, and that’s, that’s where we’re at. Uh, is, is the, the companies sitting here today embraced the cloud years ago and won. Uh, and and there’s a set of companies here today who are gonna embrace agents in the, for both buyers and sellers, and will win. And there are those who won’t and they won’t win. And so for me, it’s like we’re, we’re at a, we’re at a crossroads. [00:41:18] Vince Menzione: And, and if you’re gonna win, you gotta leap into that, you know? I love it. And, uh, and, and, and it’s, it means the cost of experimentation is so much lower now. Development and, and even business development or software development is, is agent enabled. And so you can take risks, you can experiment and, and you have to, it’s, it’s an existential moment. [00:41:37] Vince Menzione: Agreed. We’ve got a couple minutes left over for any questions. What do you think? Sure. Are there any here. I think there are a couple. Yeah, we’ve got, we’ve got a co-sell question I’m sure coming up here. [00:41:51] Audience Member: Um, I’m Cassandra, I’m the CEO of Partner Tap. And one of the questions I had was, I think, you know, the co-selling between the sellers is where things get. Really, really hard when you’re multi-partner. And so when I was listening, um, with, you know, the Accenture and Elastic together, you talked about how you had, you, you had to get these BD business development people. [00:42:22] Audience Member: Um, is this a new team that is over the client team? And how do these teams interact like with the elastic sellers? Are you doing a lot of coaching to the field and then with if AWS sellers are, are involved, like what is that whole picture? What does look like, [00:42:43] Allison McFadden: like [00:42:44] Audience Member: on the ground? I mean, that is the hardest part, I think, and that’s what we hear. [00:42:48] Allison McFadden: It’s so, it’s so, it’s so tough. Um, and I will, I’ll just say, so our business development leaders that we now have kind of. Expanded their capacity. They have always been, they have always been there. Um, but they have not been well resourced. They haven’t, they haven’t had very clear kind of job description. [00:43:12] Allison McFadden: I’m gonna say I, in the past they have been kind of focused on partner relationship. And so like more like an alliance manager and maybe working on some of the data. Right? So when I say I have nightmares about Lars, because we’re always trying to increase the LAR for Accenture and, and they were focused like in those detailed weeds of like trying to pass ACE and trying to call the PDM and all this stuff. [00:43:39] Allison McFadden: What we are doing is really pivoting them to be proper sales, business development focused on client outcomes and focused on. Technical skills to be able to describe what this solution is to the field. So, um, and because we need, I have many, many questions about, I gotta get agents to work with Eurogen co-sell so that that part somehow goes away. [00:44:05] Allison McFadden: So that’s a, that’s the thing we gotta solve still, but, um, so we’re pivoting them to be kind of driving. More of that co-sell enablement with the field, um, and taking that message to the field rather than being there, waiting for questions to come in from the field, waiting for like our field teams to discover, oh, I saw something that we’re doing with Elastic, like on a press release on LinkedIn. [00:44:30] Allison McFadden: Right. So we’re kind of trying to pivot them to be more proactive. [00:44:33] Vince Menzione: Very cool. [00:44:34] Rekha Thangellapalli: Yeah. And uh, Cassandra, that’s an excellent question because I think. Multi-party, you know, sort of tri-party offerings. The hardest part is operationalizing it at scale, right? Yeah. And so for this particular offering, we are basically having three routes to market. [00:44:51] Rekha Thangellapalli: So one is seeing how this offering fits into our existing elastic go to market. And so I am constantly enabling our field sellers to say, okay, within our three field sales place, here’s exactly where this fits in. Here are, you know, uh. Keywords that you hear in customer conversations where you bring up this offering and here’s a process of how it works. [00:45:14] Rekha Thangellapalli: Um, exactly At what sales stage do I bring in Accenture, how, you know, what are the roles and expectations? Right? So that’s on the elastic side. We’re doing the same thing on the Accenture side. So we’re doing a ton of training enablement and lunch and learns, and we’re also looking at how do we fit into. [00:45:31] Rekha Thangellapalli: Uh, Accenture’s AI transformation projects, we are the semantic layer, right, of their enterprise brain. And so it’s a whole different sales motion, um, and, you know, having the right assets, having the right process again to make sure that that goes smoothly. And then finally, we’re going directly to the customer. [00:45:49] Rekha Thangellapalli: So we are launching multiple external campaigns where, you know, if the customer raises their hand. We will, we will line up immediately. Right. Um, and so, [00:46:01] Allison McFadden: I mean, I can’t, I can’t, I can’t say how important that third leg of the stool is. ’cause the second part, she talked about getting into our catalog is the first thing. [00:46:09] Allison McFadden: ’cause my BU business development leaders have the catalog. Right. And that’s what they’re selling. So what Elastic has done has gotten into one of those offerings and then. If we have a customer that asks for it, that is the fastest way to alignment. That is like the number one thing that we respond to [00:46:26] Vince Menzione: customer at the center. [00:46:27] Vince Menzione: This is great. Well, I think we’re up to time. This was a great session. I want to thank you. This is what a great, what a great group. [00:46:34] Vince Menzione: Thanks for listening to the Ultimate Partner Podcast. If today’s conversation resonated, share it with a partner leader in your network. Subscribe where [00:46:43] Vince Menzione: you listen, and head over to the ultimate partner.com. [00:46:47] Vince Menzione: For show notes related content and the resources for this episode. And if you haven’t already, now’s the time to register for the Ultimate Partner Live Event in Reston, Virginia, October 26th through October 28th. Until next time, keep showing up in the rooms that matter because being in the room changes everything [00:47:09] I.

Technical difficulties bring you the combination of Alec, Bobby Belt, and RJ Choppy for the first hour of the show!

The Award Travel 101 crew kicked off Episode 181 by discussing one of the week's hottest travel deals: Norse Atlantic's $118 one-way fare from Orlando to London Gatwick. While the price grabbed plenty of attention, the hosts reminded listeners to look beyond the headline fare, noting Norse's low-cost model means extra fees for amenities that many travelers expect. They also covered several major developments in the points and miles world, including American Airlines quietly increasing award prices on certain Japan Airlines partner flights, an enhanced World of Hyatt credit card welcome offer, a wave of valuable Amex Offers for hotels and travel, and Marriott's latest award pricing increase. Angie and Cameron also shared updates on their own points-earning progress and upcoming travel plans, including schedule changes, hotel decisions, and new credit card bonuses.The main discussion centered on whether booking hotels directly with points is still the best strategy as hotel loyalty programs continue to devalue their currencies. Using real-world examples from Marriott, Hilton, and Hyatt, the hosts compared direct award bookings against Chase Travel, Capital One Travel, Citi Travel, and American Express Travel. In many cases, travel portals—especially when paired with annual travel credits, Points Boost, Fine Hotels + Resorts, or The Edit benefits—required significantly fewer transferable points than booking directly, particularly for Marriott and Hilton stays. Hyatt remained the notable exception, where transferring Chase Ultimate Rewards to Hyatt often continued to provide the strongest value. The episode concluded by encouraging listeners to think beyond traditional award bookings, weigh elite benefits and earnings when comparing options, and wrapped up with a practical international travel tip: always pay in the local currency when using a credit card abroad and avoid Euronet ATMs, which typically offer poor exchange rates.Episode Links:American Partner awards increaseHyatt personal card increased offerAmex Hotel OffersMarriott award rates are increasingWhere to Find UsThe Award Travel 101 Facebook Community.To book time with our team, check out Award Travel 1-on-1.You can also email us at 101@award.travelBuy your Award Travel 101 Merch hereReserve tickets to our Late Summer 2026 Meetup in Milwaukee now. award.travel/mke2026Our partner CardPointers helps us get the most from our cards. Signup today at https://cardpointers.com/at101 for a 30% discount on annual and lifetime subscriptions! Lastly, we appreciate your support of the AT101 Podcast/Community when you signup for your next card!Technical note: Some user experience difficulty streaming the podcast while connected to a VPN. If you have difficulty, disconnect from your VPN.  

Our pair of records on the podcast this week tilts towards the Germanic, with Die Krupps' 2013 release The Machinists Of Joy holding up as one of the veterans' strongest efforts upon review, and Oklahoman act Karger Traum's III still shining as an homage to classic NDW experimentation. We're also looking ahead to Terminus next week and playing America's favourite game show, "Giallo or Inkubus Sukkubus?". 

Markets continue to grind higher after breaking out of a multi-week consolidation pattern, with resistance near previous highs still in focus. Technical trends remain constructive as buy signals stay intact and moving averages continue rising, but momentum is becoming increasingly stretched as markets approach overbought territory. The bigger story is happening beneath the surface. Leadership rotated sharply on Wednesday as investors moved back into Mega Cap technology names like Nvidia, Microsoft, and Amazon while semiconductor stocks suffered broad selling pressure despite ASML's earnings. With the semiconductor sector breaking below key technical support, investors should watch closely to see whether this is simply a healthy consolidation or the beginning of a larger topping pattern. Lance Roberts examines the technical outlook for the S&P 500, the developing head-and-shoulders pattern in semiconductor stocks, why the 50- and 100-day moving averages matter, and whether slowing earnings growth expectations could signal a shift in market leadership. We also discuss the potential for a reflex rally in chip stocks and what investors should monitor before making portfolio adjustments. Hosted by RIA Chief Investment Strategist, Lance Roberts, CIO Produced by Brent Clanton, Executive Producer --- Watch the Video version of this report on our YouTube channel: https://youtu.be/9PJPUe3i390 --- Articles mentioned in this report: "Why Are BDCs Ignoring Junk Bonds?" https://realinvestmentadvice.com/resources/blog/why-are-bdcs-ignoring-junk-bonds/ --- Get more info & commentary: https://realinvestmentadvice.com/insights/real-investment-daily/ --- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo --- * REGISTER for our next Candid Coffee, "Narrative Busters: Market Stories Investors Should Approach With Caution," Saturday, July 18, 2026: https://streamyard.com/watch/RfJtCj2byfDr --- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN --- Subscribe to SimpleVisor : https://www.simplevisor.com/register-new --- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #StockMarket #MarketOutlook #SectorRotation #Investing #TechnicalAnalysis

$473 million worth of Bitcoin vanished overnight when Mount Gox collapsed in 2014. I was on that exchange. I lost Dogecoin to a hack on a random platform. I used leverage once and did not sleep properly for three weeks. This episode is the five technical mistakes that cost me real money so they never cost you.In this episode:Why leaving your Bitcoin on an exchange means you do not actually own Bitcoin what Mount Gox taught me the hard way and the twenty minute fix that means nobody can ever take yoursWhy yield scams and guaranteed return platforms have wiped out more Bitcoin wealth than almost anything else what Celsius proved and how to spot the difference between a legitimate product and a Ponzi schemeWhy I tried leverage once, could not sleep for three weeks, and why ten billion dollars of leveraged positions were wiped out in a single day in 2021I built a free calculator that shows exactly what consistent monthly Bitcoin investing could do to your wealth over 5, 10 or 20 years. It's called the Steady Stack Calculator — punch in what you can afford to put in each month and see what the numbers actually look like at the other end. Most people are genuinely surprised. You can also download the 10 Bitcoin Mistakes to Avoid document completely free at the same link.Steady Stack Calculator and 10 Bitcoin Mistakes Document — click here to grab both for freeHit follow, so you never miss the latest insights on money, finance, invest and build wealth - plus clear guidance on cryptocurrency, Bitcoin, and Bit Coin for today's serious investors.

Is mainstream history a record of objective fact, or is it a calculated tool designed to protect the System of White Suprermacy?

Cypherpunk Bitcoin builders Jesse Posner and Erik Cason (author of Crypto Sovereignty) return to Hell Money to talk about their new venture, Vora Aegis — a local-first, privacy-preserving personal AI device built on the same self-custody and cryptographic principles that power Bitcoin.We dig into the growing collision between government power and frontier AI labs like Anthropic and OpenAI, the EU's Chat Control and the US KIDS Act, mandatory digital ID and KYC creep across the internet, and why Big Tech companies like Facebook are quietly lobbying for identity verification. Jesse and Eric break down the security architecture behind sovereign AI — dual-LLM privilege separation, prompt injection defense, OPRF cryptography, formal verification, and Fifth Amendment-resistant key recovery — plus the philosophical stakes of AI, human cognition, surveillance capitalism, decentralization, and digital sovereignty in an era of centralized control.PRE-ORDER THE VORA AEGIS: https://shop.vora.io/products/vora-aegis-vip-depositFOLLOW ERIK & JESSE:https://x.com/Erikcasonhttps://x.com/jesseposnerGet bonus content by subscribing to @hellmoneypod on X: https://x.com/hellmoneypod/creator-subscriptions/subscribeOr support the podcast by sending a BTC donation: bc1qztncp7lmcxdgude4px2vzh72p2yu2aud0eyzys ORDINALS SHIRT: https://shop.inscribing.com/products/ordinals-protocol-shirtTimestamps0:00 Intro4:56 Sovereign AI vs. frontier AI7:43 AI psychosis9:52 Is AI already the new power structure?14:19 EU Chat Control and the US KIDS Act16:05 The Banality of Evil: Facebook and mandatory digital ID23:22 Anonymity, Operation Choke Point 2.030:08 AI telepathic hive mind34:39 Bitcoin self-custody & sovereign AI43:55 Introducing the Vora Aegis48:32 How AI could save decentralization49:47 How Vora Aegis works1:13:04 Technical challenges building sovereign AI1:17:00 Eschatology, sovereignty, and the future of AI1:27:21 The new Gutenberg printing press1:33:19 Non-state actors more powerful than governments1:38:04 Vora Aegis pre-orders and launch timelineTopics: Bitcoin self-custody, cypherpunk ethos, sovereign AI, AI safety politics, Anthropic, OpenAI, surveillance state, digital ID, encryption, privacy, prompt injection, hardware wallets, decentralization, local AI, open weight models, personal data ownership.

Modern farming has seen many changes over the generations. Understanding the latest technology, including biostimulants and biofertilizers, can be powerful tools to maximizing productivity. DunhamTrimmer Chief Technology Officer Vatren Jurin provides thoughtful insight into this subject with The Reckoning, his Substack of scientific writing rooted in practicality in finding positive outcomes for growers.  “Be accountable to what you said to the grower,” he said. “not for one season, but for 35 or 40, because that's the last span of decision making that our clients have.” Jurin said he wants to see more grower input in new product development, better use of updated agronomic tools and more specialists guiding growers.Find out more at https://dunhamtrimmer.com and https://vatrenjurin.substack.com/. 

It's been more than 400 years since she first appeared on stage, and she's still controversial. Margaret of Anjou appears in not one, not two, but four of Shakespeare's plays—Henry VI Parts 1, 2, and 3 as well as Richard III—maturing from a young bride-to-be to a vengeful widow. She also speaks the most lines of any of Shakespeare's female characters. Although her historical counterpart never saw battle, Shakespeare's Margaret leads armies. And while the real Margaret was permanently exiled to France, the Shakespearean version returns to England to confront her old foes. Charles O'Malley and Scott W. Stern, co-authors of Shakespeare's Margaret: The Dramatic Life of a Warrior Queen, share how Margaret exists as an avatar for anxieties about women in power throughout the ages. Shakespeare's depiction may have been influenced by Elizabeth I, but Margaret has been portrayed on stage as a witch, a seductress, an anti-fascist resistance fighter, and even an analogue for Margaret Thatcher. In this episode, O'Malley and Stern shine the spotlight on Shakespeare's most deliciously complex anti-heroine. From the Shakespeare Unlimited podcast. Published July 14, 2026. © Folger Shakespeare Library. All rights reserved. This episode was produced by Matt Frassica. Garland Scott is the executive producer. It was edited by Gail Kern Paster. Technical support was provided by Pat Mesiti-Miller in Oakland and Voice Trax West in Studio City, California. Web production was handled by Megan Fraedrich. Transcripts are edited by Leonor Fernandez. Final mixing services provided by Clean Cuts at Three Seas, Inc.

Did you like the episode? Send me a text and let me know!!No Money, No Problem: The Step-by-Step Framework for Finding a Technical Co-Founder Using ValidationEpisode Summary: You have the idea. You have the drive. You have absolutely zero cash for salaries. So how do you find the brilliant technical partner who can actually build the thing — and convince them to join you? In this episode of Business Conversations with Pi and Piette 2.0, PI and Piette tackle one of the most dangerous and high-stakes challenges in entrepreneurship, driven by a real listener question from tuepodcast.net/askpi.Drawing from Harvard Business School research, Y Combinator strategy, Mike Moyer's Slicing Pie model, Dan Martell's co-founder playbook, and startup employment law, this episode delivers the exact blueprint for building a technical team when cash isn't an option — and reveals why that constraint might actually be your greatest advantage.What You'll Learn:Why 65% of startups die because founders hate each other — not because they ran out of moneyWhy you probably don't need a developer yet — and the no-code trap most founders fall intoHow to build leverage before you pitch anyone using no-code validation toolsWhere to find technical co-founders beyond your immediate networkThe 90-day rule that forces a decision and prevents analysis paralysisHow to vet a developer when you don't know a single line of codeDan Martell's "10-hour weekend test" and what friction response revealsWhy a 50/50 equity split on day one is called the "quick handshake penalty" — and how it kills valuationsHow Mike Moyer's Slicing Pie dynamic equity model works with multipliersThe employment law trap that can destroy your company before it startsWhat a four-year vesting schedule and one-year cliff actually mean — and why they protect everyoneTimestamps:[00:00:00] – Introduction & The Listener Question[00:01:00] – The Harvard Study: 65% of Startups Die Because Founders Hate Each Other[00:02:30] – Why Co-Founded Startups See 163% More Valuation Growth[00:03:30] – Do You Actually Need a Developer Right Now?[00:04:00] – No-Code First: Webflow, Airtable, Bubble — Validate Before You Build[00:04:30] – Dan Martell's Filter: Why Top Developers Ignore Idea Guys[00:05:30] – How to Show Up With Leverage, Not a Pitch[00:06:00] – Where to Find Technical Co-Founders: Start Closer Than You Think[00:06:30] – Michael Seibel's Strategy: Make a Real Offer, Not a Favor[00:07:00] – Friends vs. Strangers: The Surprising Data on Who Makes Better Co-Founders[00:08:30] – Co-Founder Matching Platforms: YC Cofounder Match & Start2Pitch Explained[00:09:30] – The 90-Day Rule: Set a Hard Deadline or Fall Into Analysis Paralysis[00:10:30] – How to Pitch Vision When You Have No Cash[00:11:30] – How to Vet a Developer When You Can't Code[00:12:30] – Dan Martell's 10-Hour Weekend Test & the Friction Response Framework[00:13:30] – The Equity Conversation: Why 50/50 Is a Trap[00:14:30] – Noam Wasserman's Quick Handshake Penalty & Investor Red Flags[00:15:30] – Mike Moyer's Slicing Pie: Dynamic Equity With 1X and 2X Multipliers[00:17:30] – The Employment Law Trap: Can You Legally Pay People Only in Equity?[00:19:00] – Contractors vs. Employees: The Classification That Could Destroy Your Company[00:19:30] – Vesting Schedules & the One-Year Cliff Explained[00:21:00] – The Full Playbook Summary[00:22:00] – The Mind-Bending Final Question: Do You Even Need VC Money?[00:23:00] – Submit Your Question & Wrap-UpPlatforms & Resources Mentioned:

Lindsey Graham is dead, Iran is escalating again, and Washington's war machine is already searching for its next mission. Then a socialist YouTube comment gives us the perfect case against blaming free markets for government-created failures. Nate and Charlie examine Lindsey Graham's interventionist foreign-policy legacy, Donald Trump's account of their final phone call, and the renewed conflict surrounding Iran and the Strait of Hormuz. They also wrestle with the uncomfortable morality of feeling relieved when a powerful politician you strongly opposed is no longer in office. The second half breaks down capitalism, cronyism, housing regulations, healthcare bureaucracy, insurance markets, grocery pricing, monetary policy, and the Federal Reserve. Are Americans suffering from too much free-market capitalism, or from a government-controlled economy that protects incumbents and restricts competition? CHAPTERS 00:00 Technical problems and sad news 01:45 Lindsey Graham's death and an uncomfortable reaction 06:45 Graham's final Ukraine sanctions push 11:45 How do you mourn a political opponent? 15:45 Lindsey Graham's most revealing war clips 20:00 Trump gives Graham a posthumous score 27:30 Iran and the Strait of Hormuz escalate 31:15 A socialist challenges capitalism 34:45 Housing prices, supply, and regulation 38:45 Is American healthcare a free market? 42:15 Grocery pricing and tiny profit margins 54:15 Inequality, technology, and capitalism's record LINKS Watch All Episodes: https://www.youtube.com/playlist?list=PLi78svKlBr_8o0dDOX8DxO_Wwxu6WYhhA Watch Host Favorites: https://www.youtube.com/playlist?list=PLi78svKlBr__Zu40RL7mWxCuOOe54zgy2 Join the Fed Haters Club @ https://www.goodmorningliberty.us/fedhatersclub Join GML: joingml.com Martens Minute: https://martensminute.podbean.com/ All links @ gml.bio.link Subscribe for more blunt, skeptical, liberty-minded analysis. Like the video, answer the pinned question, share it with someone who disagrees, and leave a rating and review on your podcast app.  

What happens when AI makes employees more productive today but gradually weakens the expertise companies will depend on tomorrow? In this episode of Tech Talks Daily, I speak with Dr. Margaret Cunningham, VP of Security and AI Strategy and Field CISO at Darktrace, about cognitive tech debt, the growing risk that companies are gaining short-term efficiency from AI while unintentionally weakening critical thinking, technical expertise, problem-solving ability, and human judgment. Margaret brings a rare combination of experience to this conversation. With a PhD in Applied Experimental Psychology and a career spanning behavioral science, cybersecurity, privacy, human-centered security, and AI strategy, she examines technology adoption through the lens of how people actually think, learn, develop expertise, and make decisions. She explains cognitive tech debt by comparing it with the technical debt familiar to software teams. Companies can introduce technology quickly and enjoy immediate improvements in speed and output, only to discover weaknesses underneath those gains later. With AI, the debt may accumulate in people. Employees can appear highly productive while outsourcing the difficult cognitive work required to build judgment, recognize patterns, understand failures, and develop genuine expertise. We discuss emerging evidence that over-reliance on AI is already affecting professional skills. Software engineers may become less capable of diagnosing problems in code they did not create themselves. Medical professionals can lose decision-making capabilities when they become dependent on automated systems. Across knowledge work, deep reading and sustained concentration are increasingly being replaced by summarization, generation, and superficial review. Margaret describes the current period as the "bridge years," when AI systems are becoming increasingly capable but people still need to maintain the expertise required to recognize mistakes, question recommendations, recover from failures, and understand when automation should not be trusted. Companies cannot safely abandon human skills before technology can reliably perform those responsibilities without supervision. The conversation also challenges one of the most repeated promises surrounding enterprise AI adoption: that automation will remove routine work and allow employees to concentrate on higher-value activities. Margaret argues that companies have done a poor job of defining which tasks people genuinely want to give up and which skills they need to preserve. Some of the repetitive, slow, and difficult work being automated may be exactly where people develop pattern recognition, creativity, and professional judgment. This creates a serious challenge for cybersecurity teams and other high-stakes professions. If employees become reviewers of AI-generated outputs rather than practitioners developing expertise through experience, where will the next generation of senior engineers, security analysts, doctors, researchers, and technical specialists come from? Margaret explains why leaders need to understand which AI techniques are being used for different business problems rather than treating every form of artificial intelligence as interchangeable. Large language models, machine learning systems, behavioral analytics, and other technologies have different strengths and limitations. Knowing what questions to ask requires domain expertise, creating a difficult paradox for companies that may be automating away the very experience needed to govern these systems responsibly. We also examine the human consequences of AI adoption. Technical specialists who enjoy solving difficult problems can lose motivation when meaningful work is replaced by reviewing machine-generated outputs. Companies may struggle to understand who owns decisions made through collaboration between humans and AI, while younger employees could lose access to the experiences that previously helped people progress from beginners to experts. Margaret offers practical advice for business and technology leaders deciding how quickly to introduce AI across their workforce. Companies can identify the skills they need to preserve, create opportunities for employees to practice difficult cognitive work, use simulations and training to maintain expertise, ask teams which aspects of their jobs give them purpose, and resist pressure to automate every task simply because the technology exists. The message is not anti-AI. Margaret sees enormous potential for artificial intelligence in scientific research, cybersecurity, productivity, and solving difficult problems. But realizing those benefits requires a more intentional relationship between people and machines. For business leaders, CISOs, technology teams, AI practitioners, and anyone concerned about the future of human expertise, this conversation provides a practical framework for recognizing cognitive tech debt, deciding what should and should not be automated, preserving critical thinking skills, and building healthier forms of human-AI collaboration. AI can make people faster. The bigger question is whether companies can capture those productivity gains without losing the human capabilities they will need when the technology gets something wrong.

The fundamentals of pH and why your mash pH might not be what you think it is.Special Guest: Ashton Lewis.

After hiking the Tour du Mont Blanc and racing the Zugspitz 100K, I flew to Corsica for one final adventure: the GR20, often called the hardest long-distance trail in Europe.I expected another scenic alpine trek. Instead, I found endless scrambling, brutal climbs, snowfields, technical descents, and some of the most rewarding mountain scenery I've ever experienced. Along the way I hitchhiked across Corsica, swam in alpine pools during a European heat wave, got sick halfway through the hike, learned why everyone fears this trail, and discovered that sometimes the biggest challenge isn't the terrain—it's stepping into the unknown.In this episode I share what makes the GR20 so difficult, what surprised me most about Corsica, how I completed the route in 4½ days, and why this month of solo travel has been about much more than backpacking.Topics include:* What makes the GR20 so infamous* Backpacking through Corsica's mountains* Refugios, bivouacs, and trail logistics* Hiking northbound instead of southbound* Technical terrain, snowfields, and massive climbs* Hitchhiking, language barriers, and travel lessons* Why doing uncomfortable things builds confidenceIf you've ever wondered whether the GR20 deserves its reputation—or you've been looking for your next big adventure—this episode is for you.Support our Sponsors: Sawyer: https://sawyerdirect.net/Janji (code: Freeoutside): https://snp.link/a0bfb726CS Coffee: CSinstant.coffeeGarage Grown Gear: https://snp.link/db1ba8abSubscribe to Substack: http://freeoutside.substack.comSupport this content on patreon: HTTP://patreon.com/freeoutsideBuy my book "Free Outside" on Amazon: https://amzn.to/39LpoSFEmail me to buy a signed copy of my book, "Free Outside" at jeff@freeoutside.comWatch the movie about setting the record on the Colorado Trail: https://tubitv.com/movies/100019916/free-outsideWebsite: www.Freeoutside.comInstagram: thefreeoutsidefacebook: www.facebook.com/freeoutside#Trailrunning #Runningnews #Outdoors #Outdooradventure

Join us as John Mark Troyer and Rakesh Gupta break down what AI observability actually means once agents leave the demo and hit production - and why the old playbook for monitoring doesn't cut it anymore. John Mark and Rakesh walk through why errors and latency are just the starting point for agents, how quality became a much harder thing to measure once bots went from answering questions to taking autonomous action, and why token-based costs are creating a confusing new economics problem for engineering teams. You'll learn the difference between online and offline evals, why a new engineering role has emerged just to build testing harnesses for agents, how trace data works differently when every prompt is its own trace, and what teams are doing to catch prompt injection and other AI-specific failure modes before they become expensive mistakes. Timestamps 0:00 Welcome & Introduction 3:20 Full Disclosure - Observe, Snowflake, and How This Conversation Started 7:07 From Developer Concerns to Boss's Boss's Boss - Spending Out of Control 8:29 What Actually Gets Measured - Errors, Latency, Quality, and Cost 10:30 The Casino Chip Problem - Confusing Token Pricing Models 13:47 Defining Quality When the Task Itself Is Nebulous 18:41 The New Role - Engineers Who Just Build Testing Harnesses 22:00 Non-Determinism and Why Testing Agents Is Expensive 32:10 Trace Data, Tool Calls, and What Observability Tools Actually See 55:08 Prompt Injection, Zero-Width Characters, and Real World Failures How to find John Mark: https://www.linkedin.com/in/johnmarktroyer/ How to find Rakesh: https://www.linkedin.com/in/rg0/ Links from the show:

In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Sarah B. Nelson, Distinguished Designer at Kyndryl and co-founder of Kyndryl Vital, about why AI's promise to remove friction is actually surfacing the human dynamics organizations have always avoided facing. They unpack how a single word like trust splinters into distinct concerns — model accuracy, data use, organizational credibility — and why treating human in the loop as a rubber-stamp step risks disengagement and stripped-out meaning. Nelson draws on the NeuroLeadership Institute's SCARF model to explain why AI rollouts stall on status, certainty, autonomy, relatedness, and fairness rather than on the technology itself, and shares stories spanning cybersecurity burnout, Holacracy at Zappos, and the extraction economics behind AI training data. The conversation keeps returning to her insistence on designing with people rather than at or for them, and on imagination as the resource most at risk of being engineered out of enterprises chasing speed. She closes with a Buckminster Fuller line she keeps returning to: that people are called to be architects of the future, not victims of it.

In this episode of Business, Finance and Soul, Shaun sits down with Jonathan Steele, Co-Founder and Chief Investment Officer of One Wealth Advisors, for a conversation about the human side of wealth. Jonathan brings more than 25 years of experience in financial services and manages over $1 billion in assets, but this conversation goes far beyond portfolios, performance, and traditional financial planning. The core idea: money is not just math — it is emotional, relational, and deeply connected to how we were raised, what we value, and what gives us peace of mind. Shaun and Jonathan explore the concept of financial therapy, why a person's relationship with money often matters more than the technical structure of a financial plan, and how childhood beliefs around scarcity, security, and success can shape adult financial decisions. They also discuss how families can talk more openly about money, including Jonathan's simple framework of spend, save, and share. The conversation touches on raising financially aware children, involving both partners in financial planning, the emotional ROI of major life decisions, and why experiences can sometimes be just as valuable as investment returns. Jonathan also shares his thoughts on AI, the future of financial advice, and why technology may change the tools — but not the need for empathy, trust, and human judgment. This episode is a reminder that wealth is not just about accumulation. It is about alignment, peace of mind, and building a life that feels meaningful. Topics include: Financial therapy Money mindset Behavioral finance Family money conversations Teaching kids about money The emotional ROI of wealth Needs, wants, and wishes AI and the future of financial advice Building financial peace of mind Learn more about Jonathan Steele and One Wealth Advisors: onewealth.net   Timestamp Highlights 00:00 — Welcome to Business, Finance and Soul 01:02 — Jonathan explains financial therapy 03:10 — The most unhealthy relationships people have with money 05:33 — Why financial restructuring is not enough 08:50 — Wealth plateaus and Maslow's hierarchy 10:51 — The emotional ROI of a boat 13:16 — Jonathan's upbringing and fiscal responsibility 17:26 — How families are talking to kids about money 22:00 — Spend, save, and share 28:36 — Needs, wants, and wishes 31:59 — Why life is not a spreadsheet 33:12 — Shaun's boarding school decision story 41:59 — When one partner carries the financial burden 46:01 — Passwords, trusts, and access to financial information 47:14 — AI, robotics, and the future of money 53:09 — Building financial scaffolding 54:35 — Stay curious About Jonathan Steele Jonathan Steele is the Co-Founder and Chief Investment Officer of One Wealth Advisors. He has more than 25 years of experience in financial services and brings a unique perspective to wealth management by combining investment expertise with behavioral finance, emotional intelligence, and what he describes as financial therapy. His work focuses on helping clients develop healthier relationships with money and use their wealth to create greater peace of mind, happiness, and life satisfaction. Learn more about Jonathan and One Wealth Advisors at onewealth.net.  

July 10, 2026 - 5am: U.S., Iran strikes intensify as officials say 'technical talks' with Tehran continue WSJ: Israel shared intel with the U.S. that said it showed Iran was considering a new plan to assassinate President Trump Calls growing for an independent investigation into deadly Texas ICE shooting Graham Platner has still not formally dropped out of Maine Senate race Growing number of Republicans are joining Democrats demanding answers about the current health status of Republican Senator Mitch McConnell  Senators investigate claims that Kash Patel misused FBI funds Ted Cruz warns that James Talarico has a "real chance" to win his Senate race in Texas  To listen to this show and other MS podcasts without ads, sign up for MS NOW Premium on Apple Podcasts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Another trading week is in the books, and we're wrapping it all up with one of my favorite formats—the Viewer Q&A! This week, we'll answer several great questions from the audience, breaking down individual stocks, technical setups, and the broader market to help you make better trading decisions. On today's show, we'll discuss: Shake Shack – Is the recent move sustainable, or has the stock gotten ahead of itself? SK Hynix – One of the biggest beneficiaries of the AI boom. Does it still have room to run? Intel – Can the chip giant regain its footing, or is it still playing catch-up in the semiconductor race? Plus several additional viewer-submitted questions covering trading, investing, and market strategy. I'll also provide an update on my Tesla trade, discussing how the position has evolved, what adjustments I've made, and what I'm watching next. Sometimes the best lessons come from managing a trade after it's been placed—not just finding the entry. Finally, we'll wrap up the week with a broad market overview, looking at: The biggest market-moving headlines Sector rotation and market leadership Technical levels to watch next week Where I see potential opportunities developing Whether you're trading individual stocks or simply trying to stay on top of the market, this episode is packed with practical insights and real-world analysis. Because every week the market tells a story... Our job is to listen carefully. Listen now:

 Episode 179 of Award Travel 101, hosted by Angie Sparks with moderator Mike Zaccheo, covers news on Delta's new "Miles Headstart" borrow-now-earn-later feature, an Alaska Atmos Rewards status match opportunity, and IHG discounts on new-hotel stays, alongside personal updates on card spend progress, upcoming trips (Punta Cana, Japan, the Milwaukee meetup), and Angie's Swiss rail and Ireland trip planning. The main segment spotlights Napa Valley as a destination, with both hosts sharing their own trip breakdowns — flights, hotel picks (Alila Napa Valley, Andaz Napa, Silverado Resort), wineries, and food recommendations like Ad Hoc and Mustard's. The episode wraps with a tip on chasing time-limited earning opportunities like the Newegg/Paze promotion before they disappear. Where to Find UsThe Award Travel 101 Facebook Community.To book time with our team, check out Award Travel 1-on-1.You can also email us at 101@award.travelBuy your Award Travel 101 Merch hereReserve tickets to our Late Summer 2026 Meetup in Milwaukee now. award.travel/mke2026Our partner CardPointers helps us get the most from our cards. Signup today at https://cardpointers.com/at101 for a 30% discount on annual and lifetime subscriptions! Lastly, we appreciate your support of the AT101 Podcast/Community when you signup for your next card!Technical note: Some user experience difficulty streaming the podcast while connected to a VPN. If you have difficulty, disconnect from your VPN.  

Join us as Bob Belderbos breaks down how to actually learn new skills and languages in a world where AI can write the code for you before you've even finished the thought. Bob shares why he taught himself Rust the hard way, how keeping deliberate friction in your learning process protects you from skill atrophy, and why AI is incredible at explaining concepts but dangerous as a crutch for understanding them. You'll learn the difference between using AI to explain versus using it to do, how to structure a project-based learning path with tests as your guide, why coding autocomplete might be quietly hollowing out your skills, and how his Python and Rust cohorts are teaching professional engineers to use agents without losing ownership of their code. Timestamps 0:00 Welcome & Introduction 1:09 Bob's Background - From VBA to Python to Rust 4:39 Why Learn Rust When Python Already Works 11:43 AI as a Learning Assistant vs. a Socratic Teacher 12:30 The Slot Machine Problem - Agents and Skill Atrophy 17:24 Working Outside Your Expertise - The Fast LED Story 27:02 Structuring Prompts That Actually Teach You Something 33:56 Teaching Agentic AI in Production - The Expense Classifier Cohort 36:07 Autocomplete, Copilot, and the Line Between Helping and Hollowing Out 44:03 AI Slop, Coauthorship, and the Anti-Slop Engineer 53:49 What's Next - Rust, Haskell, and Bob's Upcoming Cohorts How to find Bob: https://www.linkedin.com/in/bbelderbos/ https://belderbos.dev/ Links from the show:

The Fast Lane with Ed Lane: Friday, July 10, 2026

This week we're discussing a pair of darkwave records which both show off the range of the genre and also sit quite far away from especially trendy versions of the style which have perhaps worn out their welcome. Fist up is the classic Gala from Argentinian legends Euroshima, which helped establish the standard for the genre for generations of South American acts to come. Next, the moody but forceful Mire Of Mercury, the most recent LP from Estonia's Bedless Bones, draws links between the dancefloor and pagan ancience.

Today's Topic:1. Sound Signature Review 6.230 – Strategic Sciences MFMD + SDX on 20-in .308 bolt-action. One of the most interesting silencer systems we have evaluated in the research, to date. The multifunction muzzle device, like all silencers, suppresses recoil, flash, and blast. How does the MFMD compare with other things on the market? Are reflex designs making a comeback? Technical discussion to accompany last week's report. (00:08:58)a. Intro and recap – what's the point of this system? (00:11:14)b. MFMD + SDX overview – size, weight, oh my! (00:18:58)c. MFMD + SDX silencer design – what in tarnation? (00:41:42)d. Hazard Map Brief 8.1.27 (00:51:43)e. System performance - Blast? Sound? Recoil? Flash? Barrel heat? (00:59:54)f. Overall thoughts (01:19:37)Sponsored by Legion Athletics and the PEW Science Laboratory!Legion Athletics: use code pewscience for BOGO off your entire first order and 20% cash back always!

Technical expertise can open doors in public health, but effective leadership requires a different set of skills: communication, self-awareness, adaptability, and the confidence to lead authentically. Gabby Hadly, emergency preparedness and response manager for the Snohomish County Health Department in Washington state, reflects on her experience in ASTHO's Executives Leading in Public Health (DELPH) program. She discusses how the program helped her develop a leadership style rooted in authenticity rather than imitation and why creating supportive spaces for emerging leaders is critical for the future of public health.  Hadley shares how DELPH strengthened her public speaking and communication skills, connected her with peers and mentors from across the country, and provided practical tools for navigating change, conflict, and uncertainty. She also highlights the value of accountability partnerships, professional networks, and learning alongside colleagues facing many of the same challenges reshaping public health today.Developing Executive Leaders in Public Health | ASTHOApplications | ASTHOPerformance Management | ASTHO

Huyen and Niki talk tech and science. Discussing their favorite news this month and interrogate AI's place in learning.Starring Dr. Niki Ackermans, Huyen Tue Dao Hosted on Acast. See acast.com/privacy for more information.

Kerry Caldwell suffered severe injuries from an accident in the brewhouse. She was airlifted and overcame the 34% chance of survival calculated by the hospital. This episode is both the story of her accident and a description of a simple, inexpensive device that should be installed in your brewery to prevent similar accidents. Special Guests: Kerry Bloxham (Caldwell) and Scott Zetterstrom.

Live July 3, 2026 | Yaron Brook Show(Season 12, Episode 113)DSA; Trump's Corruption; SCOTUS; Venezuela; Iran; Germany; CA Crime; Achievement | Yaron Brook ShowDemocratic Socialists Are Winning. Trump Profits. SCOTUS Reshapes America. Is Anyone Defending Capitalism?The political center continues to collapse—and almost nobody is making the case for freedom.This week, Yaron Brook dives into the Democratic Socialists' stunning victories, Trump's growing conflicts of interest, major Supreme Court rulings, Venezuela, Iran, crime, scientific fraud, and why the moral defense of capitalism is disappearing just when it's needed most.Is socialism becoming mainstream? Is corruption now accepted as normal politics? Are America's institutions protecting individual rights—or abandoning them?Plus, Yaron answers live audience questions on selfishness, Objectivism, Iran, and much more.Watch the full episode here: https://youtube.com/live/AqIL97S50eAMain Topic Timestamps00:00 Introduction, schedule & OCON travel recap03:06 OCON virtual options, video releases & poker night05:10 Next OCON in Keystone & Atlas Shrugged anniversary07:26 Democratic Socialists' primary victories10:40 What the DSA is—and why it's growing24:34 Why capitalism has lost its defenders31:35 Identity politics and DSA controversies32:27 Why socialism is making a comeback36:22 New York's 78° A/C rule39:46 Trump's financial disclosures & corruption concerns56:16 Major Supreme Court decisions1:01:14 Birthright citizenship & birth tourism1:06:00 Election conspiracies & court legitimacy1:08:55 Venezuela's instability1:15:12 Iran's regional ambitions1:19:49 Crime, policing & public safety1:26:13 Scientific fraud & research integrity1:30:00 NASA satellite rescue1:31:35 Breakthroughs in emergency medicine1:32:38 Trade agreements & economic policy1:34:25 Upcoming shows1:36:57 Fundraising update1:37:22 OCON stories & early SpaceX memories1:38:44 The decline of Enlightenment values1:41:48 Can politicians be persuaded?1:43:07 Why Ayn Rand walking tours matter1:44:36 Technical difficulties with superchatLive Audience Questions2:07:25 Is "selfish" really the wrong moral concept—or just commonly misunderstood?2:08:25 If Iran wanted Trump Tower, why wouldn't it simply invest?If you enjoyed the discussion, subscribe, like the video, and share it with someone interested in politics, economics, philosophy, and current events.#Capitalism #Objectivism #Politics #Trump #Socialism #DSA #SupremeCourt #Iran #EconomicsThe Yaron Brook Show is Sponsored by[The Ayn Rand Institute](https://www.aynrand.org/starthere)[Energy Talking Points, featuring AlexAI, by Alex Epstein](https://alexepstein.substack.com/)[Express VPN](https://www.expressvpn.com/yaron)[Hendershott Wealth Management](https://www.youtube.com/watch?v=X4lfC...) &(https://hendershottwealth.com/ybs/)[Michael Williams & The Defenders of Capitalism Project](https://www.DefendersOfCapitalism.com)[Support the Show]( / yaronbrookshow )[Sponsor the Show](askyaron@yaronbrookshow.com/)[One-time donation](https://bit.ly/2RZOyJJ)Join the [Yaron Brook Show YouTube channel]( / @yaronbrook )Like what you hear? Like, share, and subscribe to stay updated on new videos and help promote the [Yaron Brook Show](https://bit.ly/3ztPxTx)Continue the discussion by following Yaron on [Twitter](https://bit.ly/3iMGl6z) and [Facebook](https://bit.ly/3vvWDDC )Want to learn more about Ayn Rand and Objectivism? Visit the [Ayn Rand Institute](https://bit.ly/35qoEC3)Become a supporter of this podcast: https://www.spreaker.com/podcast/yaron-brook-show--3276901/support.Yaron is the executive chairman of the Ayn Rand Institute and a world class speaker. He is the coauthor of the national best-seller Free Market Revolution: How Ayn Rand's Ideas Can End Big Government, Equal is Unfair: America's Misguided Fight Against Income Inequality and In Pursuit of Wealth: The Moral Case for Finance. He speaks around the world on a variety of topics including the morality of capitalism, Ayn Rand and her philosophy, finance and economics, and the value of inequality.

Today's Mystery: After a man is gunned down outside his home following a bitter domestic argument, Joe Friday and Ed Jacobs launch a search for the shooter's wife, who has vanished after warning that she'll kill anyone who tries to capture her. With the suspect making taunting phone calls while remaining one step ahead of police, the detectives race against time to track her down before violence erupts again.Original Radio Broadcast Date: April 3, 1952Originating from HollywoodStarred: Jack Webb as Sergeant Joe Friday and Barney Phillips as Sergeant Ed Jacobs. Also featuring Herb Ellis, Jack Kruschen, and Helen Kleeb. Script by Jim Moser.Music by Walter Schumann.Announcer: Hal Gibney. Technical advice from the Los Angeles Police Department.Support the show monthly at patreon.greatdetectives.netPatreon Supporter of the Day: Rochelle, Patreon supporter since April 2025.Support the show on a one-time basis at support.greatdetectives.netMail a donation to: Adam Graham, PO Box 15913, Boise, Idaho 83715Take the listener survey at survey.greatdetectives.netGive us a call 208-991-4783Become one of our friends on Facebook at facebook.com/radiodetectivesFollow us on Instagram at instagram.com/greatdetectivesFollow us on Twitter/X at twitter.com/radiodetectivesJoin us again tomorrow for another detective drama from the Golden Age of Radio.

In this episode reshaping how we think about AI, Joan Nguyen and Sarah Willersdorf take over the podcast to talk about what's possible right now. Joan Nguyen is the co-founder and CEO of Bümo, the first AI family assistant to help parents instantly book care and handle the logistics of family life. Sarah Willersdorf is the former Head of Luxury, Fashion & Beauty at Boston Consulting Group, and a former CMO who now advises boards and CEOs on where AI actually drives value. They explore how execution is being democratized, why women are positioned to win in this shift, and what fundamentally can't be automated. They discuss how they're building in their lives every day, and why this moment is real—and closing. Key highlights: How they actually use AI in their lives every day—from household admin to building companies Why women have a unique competitive advantage right now: communication, judgment, strategy What builders are genuinely creating in this moment when execution costs have dropped What AI can't replace: human judgment, conviction, and deciding what's worth building The real opportunities and what's at stake in this moment Ready to start building with AI? If you're ready to start building with AI and want to know where to actually start, or what you should pay attention to—Joan and Moj created AI Maxxing, a 6-week mentorship program for founders, operators, and executives. The 1st cohort begins August 20.Visit joinaimaxxing.com and use code GOOP at checkout for exclusive 10% off. Connect with Joan Nguyen and Sarah Willersdorf: Follow Sarah Willersdorf on LinkedIn Follow Joan Nguyen on LinkedIn To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices