Podcasts about predict

How can you live without fear of death? Pastor Skip reveals how trusting Jesus turns even life's hardest questions into unshakable hope.

Today on Connect with Skip Heitzig, how can you live without fear of death? Pastor Skip reveals how trusting Jesus turns even life's hardest questions into unshakable hope. To support this ministry financially, visit: https://www.oneplace.com/donate/104/29?v=20251111

Can you predict your future? Pastor Skip shares how you can face uncertainty with confidence when your hope is anchored in Christ.

Dr. Daniel Amen (brain health expert, psychiatrist and physician) wants to reframe “mental health” as brain health, and explain how brain imaging can reveal patterns behind depression, anxiety, addiction, and even chronic pain. They unpack automatic negative thoughts, negativity bias, and simple daily “tiny habits” that can reshape your brain and your life. Plus, Dr. Amen connects science with meaning, purpose, and spirituality, asking one powerful question: is what you're doing right now good for your brain and does it honor your creator? SPONSORS!

Today on Connect with Skip Heitzig, can you predict your future? Pastor Skip shares how you can face uncertainty with confidence when your hope is anchored in Christ. To support this ministry financially, visit: https://www.oneplace.com/donate/104/29?v=20251111

Come Again: Sexuality and Orgasm, my solution-driven audio Series, for both non-healthcare professionals and healthcare professionals is now  available on demand on drstreicher.com. Subscribers get loads of supplementary guides and resources. Health care professionals have an option to purchase additional material on incorporating sexual medicine into their practice.  For a 25% discount to the COME AGAIN Series, use code PODCAST25. This discount code expires December 21. This episode is a free preview from COME AGAIN Episode 19 When it comes to testosterone, hairy guys with round the clock virility come to mind, thanks to those non-stop ads warning men of the dire consequences of "Low T". Not as well known is that TESTOSTERONE is not just a male hormone but is a HUMAN hormone that is just as important for women.  In this episode: ·      The ROLE of testosterone in women ·      WHERE testosterone is normally produced  ·      The potential BENEFITS of taking testosterone  ·      How well testosterone therapy WORKS and why it doesn't work in everyone ·      How to PREDICT if you will respond to testosterone therapy ·      What TESTS you should have prior to starting testosterone therapy ·      Why is SEX HORMONE BINDING GLOBULIN important?  ·      Why someone would have a HIGH SEX HORMONE BINDING GLOBULIN ·      Why the FDA has never approved testosterone for women ·      Why PELLETS are a PROBLEM ·      Why gels are the SAFEST and MOST EFFECTIVE form of testosterone for women  ·      The potential SIDE EFFECTS of testosterone therapy

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Season 3: Episode 9Host Jaylon Fudge is joined by co-hosts Alex Elmore and Javion Hall as they welcome Simon Wheeler for a full-scale deep dive into the 12-team College Football Playoff. From first-round matchups to championship predictions, the crew analyzes every path, every pressure point, and every potential upset in a bracket that could redefine the sport.But the chaos doesn't stop there.The episode closes with a ruthless and unpredictable blind ranking of iconic Heisman Trophy winners, forcing hot takes, instant regret, and debates that only get louder as the list fills up. Legends collide, legacies are questioned, and no take is safe.Bracket chaos. Heisman history. Pure Burner energy.

Hour 1 of Jake & Ben on December 17, 2025 Thoughts on the NBA Cup with the New York Knicks taking it home last night. Is it any sort of prediction for the NBA Champion?  Utah Jazz Analyst Mike Smith joined to talk about the Utah Jazz & their "Potential Superstar" in Keyonte George.  Keyonte George's Third Year stats are eerily similar to Donovan Mitchell's. 

What's coming in Lorwyn Eclipsed?

Most visibility programs fail because teams don't know what to measure—or they measure too much, too late. In this final episode of the Visibility Engineering series, Gini Dietrich breaks down three simple metrics that tell you whether your work is driving real pre-pipeline demand. No dashboards. No spreadsheets. Just signal.

SBS Finance Editor Ricardo Gonçalves speaks with Jonathan Shead from State Street Investment Management about the day's market action including where interest rates are going and the opportunities for investors in 2026.

Gary Marcus, professor emeritus at NYU, explains the differences between large language models and "world models" — and why he thinks the latter are key to achieving artificial general intelligence.

Gary Marcus, professor emeritus at NYU, explains the differences between large language models and "world models" — and why he thinks the latter are key to achieving artificial general intelligence.

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In this episode, Doug adds up wins, Andrew evaluates juniors, and the guys Predict the Portal

1. Kevin's Two-Minute DrillA. Game SummaryBucs lose a heartbreaker: 29–28 to the Falcons.Fourth-quarter collapse:Blew a 14-point lead.Defense folded.Baker Mayfield missed two key passes.B. Todd Bowles on the Hot SeatKevin declares: “Goodbye, Todd Bowles… that seat is on fire.”Falcons details:Only 4 wins coming into the game.19 penalties committed.A 37-year-old QB.Kevin's repeated sendoffs: “See ya, Todd. Adios, Todd. Au revoir, Todd. Arrivederci, Todd. Sayonara, Todd.”C. Post-Game ControversyTodd Bowles blames the players, throwing them under the bus with strong language.Kevin highlights how harsh and unnecessary the comments were.D. Baker Mayfield's PerformanceRough fourth quarter:One interception.Missed a winning-drive throw.Baker's post-game remarks:Takes accountability: “It's our fault. It's my fault.”E. A Bright SpotMike Evans returns strong:6 catches, 132 yards.But not enough to save the game.F. Next WeekMust-win game vs. the Carolina Panthers in Charlotte.Game time: Sunday at 1 PM on FOX. 2. Post-Drill DiscussionA. Hosts ReactHosts comment that Kevin's “two minutes” was more like five.Agreement that Todd Bowles throwing players under the bus was uncalled for.Concerns about coaching strategy and season-long issues.B. Season OutlookRemaining schedule: Panthers twice, Dolphins once.Hosts predict:Unlikely the Bucs win any of the remaining games.Even if they make the playoffs, they won't win a playoff game.Discussion about whether the Glazers would fire Todd Bowles mid-season.Historically, they've never done it.Hosts believe it should happen but probably won't until season's end.C. Locker Room ConcernsHosts believe Bowles may have lost the locker room entirely.Predict continued struggles due to lack of cohesion and confidence.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Computational methods can predict stability issues before the lab. But how do you actually implement these approaches in your formulation workflow? From excipient selection to long-term stability prediction, in silico tools are transforming how biotech teams develop robust formulations while reducing costly trial-and-error cycles.In Part 2, Giuseppe Licari, Principal Scientist in Computational Structural Biology at Merck KGaA, returns to share practical implementation strategies for integrating computational methods into biologics formulation development. Giuseppe reveals how molecular dynamics simulations guide excipient selection, where current methods hit their limits, and how emerging AI capabilities are expanding what's possible in formulation prediction.Whether you're at a well-resourced pharma company or a lean startup, Giuseppe offers actionable guidance for leveraging computational tools to predict protein behavior, optimize formulations, and accelerate your development timeline.Topics covered:Predicting protein aggregation and excipient interactions before manufacturing (00:45)Using molecular dynamics to understand protein behavior over time and in different environments (03:03)The interplay between computational predictions and experimental stability studies (04:49)The limitations of current in silico methods for predicting long-term stability (05:08)Emerging use of AI and machine learning to predict protein properties and improve developability (06:36)Future possibilities: Generative AI for protein design and formulation prediction (08:06)Advice for small companies: leveraging software-as-a-service and external partners to access computational tools (09:55)The impact of increasing computational power on the field's evolution (11:12)Most important takeaway: being open and curious about new computational techniques in biotech formulation (12:08)Discover how to bridge computational predictions with experimental validation, navigate the current limitations of in silico stability forecasting, and position your organization to benefit from AI-driven formulation development, regardless of your resource constraints.Connect with Giuseppe Licari to continue the conversation and explore how computational approaches can solve your formulation challenges before you ever step into the lab.Connect with Giuseppe Licari:LinkedIn: www.linkedin.com/in/giuseppe-licariNext step:Need fast CMC guidance? → Get rapid CMC decision support hereSupport the show

Nick and Josh predict the winners of The Game Awards. Josh explains the difference between a Mega Man X and a Mega Man Zero. Nick has played Horses and it left him saying “what the hey?” about all this censorship.In lieu of ratings and reviews we say … FUCK THE ALGORITHM, TELL A FRIEND!We have a new website! Come check it out! https://www.smashinggametime.com/Thank you to Alex Marvin Clark for our opening theme Hunt Him Down. https://soundcloud.com/lizardbeach?ut...

In this episode I get my buddy Mark Olis from Moultrie on to talk about the history of Moultrie and the new Edge 3 and Edge 3 Pro! Podcast brought to you by:Asio : SEBH for 15% off https://asiogear.com/Summit: SEBH15 for 15% off https://www.summitstands.com/Bowtique: SEBHP https://thebowtiquellc.com/Bergy Bowsmith: SEBH10 for 10% off https://bergybowsmith.com/G5 Outdoors https://www.g5outdoors.com/Prime Archery https://www.g5prime.com/Dialed Archery https://dialedarchery.com/ Moultrie https://www.moultrie.com/BHL https://bowhuntingleague.com/Bohning Archery SEBHP2025 for 20% off https://www.bohning.com/12:27 ProductionsScrape doctor SEBH10 for 10% https://scrapedoctor.com/Victory Archery https://www.victoryarchery.com/

What if you could predict formulation failures before ever touching a pipette? Computational approaches are revolutionizing biologics development, replacing trial-and-error experimentation with predictive intelligence that catches stability issues early and accelerates your path from candidate selection to clinic.In this episode, David Brühlmann welcomes Giuseppe Licari, Principal Scientist in Computational Structural Biology at Merck KGaA. A chemist by training, Giuseppe transitioned from wet lab experimentation to the predictive power of in silico modeling. Today, he operates at the intersection of computational biology and CMC development, using digital tools to screen candidates for developability, predict formulation challenges, and de-risk development programs before committing resources to the lab.Discover how computational methods are transforming the way biotech companies approach developability assessment and formulation strategy:Why maximizing shelf life isn't always necessary in early development phases (02:56)The critical role of communication between computational and bench scientists (06:46)Core properties to assess for developability, including hydrophobicity, aggregation, charge, and immunogenicity (11:06)How accurate are in silico predictions, and where do they add the most value? (13:23)The limitations and strengths of machine learning and physics-based models in predicting protein behavior (15:19)The differences between developability, formulation development, and formulatability, and the value of early cross-functional collaboration (17:17)When to use platform formulations and when tailored approaches are needed for complex molecules (19:25)The advantages of using computational methods at any stage, especially for de-risking strategies (20:13)Listen in for practical strategies for integrating in silico predictions into your developability and CMC workflows, catching stability issues before the lab, and making smarter development decisions that save time, material, and money.Connect with Giuseppe Licari:LinkedIn: www.linkedin.com/in/giuseppe-licariNext step:Need fast CMC guidance? → Get rapid CMC decision support hereOne bad CDMO decision can cost you two years and your Series A. If you're navigating tech transfer, CDMO selection, or IND prep, let's talk before it gets expensive. Two slots open this month.Support the show

Episode Info As the president of Personal Lines at Nationwide, Casey Kempton is responsible for all aspects of the business including product, underwriting, sales and distribution, claims and services. Her organization focuses on delivering effortless, personal and reassuring experiences for distribution  professionals and customers who value protection and service. Casey previously served as the executive vice president, digital business officer at Chubb where she was responsible for small business revenue generation, agency experience and the build of digital acquisition channels via direct-to-consumer affinity partnerships, eBrokers and agent-carrier connectivity. Prior to Chubb, she led the personal lines agency channel at The Hartford including oversight of field sales performance, distribution strategy, marketing and product portfolio management. She also spent time with the ACE Group accountable for global personal and commercial lines as well as leading the operations and information technology for the Latin America region. Casey's early career included working on P&C strategic initiatives across the insurance value chain at The Hartford. A graduate of the University of Connecticut, Casey holds Bachelor of Arts degrees in Cognitive Anthropology and English. She also has two patents in her name relating to homeowners insurance rating. Episode Overview: Casey shares her expertise and vision for the future of personal insurance lines, discussing the evolving landscape of the industry and the innovative strategies Nationwide is implementing to stay ahead. Key Topics Discussed: Introduction to Casey Kempton: Casey introduces herself and her role at Nationwide, where she oversees Auto, Home, Umbrella, and other personal lines. She shares her journey and experiences since taking on the role in February 2024. Customer-Centric Approach: Nationwide's strong focus on customer satisfaction and building robust relationships with distribution partners. The importance of understanding customer needs and providing tailored insurance solutions. Predict and Prevent Strategy: Discussion on the "Predict and Prevent" initiative, which aims to mitigate risks before they occur. How this strategy is reshaping the insurance landscape by focusing on prevention rather than just compensation. Technological Advancements: The role of AI and data in enhancing pricing sophistication and service delivery. The impact of telematics and connected technologies in personal lines insurance. Industry Challenges and Opportunities: Navigating the complexities of personal lines insurance, including risk management and loss prevention. The evolving consumer mindset towards insurance as a necessary investment rather than a mere obligation. Future Outlook: Casey's vision for the future of insurance, emphasizing the need for continuous innovation and adaptation. The potential for growth in embedded insurance and partnerships with OEMs. Conclusion: Casey Kempton provides a comprehensive overview of the current state and future direction of personal lines insurance. Her insights into Nationwide's strategies and the industry's evolution offer valuable perspectives for anyone interested in the future of insurance. This episode is brought to you by The Future of Insurance book series (future-of-insurance.com) from Bryan Falchuk. Follow the podcast at future-of-insurance.com/podcast for more details and other episodes. Music courtesy of Hyperbeat Music, available to stream or download on Spotify, Apple Music, and Amazon Music and more.

We review the results from SentinelOne (S) and Snowflake (SNOW) and predict which stock is more likely to record profits first. We also take a critics-eye view of the Netflix-Warner Bros. deal amid Paramount's hostile counter offer. Rick Munarriz, Sanmeet Deo, and Tim Beyers: - Review last week's results from SentinelOne and Snowflake. - Predict which of the two will reach GAAP profitability first. - Give a critics choice take on the Netflix-Warner Bros deal, including some thoughts on Paramount's just-launched hostile takeover. Companies discussed: S, SNOW, NFLX, WBD, PSKY Host: Tim Beyers Guests: Rick Munarriz, Sanmeet Deo Producer: Anand Chokkavelu Engineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

Silver is flashing every warning sign in the global financial system! 
In only the last 30 days we've seen:


For nearly two centuries, international relations have been premised on the idea of the "Great Powers." As the thinking went, these mighty states—the European empires of the nineteenth century, the United States and the USSR during the Cold War—were uniquely able to exert their influence on the world stage because of their overwhelming military capabilities. But this conception of power fails to capture the more complicated truth about how wars are fought and won.  Our focus on the importance of large, well-equipped armies and conclusive battles has obscured the foundational forces that underlie military victories and the actual mechanics of successful warfare. Phillips O'Brien suggests a new framework of "full-spectrum powers," taking into account all of the diverse factors that make a state strong—from economic and technological might, to political stability, to the complex logistics needed to maintain forces in the field.  Drawing on examples ranging from Napoleon's France to today's ascendant China, he offers a critical new understanding of what makes a power truly great. Phillips Payson O'Brien is a professor of strategic studies and head of the School of International Relations at the University of St. Andrews in Scotland. He is the author of six books, including his latest War and Power: Who Wins Wars—and Why.

Episode #144 of the Grant Mitt Podcast. How to Predict Your Future: Designing Your Dream Life. Save Your Spot to the 2 Day Bootcamp: https://grantmittconsulting.com/blitz-workshop-register Apply for my Inner Circle Group: https://www.grantmittconsulting.com Learn more about your ad choices. Visit megaphone.fm/adchoices

Confusion around omega-3, seed oils and the omega-6:3 ratio has fuelled major misconceptions. In this episode, Angela speaks with leading researcher Dr William Harris to clarify what the evidence really shows about omega-6 fats, seed oils and long-chain omega-3s - and why much popular advice is outdated. They explore why the omega-6:3 ratio doesn't predict inflammation, why EPA/DHA deficiency is so common, and how omega-3 status affects mental health, pregnancy, cognition and cardiovascular resilience. WHAT YOU'LL LEARN • Why omega-6 isn't inherently inflammatory • What research shows about seed oils & chronic disease • How the Omega-3 Index works • Why adults, kids & athletes are often low in EPA/DHA • Omega-3 links to mood, postpartum recovery & cognition • DHA needs in pregnancy, breastfeeding & childhood • EPA/DHA effects on triglycerides & heart health • Fish oil vs algae vs krill - key differences • The truth about oxidation, mercury & microplastics • How much EPA/DHA is needed • Omega-3 for children's learning & behaviour • Early findings on omega-3 and skin hydration Timestamps0:00:00 Introduction0:00:19 Debunking Omega-3 & Omega-6 Myths 0:05:38 Seed Oils & Omega-6/Omega-3 Fatty Acid Ratio: Health Implications 0:11:47 Grass-Fed vs Grain-Fed Meat 0:14:18 Health Benefits of Omega-3 0:19:23 Omega-3 for Depression & Postpartum 0:22:36 Is Omega-3 Safe for Pregnant Women & Children? 0:29:39 Dosing Guide & Best Sources of Omega-30:37:28 Is Mercury in Fish Really Harmful? 0:43:22 How to Choose a High-Quality Omega-3 Supplement 0:49:34 Omega-3 for Heart Health, Blood Sugar & Diabetes Risk 0:52:59 Omega-3 for Brain Health0:55:50 Omega-3 for Skin & Beauty 1:02:17 Omega-3 for Dysmenorrhea & Menopause Hot Flashes VALUABLE RESOURCES A BIG thank you to our sponsors who make the show possible:• Hormone Harmony – Go to https://lvluphealth.com/angela | Use code ANGELA for an exclusive 15% off • Ozlo Sleepbuds® – Fall asleep faster and stay asleep longer | Use code ANGELA at https://ozlosleep.com/angela for your exclusive discount.• Kineon MOVE+ – Relieve joint pain, reduce inflammation, and improve mobility with clinically backed red light therapy | Use code ANGELA at https://kineon.io/angela for $50 off ABOUT THE GUEST Dr William Harris is one of the world's leading researchers in omega-3 fatty acids and co-inventor of the Omega-3 Index, the globally recognised biomarker for long-term EPA and DHA status. He has published over 300 scientific papers on omega-3s, cardiovascular health, cognition and inflammation, and is the founder of the Fatty Acid Research Institute (FARI), advancing clinical understanding of fatty acids and health.

Only a few more days until season 2! Charlie finally got Raye to sit down and watch the trailers to analyze every SINGLE second.Of the Eldest Gods will be moving to a Sunday release schedule throughout our review of the TV series. Send us an Iris message at oftheeldestgodspod@gmail.com with your thoughts and theories going forward! We would love to hear from you. Make sure to subscribe so you know when our next episode drops and rate and review if you like what we are doing.IG:⁠ www.instagram.com/oftheeldestgodspod/⁠Tumblr:⁠ https://www.tumblr.com/oftheeldestgodspod⁠SUPPORT US ON PATREON:⁠ www.patreon.com/oftheeldestgods⁠BUY OUR MERCH, PLZ:⁠ ⁠⁠https://www.redbubble.com/people/OfTheEldestGods/shop⁠Charlie's IG: ⁠ www.instagram.com/greenpixie12/⁠ and⁠ www.instagram.com/greenpixiedraws/⁠ Charlie's Plug: Haley Whipjack (YouTuber)Raye's Plug: Euro Brady (YouTuber)

Dr. Satyajit Wattamwar is a Data Science & Digital Expertise Leader with over 17 years of professional experience in enabling digital transformation across manufacturing, R&D, and innovation processes. He currently leads the development of in-house cloud AI platforms and data science technologies for cross-country, cross-functional business initiatives. His expertise spans predictive modeling, IoT analytics, advanced process control, and manufacturing analytics.On The Menu:Data scientist empowerment through AI-powered digital assistantsScaling digital solutions across 180+ global factoriesIndustry 4.0 ROI measurement strategies and KPIsDigital twin technology revolutionizing manufacturing operationsQuantum computing's potential impact on process optimizationExplainable AI methodologies for industrial safety applicationsSupply chain optimization using predictive data science

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

Last year, 1 in 10 U.S. babies was born before 37 weeks of pregnancy, which is considered preterm. That’s one of the highest premature birth rates among developed nations, according to the March of Dimes. We hear from parents of preterm babies about their experiences, and Ali Rogin speaks with an entrepreneur who’s using AI to help doctors predict when preterm births are likely. PBS News is supported by - https://www.pbs.org/newshour/about/funders. Hosted on Acast. See acast.com/privacy

Last year, 1 in 10 U.S. babies was born before 37 weeks of pregnancy, which is considered preterm. That’s one of the highest premature birth rates among developed nations, according to the March of Dimes. We hear from parents of preterm babies about their experiences, and Ali Rogin speaks with an entrepreneur who’s using AI to help doctors predict when preterm births are likely. PBS News is supported by - https://www.pbs.org/newshour/about/funders. Hosted on Acast. See acast.com/privacy

Strap in. This one's long.

12.5.25 Hour 2, Kevin Sheehan and Producer Max go around the NFL to preview and predict the week 14 slate of games on Sunday. Kevin Sheehan gives you his College Football and NFL smell test picks for this weekend of games.

Let's get lots of spoken practice with verbs Andar and Regresar, as well as our new nouns, numbers, and everything else we've learned this week. Predict the Spanish and speak out loud! Practice all of today's Spanish for free at LCSPodcast.com/205

Bass After Dark — inch for inch and pound for pound, the best show in fishing — is back for another lively, and LIVE, episode. Don't miss Ken Duke, Brian the Carpenter, and our mystery panelists (spoiler alert: it's Matt Pangrac, Andrew Hayes, Bryce Atchison, and Drew Gill) in a slightly different format for a very special 100th episode!

The start of a new round! Let's Predict!

“Can a dog really predict NFL games better than the experts?” That's the hilarious question that kicks off today's episode of The Ben and Skin Show, and trust us—you'll want to hear where this goes. Ben Rogers, Jeff “Skin” Wade, Kevin “KT” Turner, and Krystina Ray bring you a jam-packed show full of sports, laughs, and jaw-dropping theories.Here's what's inside:Poppy the Puppy's shocking pick: The Fox 4 canine sensation makes its call for   Cowboys vs. Lions—and it's not what you want to hear.Cowboys game day breakdown: Why tonight's matchup matters and the injury news that could shake up the NFC East.Ben's Mavericks bombshell: Is Jason Kidd secretly sabotaging Nico Harrison to take over as GM? Ben lays out his wild theory—and it might make more sense than you think.Mavs momentum: Anthony Davis is healthy, Cooper Flagg is clutch, and Ryan Nembhard is running the show. Is it too late to tank? Or is this team ready to make a run?

What if legacy security cameras already installed at distribution centers and warehouses could do more than just record footage? What if they could also prevent spoiled food from reaching grocery stores or catch cargo errors or even theft before it happens?That's the vision driving Technova Industries, a company transforming how the logistics industry handles cold chain verification. On this episode of Predict & Prevent, host Pete Miller, CEO of The Institutes, sits down with Aymen Azim, co-founder and CEO, and Jenna Azim, co-founder and Chief Marketing Officer, to explore how their AI-powered technology is breathing new life into legacy security systems.The conversation covers how generative AI has dramatically improved the accuracy of visual verification, why this approach solves liability challenges for shippers and insurers alike, and where the technology is headed. From preventing spoiled vaccines from reaching pharmacies to detecting potential cargo theft through USDOT number verification, Aymen and Jenna share their vision for creating continuous visibility checkpoints throughout the entire cold chain—including truck stops during transit.Resources:Technova Industries: https://www.technova-industries.com/ The Institutes: https://global.theinstitutes.org/Predict & Prevent website: https://www.predictandprevent.org/Sign up for our weekly Predict & Prevent newsletter: https://www.predictandprevent.org/newsletter/

Brad Evans & PJ Glasser break down their favorite prop bets for NFL Week 14.

12.3.25, Tim Murray from VSIN joins The Kevin Sheehan Show to discuss the College Football Playoff rankings, which teams should get in and the difficulties of finalizing the seeding.

Small and mid-sized businesses face increasing pressure to integrate visual and written content strategies. Helen Pollitt, content strategist at iStock with expertise in enterprise visual content optimization, challenges the traditional separation between content formats. She advocates for breaking down barriers between written, visual, and video content to create holistic content strategies that match audience intent rather than defaulting to format-specific approaches.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week we're replaying our favorite shows about winged mammals. In this episode from November 2020, researchers at Johns Hopkins University say bats can essentially “hear” into the future to find food. Plus: when The MTV European Music Awards let fans vote on the internet for Best Act Ever, the internet Rickrolled music history. Hearing the Future (Johns Hopkins University)MTV EMAs name Rick Astley ‘Best Act Ever' (NME)Cool Weird Awesome will never give its Patreon backers up, will never let them down… 

Gaming hosts Josh, Ryan and Ace are diving into the biggest twists, shocks, and “no way that just happened” moments that have hit the gaming world—and even our own podcast. From unexpected breakout hits to wild industry shakeups, we're breaking down the surprises that had us rewinding trailers, double-checking headlines, and questioning everything we thought we knew about video games. Whether it was a sleeper indie that stole the spotlight, a major studio making the boldest move of the year, or a moment on the show none of us saw coming, we're covering it all. If you love video games that keep you guessing and a podcast crew that's always ready for a good plot twist, this is the episode for you. Don't miss this jam-packed, unpredictably fun celebration of the year's most shocking stories in gaming—only on the Video Gamers Podcast!   Thanks to our MYTHIC Supporters: Redletter, Disratory, Ol' Jake, Gaius, Jigglepuf, Phelps and NorwegianGreaser   Thanks to our Legendary Supporters: HypnoticPyro, PeopleWonder and Bobby S.   Connect with the show: Support us on Patreon: ⁠patreon.com/videogamerspod⁠ Join our Gaming Community: https://discord.gg/vgp Follow us on Instagram:⁠ https://www.instagram.com/videogamerspod/⁠  Follow us on X:⁠ https://twitter.com/VideoGamersPod⁠  Subscribe to us on YouTube:⁠ ⁠⁠https://www.youtube.com/@VideoGamersPod?sub_confirmation=1⁠    Visit us on the web:⁠https://videogamerspod.com/⁠   Learn more about your ad choices. Visit megaphone.fm/adchoices

Joe, Hugh and Kyle play another round of Kiss the Baby, where they and one caller try to predict the NFL playoff bracket one week at a time.

We review the results from Zscaler (ZS) and Workday (WDAY) and predict which stock is more likely to outperform over the next 10 years. Who ya got? Asit Sharma, David Meier, and Tim Beyers: - Review last week's results from Zscaler and Workday. - Predict which of the two will outperform more over the next 10 years. - Tackle investors' pressing Mindset questions. Have a Mindset question you'd want answered on a future show? Reach out to Tim at tbeyers@fool.com. Don't wait! Be sure to get to your local bookstore and pick up a copy of David's Gardner's new book — Rule Breaker Investing: How to Pick the Best Stocks of the Future and Build Lasting Wealth. It's on shelves now; get it before it's gone! Companies discussed: ZS, WDAY Host: Tim Beyers Guests: Asit Sharma, David Meier Producer: Anand Chokkavelu Engineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

This week, we're giving you our full predictions for The Game Awards 2025! Join us as we predict the winners of each and every category, along with some predictions for a few of the surprises the show may have in store, on this week's hgo podcast.Thank you to Brandon Knight for sponsoring this video! His new novel "Zombies Ate My Staff Sergeant" is out right now on Amazon. What would you do in the event of a zombie apocalypse? Join Hayden Steel on his journey by checking out the novel here: https://a.co/d/4Em0tuE Timestamps:00:00:00 - Intro00:04:20 - Game Awards 2025 Winner Predictions00:07:00 - Most Anticipated Game00:11:00 - Best Adaptation00:15:00 - Best Multiplayer Game00:17:30 - Best Sports / Racing Game - check local 00:22:00 - Best Sim / Strategy Game00:26:00 - Best Family Game00:29:00 - Sponsor: Zombies Ate My Staff Sergeant00:29:30 - Best Fighting Game00:31:30 - Best RPG00:35:00 - Best Action / Adventure Game00:37:30 - Best Action Game00:40:00 - Best VR / AR Game00:43:30 - Best Mobile Game00:46:00 - Best Debut Indie Game00:53:30 - Best Indie Game00:58:30 - Best Community Support01:02:30 - Best Ongoing Game01:04:30 - Games for Impact01:10:30 - Innovation in Accessibility01:13:30 - Best Performance01:23:30 - Best Audio Design01:27:00 - Best Score and Music01:32:30 - Best Art Direction01:34:30 - Best Narrative01:37:30 - Best Game Direction01:44:30 - Game of the Year01:53:30 - Game Awards 2025 Reveal Predictions02:16:30 - OutroRemember to follow us on twitter at @hotgamersonly and subscribe to our youtube channel for the video version at youtube.com/hotgamersonly. You can also follow the boys on twitter/bluesky: Ethan @ChaoticAether, Hunter @ReaperHunter23 and Kyle @KDavisSRL.Be sure to also follow us on your favorite podcast service and we greatly appreciate anyone who leaves a review!

Bureau of Meteorology Website Renovation Fails — Jeremy Zakis — Zakis reported on the Australian Bureau of Meteorology (BOM), which failed to accurately predict the La Niña weather cycle and subsequent rainfall patterns. A $96.5 million website renovation project resulted in a broken, non-intuitive digital platform that systematically downplayed rainfall severity in visual representations. The project's exorbitant cost, attributed partly to expensive consulting fees and extensive testing protocols, has prompted investigation by the Australian federal government regarding waste and contract oversight. 1913 BRISBANE

AI sounds like a shortcut until your “great” ideas flop in the wild, and that is exactly what Jay Schwedelson digs into here. He breaks down a simple 100,000 person prompt that quietly flips AI out of generic creative mode and into deeper statistical thinking, then shares what happened when he A/B tested it on subject lines and CTAs. Plus, a surprisingly relatable question about hating phone calls turns into a legit strategy for staying connected without awkward calls or endless text threads.ㅤBest Moments:(01:00) Alyssa from Denver asks why AI generated ideas keep underperforming, and Jay flags the hidden problem with how most of us prompt these tools.(01:47) Jay introduces the 100,000 person prompt and shows how to ask AI to simulate huge audiences reacting to subject lines, landing pages, and offers.(03:05) Jay explains how framing prompts around 100,000 real people forces AI out of pure creativity and into deeper statistical mode for sharper recommendations.(03:45) Jay shares A/B test results where 100,000 person prompts beat generic AI suggestions over 70 percent of the time and even double click throughs on CTA buttons.(05:15) Jared from Dallas admits he hates phone calls and finds texting shallow, and Jay gets real about how easy it is to drift into isolation.(06:00) Jay reveals his go to solution of voice memos as a low pressure, high connection way to maintain relationships without live calls or walls of text.ㅤPrompts mentioned:Predict how 100,000 real subscribers would respond to each of these subject lines, rank them by expected open rate, and explain the psychology.Evaluate this hero section as if 100,000 new visitors landed on this landing page. Identify confusion points and drop-off risks.How would 100,000 consumer buyers or 100,000 B2B buyers interpret this offer? What is confusing, what is strong, and what is missing?We want you to simulate 100,000 people interacting with this call-to-action button. What should the language be?ㅤCheck out Jay's YOUTUBE Channel: https://www.youtube.com/@schwedelsonCheck out Jay's TIKTOK: https://www.tiktok.com/@schwedelsonCheck Out Jay's INSTAGRAM: https://www.instagram.com/jayschwedelson/