Podcasts about Token

What happens when an AI experiment becomes a production service that your employees, customers, and daily operations depend upon? In this episode of Tech Talks Daily, I speak with Brian Klingbeil, Chief Strategy Officer at Ensono, about AI infrastructure resilience, operational dependency, FinOps, legacy modernization, and the growing pressure to prove that enterprise AI investments are producing meaningful returns. Brian has been speaking with major enterprises through Ensono's Executive Advisory Council. Three years ago, many participants were experimenting with proofs of concept. Today, they are being asked to present AI projects that are already in production, approaching production, or demonstrating a clear return through productivity, lower risk, service quality, or financial results. That progression creates a new problem. When an AI model begins supporting product delivery, customer service, logistics, software development, or internal operations, it becomes part of the company's operating infrastructure. Leaders must then ask familiar IT questions about availability, monitoring, security, incident response, disaster recovery, ownership, and cost. Brian believes FinOps often provides the first warning. Token consumption can be difficult for CFOs and business leaders to interpret, particularly when hundreds of agents are operating across different models. Ensono's internal platform has produced around 1,000 agents, prompting questions about which are effective, which are expensive, and who should carry the cost. We discuss why chargeback and showback could change employee behavior. When AI spending is absorbed by a central corporate budget, teams may have little reason to question whether an expensive model is suitable for a routine task. When the cost reaches their departmental budget, the decision can look very different. Architecture also matters. Brian recommends systems that are loosely coupled and tightly integrated. Companies should be able to replace a model, provider, FinOps tool, or service as the market changes, while still connecting each component closely enough to deliver useful business outcomes. That creates a genuine tradeoff. Providers such as Microsoft, Amazon, Google, OpenAI, and Anthropic can offer specialist capabilities that businesses may want to use. Avoiding every provider specific feature can limit what the technology delivers, while becoming too dependent on one provider can make future change expensive and disruptive. The conversation then turns toward legacy technology. Brian argues that many systems described as outdated still process airline reservations, banking transactions, insurance claims, government services, and other high volume workloads. Turning them off without suitable replacements would create far bigger problems than the word "legacy" suggests. AI can change the modernization decision. Ensono worked with Markerstudy Group to analyze six million lines of RPG code running on an IBM i platform. The resulting plan identified applications that should move elsewhere while preserving workloads that still benefited from the platform's reliability and transaction processing capabilities. Brian treats migration as one possible part of modernization. AI tools can document old code, support modern development environments, and allow younger developers to work with established platforms without immediately beginning a lengthy and expensive replacement program. We also discuss Ensono's use of AI operations. Brian says the company reduced mean time to repair by 50% while processing approximately 50,000 tickets each month. The example shows how AI value can be measured through service quality and operational performance rather than relying entirely on direct revenue. The result is a balanced conversation about moving quickly while building enough control to keep AI dependable. Organizations need space for experimentation, but production services also require ownership, budgets, recovery planning, and people who know what to do when something fails. If one AI model or provider disappeared tomorrow, how much of your business would stop working? Listen to the episode and share your thoughts with me.

Most companies are not short on data. They are short on the time, cost, and coordination required to turn it into action.Ethan Ding, co founder and CEO of TextQL, joins The Tech Trek to explain how AI agents are changing enterprise analytics. The conversation moves beyond faster dashboards into a larger shift, analysts managing fleets of agents, business teams asking far more questions, and companies finding revenue and cost opportunities that were previously too expensive to pursue.What Technical Teams Can Take From This• Making answers cheaper does not reduce analytics work. It increases the number of questions people ask.• Analysts may spend less time assembling dashboards and more time managing agents, data sources, permissions, quality, and costs.• The clearest ROI comes from decisions with direct financial outcomes, including fraud prevention, upsell opportunities, churn risk, and unused vendor spend.• Faster analysis matters most when teams can act on valuable opportunities they previously could not afford to investigate.• Token costs will force AI companies and buyers to reconsider where software budgets go, especially across BI tools and data platforms.Moments Worth Hearing00:00 Ethan explains how TextQL agents work across messy enterprise systems including Cognos, Teradata, Snowflake, Databricks, Tableau, and Power BI.04:52 Why giving people faster answers does not create free time. It creates even more demand for analytics07:10 How self service analytics quickly moves from asking what a number is to asking whether it matters and what to do next.10:08 The analyst role shifts toward managing fleets of agents and tuning an insight factory for the business.14:38 Why faster access to data can reveal valuable opportunities that were previously too expensive to investigate.19:55 A practical way to measure analytics ROI through fraud prevention, upsell opportunities, and other direct financial outcomes.24:18 How token costs, AI margins, and easier migrations could reshape spending on traditional BI tools.One Line That Stuck“It becomes much more of an operations manager job. It is a factory. It takes in tokens and churns out dashboards, reports, and recommendations.”Follow The Tech Trek on your podcast platform, subscribe for future episodes, and share this conversation with someone rethinking how their team works with data.

This week, Chad has another run-in with the law and Cy flies home. Sign up for Chad's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠texting list here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Or, text the word CHAD to 208-379-6947! Sign up for Cy's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠texting list here!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Or⁠, text the word SHOW to 202-771-5171! This episode is brought to you by ⁠⁠⁠⁠⁠⁠BetterHelp⁠⁠⁠⁠⁠ and ⁠Chime⁠! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --- Follow us on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! Chad Daniels (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@ThatChadDaniels⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠) is a Dad, Comedian, and pancake lover. With over 750 million streams of his 5 albums to date, his audio plays are in the 99th percentile in comedy and music on Pandora alone, averaging over 1MM per week. Chad's previous album, Footprints on the Moon was the most streamed comedy album of 2017, and he has 6 late-night appearances and a Comedy Central Half Hour under his belt. Cy Amundson (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CyAmundson⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠) With appearances on Conan, Adam Devine's House Party, and Comedy Central's This is Not Happening, Cy Amundson is fast-proving himself in the world of standup comedy. After cutting his teeth at Acme Comedy Company in Minneapolis, has since appeared on Family Guy and American Dad and as a host on ESPN's SportsCenter on Snapchat. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Lin Qiao is the Co-Founder and CEO of Fireworks AI, the leading specialized intelligence and AI inference platform that last week raised $1.5BN at a whopping $17BN valuation. With just 200 people, the company has hit $1BN in ARR and expects to hit $2BN before the end of the year. Prior to Fireworks, Lin spent several years at Meta including on the founding team of PyTorch.  AGENDA: 00:07 — Why Did Fireworks Bet on Inference When Everyone Else Was Chasing Training? 00:13 — Can Open-Source Models Turn AI Infrastructure into a Commodity? 00:19 — Should Enterprises Trust Chinese Open Models With Their Most Sensitive Data? 00:25 — Will Model Progress Keep Moving This Fast—or Are We Nearing a Plateau? 00:28 — Will the Multi-Model World Create a $100BN Routing Layer? 00:37 — How Much Will AI Token Usage Explode Over the Next Two Years? 00:43 — Will Token Costs Fall 10x—and Unleash 100x More Demand? 00:49 — Does Fireworks Eventually Have to Build Its Own Data Centres? 01:02 — What Is the Real Bottleneck Holding Back the AI Economy?  

For generations, the narrative sold Black folks a dangerous promise: proximity to whiteness equals safety. But stepping into a primarily white space without a safety net of your own people isn't progress, it's exposure.From the 1841 capture of Solomon Northup to the 1936 creation of the Green Book, history has repeatedly proven the fatal reality of being the "only one." Today, the tragic case of Nolan Wells reminds us why that nagging anxiety in a room full of white faces isn't paranoia. It is a highly evolved survival instinct forged by a history of betrayal.Sources:Twelve Years a Slave by Solomon NorthupThe Negro Motorist Green Book by Victor Hugo GreenSundown Towns by James W. Loewen

In dieser Episode spricht Erik Siekmann mit Sebastian Denef, Mitgründer und CEO von AGENTS.inc, über den Einzug von autonomen KI-Agenten im Marketing und die Abgrenzung von Hype und Realität. Sebastian erklärt, warum herkömmliche Copiloten oft nur reaktive „Anstupser-Systeme“ sind und wie echte, vollautonome Agenten im Hintergrund arbeiten, während wir schlafen. Ein Highlight der Folge ist der tiefe Einblick in das Thema „Enterprise Agents“: AGENTS.inc widmet sich bereits seit 2016 – lange vor dem aktuellen Hype – ausschließlich hochgradig kontrollierten Agenten-Infrastrukturen. Erfahre, wie Unternehmen durch vollautonomes Monitoring globale Märkte und Kontexte in Echtzeit analysieren, warum einfache Prompts bei ChatGPT für geschäftliche Zwecke scheitern und wie KI-Agenten heute sogar hochkomplexe Werbematerialien bis hin zu druckfertigen Adobe InDesign-Layouts völlig selbstständig generieren. Über Sebastian Denef: Sebastian Denef ist Mitgründer und CEO von AGENTS.inc, einem Pionier-Unternehmen für KI-Agenten, das er aus seiner Forschungsarbeit am Fraunhofer-Institut heraus gründete. Seit vielen Jahren erforscht er die Human-Computer-Interaction und die Zukunft der Arbeit. Sebastian gilt als absoluter Vordenker im Bereich der Mensch-Maschine-Kollaboration und ist Autor des zukunftsweisenden Buchs „The Last Boss: How AI Agents Will Unlock Artificial General Intelligence“. Sein pragmatischer Ansatz bei AGENTS.inc zeigt, wie Unternehmen komplexe Datenströme bändigen, Halluzinationen in Geschäftsprozessen durch kontrollierte Agent-Workflows eliminieren und echte Software-Autonomie gewinnbringend im Enterprise-Alltag etablieren können. Der Marketing Transformation Podcast wird produziert von TLDR Studios.

Bei lokalen KI-Modellen muss man nicht jedes Token auf die Goldwaage legen. Statt teurer Abos für KI-Dienste, fallen leichter zu überblickende Hardware- und Stromkosten an. Wir sprechen darüber, was mit einem lokalen KI-Server für privat oder kleine Teams möglich ist, welche Hardware man dafür braucht und welche coolen Dinge man damit tun kann.

Egal ob man gern ausufernde Gespräche mit einem Chatbot führt, jede Menge Bilder generiert oder Programmierprojekte mit KI umsetzen will: Die Token schwinden wie Eis in der Sonne und das Ganze geht schnell ins Geld. Mal ganz abgesehen davon, dass gerade im beruflichen Kontext Vorsicht geboten ist, welche Daten man an die Onlinedienste weitergibt. Lokale KI-Modelle sind da die deutlich bessere Wahl: Die Kosten sind besser kalkulierbar, weil man nur in Hardware investieren und kein Abo bei KI-Firmen abschließen muss. So muss man nicht mehr jedes Token auf die Goldwaage legen. Und um den versehentlichen Abfluss von Daten braucht man sich dann auch keine Sorgen machen. In dieser Folge des c't uplink sprechen wir darüber, was mit einem lokalen KI-Server möglich ist, ab welcher Hardware das Spaß macht und welche coolen Dinge ein solcher KI-Server tun kann. Jan Mahn berichtet von seinen Erfahrungen beim [Aufsetzen eines LLM-Servers für kleine Teams](https://www.heise.de/ratgeber/Sprachmodelle-mit-Open-WebUI-LLM-Server-fuer-kleine-Teams-selbst-hosten-11333185.html), während Jan-Keno Janssen für ein c't-3003-Video mit agentischer KI experimentiert hat. Zu Gast im Studio: Jan Mahn, Jan-Keno Janssen Host: Liane M. Dubowy Produktion: Tobias Reimer ► Mitdiskutieren auf dem heise & c't Discord-Server: https://discord.gg/Wf6ewnWpxH ► c't Magazin: https://ct.de ► c't auf Mastodon: https://social.heise.de/@ct_Magazin ► c't auf Instagram: https://www.instagram.com/ct_magazin ► c't auf Facebook: https://www.facebook.com/ctmagazin ► c't auf Bluesky: https://bsky.app/profile/ct.de ► c't auf Papier: überall wo es Zeitschriften gibt!

Egal ob man gern ausufernde Gespräche mit einem Chatbot führt, jede Menge Bilder generiert oder Programmierprojekte mit KI umsetzen will: Die Token schwinden wie Eis in der Sonne und das Ganze geht schnell ins Geld. Mal ganz abgesehen davon, dass gerade im beruflichen Kontext Vorsicht geboten ist, welche Daten man an die Onlinedienste weitergibt. Lokale KI-Modelle sind da die deutlich bessere Wahl: Die Kosten sind besser kalkulierbar, weil man nur in Hardware investieren und kein Abo bei KI-Firmen abschließen muss. So muss man nicht mehr jedes Token auf die Goldwaage legen. Und um den versehentlichen Abfluss von Daten braucht man sich dann auch keine Sorgen machen. In dieser Folge des c't uplink sprechen wir darüber, was mit einem lokalen KI-Server möglich ist, ab welcher Hardware das Spaß macht und welche coolen Dinge ein solcher KI-Server tun kann. Jan Mahn berichtet von seinen Erfahrungen beim [Aufsetzen eines LLM-Servers für kleine Teams](https://www.heise.de/ratgeber/Sprachmodelle-mit-Open-WebUI-LLM-Server-fuer-kleine-Teams-selbst-hosten-11333185.html), während Jan-Keno Janssen für ein c't-3003-Video mit agentischer KI experimentiert hat. Zu Gast im Studio: Jan Mahn, Jan-Keno Janssen Host: Liane M. Dubowy Produktion: Tobias Reimer ► Mitdiskutieren auf dem heise & c't Discord-Server: https://discord.gg/Wf6ewnWpxH ► c't Magazin: https://ct.de ► c't auf Mastodon: https://social.heise.de/@ct_Magazin ► c't auf Instagram: https://www.instagram.com/ct_magazin ► c't auf Facebook: https://www.facebook.com/ctmagazin ► c't auf Bluesky: https://bsky.app/profile/ct.de ► c't auf Papier: überall wo es Zeitschriften gibt!

Ramez Naam is an investor at Planetary VC and a longtime clean energy and AI expert. In this conversation, we break down the energy bottleneck constraining AI growth — from gas turbines and batteries to floating ocean data centers and Elon's orbital data center ambitions. We also cover why bitcoin miners are pivoting to AI infrastructure, general vs. narrow superintelligence, and the data bottleneck reshaping AI training.====================Turn every conversation into a searchable business asset with PLAUD NotePro. Visit https://Plaud.ai/pomp  and use code POMP for 15% off.====================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp====================Uphold is the easiest way to buy and sell crypto unlike any other platform allowing you to trade in just one step between any supported asset. Check them out at https://www.uphold.com/pomp/ This video includes a paid sponsorship with Uphold. I'm compensated by Uphold for promoting its products and services and may receive commissions from referrals. Terms apply. Not available in all jurisdictions. Digital assets are risky and may result in the total loss of your capital.====================0:00 - Intro1:03 - Why power is the real bottleneck for AI & solutions7:35 - Elon's orbital data center thesis11:17 - Cooling & maintenance challenges in space15:06 - Panthalassa: floating ocean data centers19:16 - Base Power & Texas deregulated grid21:30 - Giga Energy: from bitcoin mining to AI infrastructure22:44 - American Consolidated Electric & supple chain bottlenecks24:58 - General vs. narrow superintelligence33:02 - Where untapped data lives & building a data moat36:47 - Token costs, open source models & model routing41:53 - What is the mission Ramez is going after?

The episode highlights a shift from technology selection to operational risk management in the AI landscape for MSPs. Service providers are being forced to navigate the fast-changing interplay between AI models, the harness software that mediates their deployment, and the financial realities of consumption-based billing. The rapid proliferation of open-source and open-weight AI models, alongside market behaviors from closed vendors and regulatory interventions, is introducing volatility and uncertainty in both cost structures and client offerings. This dynamic creates structural challenges related to margin maintenance, vendor dependency, and responsibility for AI-driven decisions. The discussion cites the release of GLM 5.2, an open-weight model from Z AI, which now rivals expensive closed models on key benchmarks at a fraction of the cost. At the same time, large-scale investments by commercial AI vendors have yet to deliver returns on expectations, with reports indicating businesses that adopted AI are not seeing projected value. Specific attention is given to operational constraints such as compute scarcity, token consumption variability, and export policy restrictions impacting AI availability. The episode notes that these pressures are driving both vendors and MSPs to reconsider the viability of reliance on expensive, closed offerings versus investigating open alternatives. Supportive examples include the proliferation of AI “harnesses” (middleware layers like Perplexity, Claude Code, and Cowork) that sit between service providers and underlying AI models, increasing both choice and complexity. Token billing models are highlighted as a source of unpredictability for MSPs, with vendors like Atera and ConnectWise experimenting with different abstractions to shield or pass through token risk to service providers. The potential for on-premises AI deployments using smaller language models is discussed as a cost-mitigation strategy, though this raises further questions about data privacy, infrastructure burden, and long-term vendor roles. Additionally, uncertainty is flagged around sustainability of leading vendors, with projections that at least one major AI player may exit or be acquired within a year due to financial vulnerability. For MSPs and IT service leaders, these structural and supporting developments translate into increased operational and financial complexity. There is a pressing need to evaluate not just which AI technologies to adopt, but how to architect solutions that can withstand rapid vendor movement, cost swings, and evolving regulatory requirements. Practical safeguards include testing open-source AI models alongside commercial offerings, exercising caution in vendor selection, and closely monitoring evolving consumption billing models. Preparing staff and clients for adaptive, process-oriented approaches—rather than fixed solutions—is positioned as a necessary step to maintain resilience as the AI adoption cycle continues to correct course. Supported by:Pax8CometBackupGuardz

RevokeCash introduces auto-revoking. Francesco leaves the Ethereum Foundation to join Ethlabs. DV Labs winds down its Aztec sequencer. And Ostium suffers a $23m hack. Read more: https://ethdaily.io/991 ETH Daily sponsorships are now open. Reach over 10,000 Ethereum-native subscribers every weekday. Learn more at ethdaily.io/ads  Disclaimer: Content is for informational purposes only, not endorsement or investment advice. The accuracy of information is not guaranteed.

My guest this week is Scott Billington.Scott is a Grammy winning record producer, an author, a record company exec and a musician. But what we're chatting about in this episode is a fascinating story about a pivotal string band album and it's journey to being reissued with extra tracks that went missing for decades.The record in question is Boone Creek's debut album Boone Creek, from the band Jerry Douglas and Ricky Skaggs formed after they left J.D. Crowe and the New South.Scott talks about how the album was recorded and how, at the time, Rounder felt it was too progressive, and asked the band to go back into the studio and record some additional tracks. After the album was released, the original tapes went missing and Rounder were keen not to reissue it on CD or streaming services until they'd been found. As a result, the record disappeared from circulation for years.We talk about how the tapes were finally unearthed, what state they were in, the process used to retrieve what was on them and how Boone Creek was finally reissued by Craft Recordings.We also chat about Scott's long career with Rounder Records and his current role with Craft Recordings, working on several key projects, including the Doc Watson A Life's Work box set. This was a fascinating conversation about a fascinating project, as well as Scott's long association with outstanding American roots music.Next week's episode will feature an interview with Jerry Douglas about Boone Creek, his memories of that band and what it was like hearing the reissued tracks everyone thought had been lost for good.You can buy Boone Creek from Craft Recordings on vinyl, CD or digital downloadFollow Craft on Instagram or Facebook to keep up to date with new reissues of classic roots music.For more info on Scott, including links to buy his book Making Tracks: A Record Producer's Southern Roots Music Journey, check out www.scottbillington.comMatt Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

AI can generate code faster, but that does not make software delivery simple. It shifts the pressure to requirements, architecture, review, and technical judgment.Goncalo Silva, CTO at Doist, explains how AI is changing the way teams behind Todoist and Twist build software. He shares why greater individual autonomy has led to more collaboration, why deep expertise still matters, and how faster execution is reshaping product delivery, project planning, and engineering hiring.What Leaders Can Take From This• Faster code generation makes strong planning and clear requirements more important, not less important.• Designers, product leaders, and engineers can work from richer prototypes, but production systems still need experienced technical judgment.• Engineering capacity does not have to move into other functions. Teams can use it to improve reliability, performance, quality, and the amount of valuable work they ship.• Token counts are a weak measure of progress. Doist looks at team feedback and whether projects are staying on track.• Engineering interviews need to test architecture, decision making, curiosity, and depth, not simply whether a candidate can produce working code.Approximate Highlights00:00 Meet GonCalo Silva and the products behind Doist02:00 How broadly AI is being used across Doist04:15 Why greater autonomy has brought teams closer together09:45 Where nontechnical coding works, and where it creates risk17:50 How AI compressed a major refactoring effort by 20 to 30 times25:05 Measuring AI value without counting tokens30:20 Why faster execution requires more up front planning34:50 How Doist changed its engineering interview processOne Line That Stuck“We are the bottleneck. Our attention span, our ability to memorize, our ability to understand, and deep expertise.”Follow The Tech Trek for more conversations on how technical teams are changing the way they build, hire, and operate.

Mastodon announces their first album since losing Brent Hinds — and it comes with a surprise Josh Homme cameo. Sleep Token keeps racking up RIAA hardware, with "Caramel" going platinum and "Dangerous" going gold. And we've got a genuinely great health update from Coal Chamber drummer Mikey "Bug" Cox after his latest cancer surgery. In this episode: [0:00] Intro [0:25] Mastodon announce "Marrow Deep," out August 28 — first album since Brent Hinds' passing, featuring Josh Homme's first Mastodon appearance since 2006 [1:30] Sleep Token's "Caramel" goes platinum, "Dangerous" goes gold — the latest in a string of RIAA certifications for "Even In Arcadia" [2:30] Coal Chamber's Mikey Cox shares a hopeful update after what's hopefully his final cancer-related surgery [3:50] Wrap-up New episodes of Metal Breakdown Daily drop every weekday morning. Subscribe so you don't miss the next one, and follow Loaded Radio at loadedradio.com and across Facebook, Instagram, and TikTok for daily hard rock and heavy metal news.

In this episode of Run the Numbers, CJ sits down with Rogo president Rahul Rekhi to unpack what AI actually changes in investment banking and finance. They dig into token economics, why adoption without ROI is a trap, how vertical AI wins, and why domain expertise still matter.—SPONSORS:Pulley is an equity management platform that lets you issue options, model dilution, and complete 409As without your cap table turning into a spreadsheet disaster. Founders raising, hiring, and scaling use Pulley to keep equity clean and stay focused on building. Learn more or request a demo at https://pulley.com/mostlymetricsRillet is an AI-native ERP built for modern finance teams that want to replace NetSuite and close faster. With revenue recognition, close management, multi-entity support, and native Stripe and Salesforce integrations, Rillet helps scaling companies run their finance stack in one place. Hundreds of teams, including Windsurf and Mercor, use Rillet to make the zero-day close real. Book a demo at https://www.rillet.com/cjMaximor is an autonomous finance platform that runs order-to-cash, procure-to-pay, the close, cash management, and reporting on self-learning agents instead of a dozen disconnected tools. One PE-backed customer cut their close in half, took audit findings from seven to zero, and cut back-office costs by 70% in six months. You pay for outcomes, not seats. See it at https://www.maximor.ai/Brex is an intelligent finance platform with AI-powered agents that capture expenses automatically, enforce policy before the spend happens, and close your books in minutes instead of weeks. 35,000+ companies like OpenAI, Coinbase, Anthropic, and DoorDash already run on Brex. It's time to get Brex AF. Learn more at https://www.brex.com/metricsAnrok is the sales tax platform that watches your exposure everywhere, automates compliance, and flags risk before it turns into a surprise back-tax letter from a state you've never set foot in. Companies like Anthropic, Notion, and Vanta already trust Anrok to stay ahead of rules that move faster than any spreadsheet can. Talk to a sales tax expert for a personalized exposure estimate at https://www.anrok.com/rtnRightRev is an automated revenue recognition platform that lets your product team ship new pricing without asking finance for permission, and your sales team close deals without creating downstream chaos. Check out their free tool at calculator.rightrev.com It scores your rev rec process, shows what's exposing you to risk, and tells you exactly where to focus before it bites you in the rear end. Check it out at https://calculator.rightrev.com—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNGuest: https://www.linkedin.com/in/rahulrekhi/Company: https://www.rogo.ai/CJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:A CFO Explains the Stock Exchangeshttps://youtu.be/pooOE6ZNGR4A CFO Explains Marketplaceshttps://youtu.be/LpbH9GpBrSY—TIMESTAMPS:0:00 Preview and Intro2:44 Why finance was first to verticalize AI6:28 What the president title means at Rogo9:55 Sponsors — Pulley | Rillet | Maximor13:02 The problem Rogo is solving16:16 Token maxing is not transformation17:43 Why ROI is so hard to measure19:39 Sponsors — Brex | Anrok | RightRev22:37 ROI is business-unit specific24:03 Budgeting tokens like a benefits load25:00 AI incentives aren't aligned to efficiency26:26 The model broker function32:03 Not all token spend is equal37:14 Who owns AI efficiency?40:59 The forward deployed banker43:00 Domain expertise: the Interstellar analogy49:21 Lightning round49:28 Screwed up: DCF error in a live deal51:13 Will new grads have the spidey sense?53:03 Meeting Pope Francis55:04 Fact-checking jobs numbers at the White House57:39 Advice to younger self59:21 Credits

Can crypto finally solve the disconnect between product success and token value?This week, we explore why Venice AI's equity raise reignited the token-versus-equity debate, what it reveals about crypto capital formation, and why better disclosures may be the industry's next major unlock.We also discuss Strategy's recovery, Robinhood Chain's launch, Venice's AI growth, MetaDAO's ownership model, and which tokens could benefit most from the next wave of onchain adoption. Enjoy! TIMESTAMPS: 00:00 Intro 01:05 Bitcoin & Strategy Turning Bullish? 06:03 Venice AI's Growth Engine 10:53 The Demand For Private AI 15:35 Venice's Token Equity Divide 23:53 Crypto's Disclosure Problem 34:01 Do You Choose Token Or Equity? 37:51 Fixing Tokenholder Alignment 45:00 Robinhood Chain Arrives 57:25 Final Thoughts FOLLOW THE SHOW › 0xResearch – https://x.com/0xResearch › Luke – https://x.com/0xMether › Kunal – https://x.com/Kunallegendd › Carlos – https://x.com/0xcarlosg › Telegram – https://t.me/+UFFz4z3qyrhhMDYx › Blockworks – https://x.com/Blockworks Check out Blockworks Research today! Research, data, governance, tokenomics, and models – all in one place Blockworks Research: https://www.blockworksresearch.com/ Free Daily Newsletter: https://blockworks.co/newsletter EVENTS › Join us at Digital Asset Summit 2026 Asia October 7th & Digital Asset 2026 London November 10-11th https://blockworks.com/events Blockworks recently acquired Messari. For more information, please visit: https://blockworks.com/insights/blockworks-acquires-messari DISCLAIMER Nothing said on 0xResearch is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only. Any views expressed are opinions, not financial advice. Hosts and guests may hold positions in the companies, funds, or projects discussed.

In this recent episode of Possible, Reid Hoffman sits down with Microsoft CEO Satya Nadella fresh off Microsoft Build 2026. The conversation goes wide: how AI is reshaping work, business, and society—and why the transformation sweeping through software development today is only a preview of what's coming for all knowledge work. Satya makes the case that human capital and "token capital" are now deeply intertwined, that companies—not just countries—must build their own AI capabilities, and that the organizations best positioned to thrive are those that can leverage their unique expertise inside intelligent systems. Reid and Satya also explore Microsoft's enterprise AI vision, Reid's work with Manas on AI-powered scientific discovery, lessons from past technological revolutions, and why demonstrating real, tangible benefits may be the most important thing the industry can do to earn—and keep—the public's trust.You can catch and subscribe to more Possible here: https://www.possible.fm/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On today's show Andrew and Ben begin with a look at the state of Meta. Topics include: Mark Zuckerberg's sins of commission vs. omission as a messenger, Meta's AI opportunity, directionally correct investments, the problems with Meta as a cloud provider, and the absence of religion in Menlo Park. From there: Why Microsoft should move on from the XBOX era, and the shift in gaming habits that doomed Game Pass from the outset. At the end: OpenAI introduces GPT-Live, a question about the cost of Ben's vibe coding adventure spawns a digression on future token costs, the cost of youth sports, American soccer and learning Chinese, tech weirdos and the future of normie app building, and Ben gets castigated for bringing a Starlink on vacation.

Quarter-Bin Podcast #243Solo Avengers 7, cover-dated June 1988."Hijacked!" by Tom DeFalco, with art by M.D. Bright and Jose Marzan. and "The Token," by Bob Layton & Jackson Guice. What happens when Professor Alan invites Jason Alberich from the Longbox Crusade to to discuss issue 7 of Solo Avengers? Will Jason be able to overcome his Hawkeye fandom to judge the stories objectively? What business management lessons does the Professor see in the stories?Listen to the episode and find out!  Click on the player below to listen to the episode:  Right-click to download episode directly You may also subscribe to the podcast through iTunes or the RSS Feed. Link: The Longbox Crusade network Promo: The Monitor TapesNext Episode: Action Comics 502, DC Comics, cover-dated December 1979.Send e-mail feedback to relativelygeeky@gmail.com "Like" us on Facebook at https://www.facebook.com/relativelygeekyYou can follow the network on Twitter @Relatively_Geek and the host @ProfessorAlanYou can follow the network on  Bluesky @relativelygeeky.bsky.social  Source: World's Greatest ComicsMusic in the episode: Victorious Path, by AudioAtlant from Pixabay

Is the internet ready for AI agents to take over our wallets and run their own businesses? In this episode of The MAD Podcast, Stripe's Emily Sands reveals how agentic commerce is rapidly shifting from a hypothetical concept to deployed financial infrastructure. From combating the rising existential threat of token theft to solving the bottleneck of "vibe deployment", Emily unpacks the shared payment tokens and real-time billing systems required to securely scale autonomous digital buyers and highlights a near future where agents operate as independent, end-to-end micro-firms.(00:00) — Cold open & Intro(01:24) — The rise of agentic e-commerce(02:11) — The spectrum of agent-led purchases(03:16) — How merchants adapt to AI-driven commerce(05:50) — Defining the levels of autonomy in AI shopping(07:08) — What is the Agent E-Commerce Protocol (AEP)?(08:49) — Shared payment tokens and secure AI transactions(09:58) — Who is adopting the Agent E-Commerce Protocol?(11:38) — Can agents negotiate and sell products?(13:32) — The macroeconomic impact of AI agents(14:46) — The boom of solopreneurs and AI-driven business creation(16:56) — Why building trust is the biggest roadblock for AI commerce(20:19) — How link wallets improve payment security(21:21) — Improving the user experience in AI shopping apps(23:16) — How the Link Wallet sets guardrails for AI agents(25:40) — One-time use virtual cards vs flexible AI wallets(28:03) — Unpacking the shared payment token primitive(29:59) — How stablecoins enable profitable AI microtransactions(35:03) — Managing liability: Who is at fault if an agent goes haywire?(36:38) — Why agent payments might be safer than human transactions(37:41) — What is Vibe Deployment?(40:13) — Why Stripe built Stripe Projects for agent deployment(41:22) — Why Stripe cares about orchestrating app deployments(42:50) — How tokens break the traditional SaaS billing model(44:34) — Why AI companies are moving to hybrid and usage-based billing(47:15) — Streaming payments and real-time token tracking(48:42) — The massive data challenge for AI company accountants(50:41) — Token theft: The fastest-growing fraud in the AI economy(52:04) — The cottage industry of free trial and multi-account abuse(54:16) — How fraudsters monetize stolen AI tokens on the dark web(01:00:06) — How Stripe Radar uses network density to fight AI fraud(01:01:15) — Tempo's role in the Agent E-Commerce Protocol(01:04:12) — The AI startup ecosystem is accelerating business creation(01:09:01) — The token cost shock: Are buyers getting carried away?(01:11:19) — 2026 Predictions: Agents running businesses end-to-end

Control what you're billed on. Tokens are the currency of AI, and how you design your app determines how many you spend. Compress conversation history instead of resending it raw, cap output tokens with matching prompt instructions, and cache static context so each reuse costs a fraction of the first request. Route each prompt to the right model by complexity, or set Model Router in Microsoft Foundry to handle that automatically — balanced, quality, or cost mode. Then optimize the whole stack. Run Agent Optimizer to test your prompt, model, and tool configurations together and surface better setups. Use Toolbox to dynamically select only the tools each request needs and cut input token overhead by 90%.  April Gittens, Microsoft Principal Cloud Advocate, joins Jeremy Chapman, Microsoft 365 Director, to share how to seize control of AI token spend through smarter app design.  ► QUICK LINKS:  00:00 - Tokenomics foundation 01:06 - Token cost basics 02:11 - Context Window creep 03:46 - Reduce unnecessary tokens 04:29 - Trim context costs 05:21 - Cap output tokens 06:27 - Cache for savings 07:54 - Model cost tradeoffs 09:15 - Model Router 09:42 - Toolbox in Microsoft Foundry Toolbox 11:18 - Agent Optimizer 12:44 - Other cost drivers 13:57 - Wrap up ► Link References Check out the tools in Microsoft Foundry at https://ai.azure.com For more about managing AI costs go to https://aka.ms/FoundryTokenomics ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics

Jetzt bei Kraken anmelden und 30 EUR Bonus erhalten: https://bit.ly/kraken-bonusThemen & Timestamps:00:00 Begrüssung und Themenüberblick01:13 Iran: Waffenstillstand aufgehoben und Folgen für Bitcoin02:49 Strikes volatilitätssicheres Bitcoin-Kreditprodukt06:17 Base B20-Token-Standard und Barrel-Upgrade07:39 Vanguard sucht Head of Digital Assets

This is a special episode produced by the collaboration between TiE San Diego and Tantra's Mantra.In this episode, I speak to Mark Budgen of Lenovo and Rajnikant Gupta of TCS on the current status of AI adoption in enterprises. We start by discussing which segments and which functions within organizations have seen deeper adoption of AI, whether AI projects have moved from PoC and trials to production, what the major challenges are in that transition, how the thinking and approach of enterprises toward AI have changed over the short period, the need for “Human in the loop,” and the necessity of Hybrid AI. We discuss key takeaways from Lenovo's “CIO Playbook 2026” report and how enterprises are now more focused on improving and accelerating business outcomes rather than simply improving productivity.Finally, we delve into what to expect in the near and far future, moving from Generative and Agentic AI to Physical and Embodied AI.Index:00:00 - Intro01:05 - Guest intro (Mark Budgen, CTO, Global Technology Partners at Lenovo, & Rajnikant Gupta, Global Head - Partner Ecosystems and Alliances, TCS)02:28 - Current status of AI adoption in Enterprises, how AI can improve business, not just efficiency, risk considerations06:30 - Difference in level of AI adoption between various functional groups within Enterprises - IT, Coding, Security, Supply Chain, Sales & Marketing13:30 - Evolution of Human involvement in AI processes. Humans in the Agentic AI loop will be required for a long time, because of the risk of failure and its costs16:56 - Key takeaways from Lenovo's "CIO Playbook 2026" report: AI is not the entire toolbox, but one of the tools; focus is on how to use AI to improve and accelerate business and finally the outcomes; mapping IT KPIs to Business KPIs22:16 - Current status of AI projects, in "Production" vs. "PoC" or "Trials" stage. The majority still in the process of moving to Production. Execs now better understand their business value; Focus on platforms to scale rather than simple point solutions28:13 - Challenges in implementing AI: Employee fear of replacement, lack of domain experts with AI knowledge,31:56 - Hybrid AI: How to decide where to run AI: Cloud or Edge? Dependencies: Sovereignty, access to data, power, and cooling; Token use optimization38:27 - What to expect to see in the near and far future: Physical AI, Embodied AI, AI becoming ubiquitous and41:20 - Closing

Google fires the engineer behind its Workspace CLI tool, OpenAI previews GPT-5.6 with three new model tiers, and Astro 7 lands with a full Rust rewrite. Plus: Coinbase cuts token costs with smarter routing, and more in this week's Syntax Live Show Notes 00:00 Intro 00:34 Welcome to Syntax! 01:46 Google fires Workspace CLI Creator 12:30 GPT 5.6 Is Coming 19:59 GLM 5.2 Released 23:23 Astro 7 Rust Re-write 32:46 Cursor Announces iOS App 35:08 Scott's Workflow: Herdr + Mosh + Termius + Tailscale 40:33 Coinbase Reduces AI Cost with Model Routing 44:22 wayfinder-router - Local AI Routing CLI 48:16 Token efficiency in models and harnesses Martin Woodward on X 52:34 performativeUI - react components for AI startups 54:31 Brought to you by Sentry.io 55:21 Reachy Mini Robot 01:02:21 FUTO Keyboard Swipe for Android 01:05:40 CSS Quake 01:07:35 HTML Invoker API is Baseline Available 01:13:17 Cloudflare Temporary Accounts for AI Agents Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

VVV is down 50% on news that should be good for Venice. David unpacks why — covering the token vs. equity distinction, Dragonfly's reasoning, and what the onchain data says about how many people are actually using Venice's paid features right now. FOLLOW THE SHOW › David — https://x.com/dcanellis › The Breakdown — https://x.com/TheBreakdownBW › The Breakdown Newsletter — https://blockworks.com/newsletter/the-breakdown DISCLAIMER As always, remember this podcast is for informational purposes only, and any views expressed by anyone on the show are solely their opinions, not financial advice.

開盤前30分鐘，08:30 - 09:00 讓我們一起解讀財經時事 。 參加財經皓角總經訂閱： 新友會員 https://jackalopelin.com 老友會員 https://yutinghao.finance 我的粉絲專頁 https://reurl.cc/n563rd 網站參加會員手冊 https://reurl.cc/rvvqAr 如有疑問，歡迎來信 jackieyutw@gmail.com """"" ♥️ 打賞網址 ：https://p.ecpay.com.tw/B83478D """"" (不提供退款服務) 《早晨財經速解讀》是游庭皓的個人知識節目，針對財經時事做最新解讀，開播於2019年7月15日，每日開盤前半小時準時直播。議題從總體經濟、產業動態到投資哲學，信息量飽滿，為你顛覆直覺，清理投資誤區，用更寬廣的角度帶你一窺投資的奧秘。 免責聲明：《游庭皓的財經皓角》頻道為學習型頻道，僅用於教育與娛樂目的，無任何證券之買賣建議。任何形式的投資皆涉及風險，投資者需進行自己的研究，持盈保泰。

前陣子說Token消耗急升，現在卻有剩餘算力打包? 為什麼科技巨頭反手向小公司買算力? NeoCloud是如何成為十倍股? 是泡沫嗎? 一切都是老黃的陰謀!

Clay Bavor is the Co-Founder of Sierra, one of the world's fastest-growing enterprise AI companies. Sierra is valued at approximately $15.8 billion, has raised more than $1.5BN from leading investors including Sequoia, Benchmark, Greenoaks, GV and Tiger Global, and today serves more than 40% of the Fortune 50. The company recently surpassed $150 ARR, making it one of the fastest-growing enterprise software businesses in history. AGENDA: 00:00 – Why Frontier AI Demand Will Be Unlimited 08:00 – Open Models vs Frontier Models: Who Actually Wins? 17:00 – China's AI Advantage & The Distillation Debate 20:30 – Inside Sierra: The AI Agents Running the Entire Company 24:00 – The $100,000 Token Budget Every Engineer Will Soon Need 29:00 – Building AI for 40% of the Fortune 50 37:00 – Why Forward-Deployed Engineers Are the Future of Enterprise AI 43:00 – Sierra's Unusual Board Meetings & Billion-Dollar Company Playbook 48:00 – The Four Values Behind a $16B Startup: Craftsmanship, Intensity & Family 56:00 – Clay Bavor's Hiring Philosophy, AI-First Teams & What's Coming Next  

This week, we're back with another weekly roundup to discuss the announcement of OUSD and what it means for the future of Circle. We then deep dive into Robinhood's recent product launches, Venice's $65M raise, crypto's continued discussion around tokens vs. equity, and more. Enjoy! -- Follow Jason: https://x.com/JasonYanowitz Follow Rob: https://x.com/HadickM Follow Empire: https://x.com/theempirepod -- Robots will soon outnumber humans onchain. peaqOS turns them into a new trusted liquid asset class, with yield tied to real-world workloads. It gives robots all they need to do business on any chain — and lets humans earn from automation. Explore the Machine Economy: https://peaq.xyz -- Timestamps: (00:00) Introduction (02:52) Did Saylor End Strategy's Sell Off? (10:15) The Launch of OpenUSD (17:49) Should Everyone Launch A Stablecoin? (32:42) peaq Ad (33:28) Cloudflare's Monetization Gateway (38:35) Robinhood Launches A Chain (56:00) Venice Raises $65M & Crypto's Token vs Equity Problem (01:16:14) Content of The Week -- Disclaimer: Nothing said on Empire is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Santiago, Jason, Rob and our guests may hold positions in the companies, funds, or projects discussed.

In this episode of Run the Numbers, CJ goes live from Rillet Recon with Dana Decker (VP of Finance at Opendoor), AJ Ljubich (SVP, FP&A at Datadog), and Micah Richard (Principal, AI at PwC) to unpack how finance teams are actually using AI. —SPONSORS:Brex is an intelligent finance platform with AI-powered agents that capture expenses automatically, enforce policy before the spend happens, and close your books in minutes instead of weeks. 35,000+ companies like OpenAI, Coinbase, Anthropic, and DoorDash already run on Brex. It's time to get Brex AF. Learn more at https://www.brex.com/metricsAnrok is the sales tax platform that watches your exposure everywhere, automates compliance, and flags risk before it turns into a surprise back-tax letter from a state you've never set foot in. Companies like Anthropic, Notion, and Vanta already trust Anrok to stay ahead of rules that move faster than any spreadsheet can. Talk to a sales tax expert for a personalized exposure estimate at https://www.anrok.com/rtnRightRev is an automated revenue recognition platform that lets your product team ship new pricing without asking finance for permission, and your sales team close deals without creating downstream chaos. Check out their free tool at calculator.rightrev.com It scores your rev rec process, shows what's exposing you to risk, and tells you exactly where to focus before it bites you in the rear end. Check it out at https://calculator.rightrev.comPulley is an equity management platform that lets you issue options, model dilution, and complete 409As without your cap table turning into a spreadsheet disaster. Founders raising, hiring, and scaling use Pulley to keep equity clean and stay focused on building. Learn more or request a demo at https://pulley.com/mostlymetricsRillet is an AI-native ERP built for modern finance teams that want to replace NetSuite and close faster. With revenue recognition, close management, multi-entity support, and native Stripe and Salesforce integrations, Rillet helps scaling companies run their finance stack in one place. Hundreds of teams, including Windsurf and Mercor, use Rillet to make the zero-day close real. Book a demo at https://www.rillet.com/cjMaximor is an autonomous finance platform that runs order-to-cash, procure-to-pay, the close, cash management, and reporting on self-learning agents instead of a dozen disconnected tools. One PE-backed customer cut their close in half, took audit findings from seven to zero, and cut back-office costs by 70% in six months. You pay for outcomes, not seats. See it at https://www.maximor.ai/—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNGuests:https://www.linkedin.com/in/aj-ljubich-cfa-727ab912/https://www.linkedin.com/in/dana-decker/https://www.linkedin.com/in/micah-richard-64a53238/Companies:https://www.datadoghq.com/https://www.opendoor.com/https://www.pwc.com/CJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—TIMESTAMPS:0:00 Preview and Intro2:27 Panel intros: AJ, Micah, Dana4:00 FP&A a year ago vs. today6:45 Opendoor: default-to-AI company7:40 Leadership being in the weeds8:30 Building a daily P&L view with Claude9:39 Sponsors — Brex | Anrok | RightRev12:38 Forecasting at Datadog: consumption model14:20 AI picks up seasonality, misses customer context15:10 Semantic layer and blessed queries16:35 Self-serve data: how far can you go?20:10 Best-in-class adoption: build over buy20:23 Sponsors — Pulley | Rillet | Maximor23:30 Does a 2-year head start matter?24:10 Build vs. buy criteria haven't changed25:10 Evaluating vendor roadmaps26:20 Procurement shifting toward build28:00 Data access controls and RBAC31:00 Token usage: haves and have-nots32:50 Encouraging tokens across the org34:40 ROI metrics haven't changed35:45 90-day advice: just start36:55 Leadership has to pull the red tape38:05 Get the data right first39:07 Credits

Erik Martinez and Pat Barry made their AI predictions six months ago. Agents, AI shopping, rising costs, governance. They were right about almost all of it, and almost none of it showed up the way they expected. Pat keeps running into the same pattern across every organization he works with. Someone has quietly built something remarkable with AI. When Pat tells them to share it, the answer is always some version of "yeah, they're not really into it." The capability exists. It's invisible. And nobody is asking why it stays that way. Meanwhile, Erik went from spending his days in Excel, PowerPoint, and Canva to doing ninety percent of his work inside tools that didn't exist in their current form six months ago. Pat's building entire training decks with agents that get him 85% of the way there in a quarter of the time. AI platforms are turning into the new office suite, and most people haven't realized the shift already happened. Token costs are climbing and Erik describes trying to track them as "absolutely maddening." One of Pat's healthcare clients made a governance decision that positioned them as what Pat calls "the team of the future." A university with 50,000 employees and access to the same tools can't keep up. The predictions were about what AI would do. What actually changed was how the humans work. That gap is the conversation in Episode 113.

AI didn't just speed up the development of Basecamp 5, it changed how it was built. This week, Jason Fried and David Heinemeier Hansson break down how much of a role AI played in building their latest product, where it shines, and how 37signals had to adjust its process to keep their code base clean.Key Takeaways00:11 – How much of a role AI played in building Basecamp 509:55 – Where the intelligence technology truly excels14:42 – The new challenge of saying no when features become easier to build16:19 – Why a leaner product roadmap still matters18:32 – Staying "easy to use" while competitors focus on AI features20:44 – Why AI deserves both the hype and the skepticism25:12 – Token spend, productivity, and staying profitableLinks and ResourcesAI Agents welcome in BasecampRecord a video question for the podcastWatch The REWORK podcast on YouTubeBasecamp is the no-nonsense project management system. Sign up for free at Basecamp.comHEY is a fresh take on email. Sign up for a 30-day free trial at HEY.comFizzy is a modern spin on kanban. Sign up for free at fizzy.doBooks by 37signalsJason Fried on XDavid Heinemeier Hansson on X

Welcome to the Bluegrass Briefing for July 2026, your monthly look at what's going on in the world of bluegrass and beyond.Here are the links to stuff mentioned in this episode.News and Announcements (Church Street News)McCoury & Douglas Family Pickin PartyBéla Fleck's My Bluegrass Heart tourReleases (The Grass is New)Natalie & Brittany Haas - North NodeNoaBass - Late BloomerVoices: A Folk OperaScroll on BuddyPunch Brothers - Found in a Frozen FogOther bitsFull list of interviewsCollings GuitarsHappy picking.Matt Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

View all cards mentioned in this episodeAndy and Anthony talk about the logistics of tokens for Cube. They talk about different ways they've managed them over the years and for different Cubes. They make recommendations for the best way to approach the problem, and even how their Cube design is influenced by token makers.Discussed in this episode:InfiniTokensMPC AutofillExample Token Page on Cube CobraCubes Discussed:Sacred GeometryRegular CubeNeoclassical CubePenrose CubeTake 5100 OrnithoptersIf you'd like to show your support for the show, please consider backing Lucky Paper on Patreon or leaving us a review on iTunes or wherever you listen.Check us out on Twitch and YouTube for paper Cube gameplay.You can find the hosts' Cubes on Cube Cobra:Andy's “Bun Magic” CubeAnthony's “Regular” CubeYou can find both your hosts in the MTG Cube Talk Discord. Send in questions to the show at mail@luckypaper.co or our p.o. box:Lucky PaperPO Box 4855Baltimore, MD 21211Musical production by DJ James Nasty.Timestamps0:00 - Intro1:44 - Main Topic: Token Logistics6:15 - Anthony's Approach to Tokens9:04 - Challenges Managing Tokens15:28 - Dry Erase Token Rant18:03 - Tokencreep21:29 - Sacred Geometry Tokens27:00 - Green In Sacred Geometry32:47 - How Token Restriction Influences Sacred Geometry34:51 - Bun Magic Tokens39:16 - Problems with Token Bags43:06 - New Token System48:15 - Why Streamline Your Tokens?51:04 - Andy's Other Tokens56:23 - Other Token Solutions

Summary   In this episode, Jack from MirageGarden discusses innovative token standards, the future of NFTs, and how new blockchain technologies can empower communities and developers. He explores the concept of liquid object assets, the importance of open standards, and the potential for on-chain applications beyond simple collectibles.   Learn more about Mirage Garden: https://www.mirage.garden/  Chapters   00:00 Introduction and Guest Background 00:27 Crypto Anniversary and Personal Journey 00:59 Jack's Background in Community Management and Crypto 01:29 Early Crypto Projects and DeFi on Cardano 02:24 Evolution of MirageGarden and Multi-Chain Plans 03:37 Crypto Events and Community Building 04:07 The Role of Education in Crypto Adoption 05:28 NFT Utility and Future Potential 06:03 Innovations in ERC Protocols and On-Chain Assets 07:20 AI and Smart Contract Development 08:42 Funging NFTs and New Token Types 09:11 Stateful Tracking of Token Assets 10:08 Community-First Token Design and Use Cases 11:17 NFT Market Evolution and Rarity 12:29 Trade and Utility of Unique Collectibles 13:45 Future of In-Game Assets and Cross-Game Utility 14:52 Inverse NFT Concept and Liquid Object Assets 16:17 Token-Gated Objects and Micro Ledgers 17:14 Stateful Objects for Debt and Collateral 18:43 Open Standard for Token Types 20:00 Use Cases for Stateful Token Objects 21:34 Combating Wash Trading with New Token Standards 22:43 Launchpad for New Token Types and Applications 24:35 Low Fees and Open Protocols 26:22 Differentiation from Other Standards and Projects 27:03 Empowering Developers and Community 28:26 On-Chain Content and Sharding 29:54 Standardization and Interoperability 30:24 Community-Driven Innovation in Crypto 32:46 Addressing Flaws and Future Improvements 34:39 Open Standard and Marketplace Vision 36:28 Features and Flexibility of New Token Types 37:50 Re-Rolling and Customization of Token Assets 39:20 Getting Started with MirageGarden 40:47 Final Words and Community Call to Action

When companies mandate AI adoption without a use case, without a strategy, and without a business outcome in mind, they don't get transformation. They get jazz hands and nightmare token bills.This month's System Update pulls apart what's actually happening beneath the headlines: Oracle's 21,000 layoffs attributed to "AI adoption," Amazon arming junior developers to replace senior engineers, and enterprises burning through AI budgets they cannot predict or control.The deeper argument George K. and George A. make is harder to dismiss than the headlines. You cannot drive deterministic business outcomes with probabilistic means of production. The CEOs and CTOs who greenlit LLM adoption at scale are now facing a math problem that no earnings call language can paper over.The free water is now a metered utility. Will the bill ever be worth paying?The episode also turns to labor theater and what we're giving our attention to: what we lose when institutions optimize for engagement over depth, and what it costs when an entire generation learns to consume rather than think.Mentioned: NYT on Schneider Electric's AI adoption without layoffs Amazon tokenmaxxing mandate goes sideways Oracle sheds 13% of its workforce amid so-called AI adoption Amazon still hiring junior employees while also doing layoffs…? The Intellectual Life of the British Working Classes, by Jonathan Rose Snap's intentional targeting of teens' attention Denmark invests in de-screening its schools

If you've ever stared at a model picker and wondered whether to click Flash, Sonnet, Opus, Instant, or Think Deeper, you are not alone. These naming conventions are genuinely confusing, and most people just pick something and hope it works. The stakes are higher than they might seem, though. Token misuse has left some companies with eye-watering AI bills, including one case where a single employee ran up a $500,000 tab in a month. The good news is that there is a simple mental model that cuts through all the noise, and once you have it, choosing the right model for any task takes seconds. In this How I AI episode, Neo and I walk through the four major AI platforms, Gemini, ChatGPT, Claude, and Copilot, and break down exactly which model to use and when. We also get into tokens, usage limits, and why matching the model to the task matters far more than most people realise. How I AI is a special series within How I Work where Neo and I explore how high performers are using AI at work to boost productivity, make better decisions and reduce overwhelm. What you'll learn: Why ignoring model numbers and reading the small print instead saves a lot of confusion What Fable and Mythos are, and why you can't use them right now How token usage works and why the right model choice protects your access Practical AI tools for productivity and focus Real-world AI workflows used by high performers How to use AI at work without burning out Smart shortcuts for managing time and mental load Connect with Neo Aplin on LinkedIn (https://www.linkedin.com/in/neoaplin/) and via inventium.ai (https://inventium.ai), where he leads Inventium's AI training and upskilling work with organisations and teams. My latest book The Energy Game is out on July 7, 2026. You can order a copy here: https://amzn.to/48ID29M Connect with me on the socials: Linkedin (https://www.linkedin.com/in/amanthaimber) Instagram (https://www.instagram.com/amanthai) If you are looking for more tips to improve the way you work and live, I write a weekly newsletter where I share practical and simple to apply tips to improve your life. You can sign up for that at https://amantha.substack.com/ Visit https://www.amantha.com/podcast for full show notes from all episodes. Get in touch at amantha@inventium.com.au Credits: Host: Amantha Imber Sound Engineer: Martin Imber See omnystudio.com/listener for privacy information.

AI工具的普及，讓許多企業主管陷入一種奇特的困境：訂閱了一堆工具，開了不少專案，生產力卻沒有等比例提升。 Agent執行速度快，但做了什麼、什麼時候完成、串聯了哪些系統，管理者往往搞不清楚，指令下得模糊，Token燒了一堆，成果卻不如預期。問題的核心不在AI，而在管理者從未被訓練過如何把工作拆解清楚、設定可量測的成果標準、在出錯時找到責任歸屬。 本集未來城市Podcast邀請意藍科技創辦人楊立偉，他同時在台大資管系與工管系開課，並帶領團隊在半年內用AI自建ERP、通過上市審查，在全台近兩千家上市櫃公司中被主管機關列為標竿案例。 楊立偉將分享企業轉型的真實挑戰，從如何拆解工作，到建立Agent品質稽核機制，一起成為AI時代的「超級管理者」。 【聽完這集你會知道】 02:33｜AI 成熟度五級框架：為何大多數企業卡在 Level 2，缺口是管理而非技術 06:09｜指令三要素：分點論述、輸入輸出規格、成果預期 16:34｜讓 Agent 查 Agent：透過通過率與錯誤傾向分析，建立可量化的品質管理機制 21:28｜A2A 協同機制：專才模型與通才模型分工，比單一模型從頭做更快更省 24:54｜Agent 上線配套清單：獨立帳號、正式布達、指定主管，三者缺一必失控 【本集金句】 「把步驟分點論述、輸入輸出講清楚，Agent 就可以做得不錯，問題是很多人自己都沒想清楚。」 主持人： 未來城市頻道總監 陳芳毓 來賓：意藍科技創辦人 楊立偉 製作團隊：詹湘淇、錢玉紘、陳繹方、陳瑞偉 ＊百工百業用AI系列 https://futurecity.cw.com.tw/special/ai-work-podcast ＊搜尋「未來城市FutureCity@天下」，追蹤更多城市議題：https://futurecity.cw.com.tw/ ＊訂閱天下全閱讀：https://bit.ly/3STpEpV ＊「聽天下」清楚分類更好聽，下載天下雜誌App：https://bit.ly/3ELcwhX ＊意見信箱：bill@cw.com.tw -- Hosting provided by SoundOn

This week's Bitesize episode comes from a fascinating conversation I had with Tristan Scroggins in 2021.In this section Tristan reflects on what it means to come to bluegrass as an 'outsider' and how culture and connection aren't just about geographical borders.Growing up in New Mexico, despite learning traditional bluegrass from his father, Tristan felt a disconnect from the roots of the music. Later, when he moved to Nashville, he found himself wondering exactly why he loves bluegrass so much. Whether we're taking about European festival fans reacting to bluegrass (and the culture they perceive accompanies it), or the generation of northern and western musicians who came to bluegrass in the 1960s and 70s as a result of the folk revival, there's a common thread of music transcending boundaries. As a Brit coming to this music from outside both the region and the culture, yet feeling like I somehow belong, I find these conversations fascinating.You can hear my full interview with Tristan on Apple Podcasts, Spotify or wherever you get your podcasts.For more on Tristan, head to tristanscroggins.com or follow Tristan on Instagram Support the show===Thanks to Bryan Sutton for his wonderful theme tune to Bluegrass Jam Along (and to Justin Moses for playing the fiddle!)Bluegrass Jam Along is proud to be sponsored by Collings Guitars and Mandolins and Token premium guitar picks- Sign up to get updates on new episodes - Free fiddle tune chord sheets- Here's a list of all the Bluegrass Jam Along interviews- Follow Bluegrass Jam Along for regular updates:InstagramFacebook- Review us on Apple Podcasts

Here's the plan the best gym owners are following right now: https://www.youtube.com/watch?v=uMPx7b3_LOA The gyms winning with AI right now are not using it to write emails. They built a machine learning algorithm that predicts who's about to cancel. They fired their ad agency and their bookkeeper. They have an AI employee living in Slack that nobody on the team can tell isn't human. Pav spent 20 years in Fortune 500 companies before opening BFT Tysons. His financial planning background and tech instincts put him in a different category than most gym owners touching AI right now. In this episode, Mike Arce sits down with one of the most advanced operators in the GSD community to break down exactly what they've built, how they built it, and what's coming next. In this episode you'll learn: — How Pav built a machine learning algorithm that ranks the 25 members most likely to cancel before they decide — The five member behavioral avatars the model uses and which signals carry the most weight — How BFT Tysons uses Claude to run Meta ads, optimize campaigns from the grocery store line, and launch new ads in five minutes instead of 45 — The AI marketing analyst that pulls weekly ad data, surfaces red flags, and sends recommendations directly to Slack — How Victor works as an AI employee inside Slack and the story of it onboarding a new team member better than the humans did — Why the era of information is over and what the era of imagination means for gym owners right now — Studio OS: the custom internal dashboard Pav's team built to track memberships, financials, and cancellations in one place — How AI analyzed BFT's three membership tiers and identified which members were most likely to upgrade — The connection between selling your highest tier first and actually getting members the results they came for — What Pav is focused on in Q3 and how AI identified three specific reasons revenue per member was declining — The security risks gym owners should actually worry about when building with AI — Why the AI revolution mirrors the printing press and what that means for the jobs being created right now If you think you're using AI because you asked it to rewrite an email, this episode will show you how far behind that really is. Episode chapters: — 0:00 — Introduction: Pav Grewal, BFT Tysons, and two years in GSD — 1:12 — From Fortune 500 financial analyst to gym owner: Pav's background — 2:08 — How their AI journey evolved from basic copy to machine learning — 2:59 — The attrition prediction algorithm: how it works and what it watches — 4:57 — Attendance as the top signal and the early dropout problem — 6:03 — The first 90 to 100 days: why onboarding drives long-term retention — 7:17 — Victor: what an AI employee actually looks like inside Slack — 9:21 — Victor's second day: onboarding a new team member better than everyone else — 10:56 — How Victor handled a HYROX registration list and corrected a missing name — 12:24 — Mike's P1, P2, P3 priority system and how Victor scheduled a meeting end to end — 13:21 — Pav's wife wants Victor too — 13:55 — Firing the ad agency: how Claude connects to Meta and runs paid ads — 14:46 — Building avatar research, hooks, and copy with AI before the ad is even created — 19:30 — Generating five to ten ad variations simultaneously and testing at scale — 20:58 — Optimizing campaigns from the deli line at the grocery store — 22:58 — The AI marketing analyst: weekly performance reports delivered to Slack — 23:46 — Competitor research through the Meta Ads Library: offers, angles, patterns — 26:04 — The difference between using AI for flyers and actually building with it — 26:58 — Firing the bookkeeper: Scott's move and QuickBooks integration — 28:23 — Why custom-built tools will replace bloated SaaS platforms — 32:42 — The era of imagination: what changes when anyone can build anything — 33:39 — From one-way communication to creation: the internet analogy — 34:15 — Using AI to get better member results, not just run the business — 35:38 — Victor frees Mike up to go deeper with clients — 35:54 — The six-step AI re-engagement plan for members who have fallen off — 36:39 — Mike's personal health project: syncing InBody, sleep, nutrition, and blood work — 37:47 — The affiliate and recurring revenue idea hiding inside member health data — 39:50 — Token costs dropping and the Chinese model conversation — 40:46 — Elon Musk putting data centers in space — 42:13 — The GSD AI cohort and what the group is building together — 43:16 — Studio OS and the mindset shift that sparked it — 44:39 — AI security: what to actually worry about and how to think about it — 45:38 — Q3 focus: shifting from more members to more revenue per member — 47:01 — Tier analysis: who's most likely to upgrade and how to have that conversation — 48:54 — The steakhouse analogy: stop selling people the chicken — 50:30 — Changing the sales conversation around conviction, not price — 51:41 — The Gutenberg printing press and what history says about the AI revolution — 53:11 — AI architects: the most in-demand job right now and Claude's $85K certification program — 54:07 — Closing thoughts ———————————————————————— If you want to understand where the gym industry is actually heading, the operators doing what Pav is doing in this episode are already three moves ahead of everyone else. Watch the 100K Plan: https://www.youtube.com/watch?v=uMPx7b3_LOA

https://novacut.ai/  Description: Anthropic pulls access to Fable, and China responds the same day with GLM 5.2. In this episode we break down the escalating AI arms race, US export controls on chips and frontier models, and whether the "Great Firewall of America" is already here. ⏱️ Topics: Anthropic restricts Fable — what happened and why China's GLM 5.2 release and how close they're catching up US trust, surveillance, and AI gatekeeping Token pricing chaos — cost per task vs. cost per token Model routing, loop engineering, and autonomous agents Anthropic's Mythos model and Fable safeguard philosophy Xiaomi NEMO V2.5 Pro Ultra Speed Midjourney's bizarre health spa pivot AI Engineer Conference wrap-up

Nikesh Arora is the Chairman and CEO of Palo Alto Networks, the global cybersecurity leader. Since taking over in 2018, he has transformed the company from an $18 billion market cap business into one worth more than $225BN with more than 21,000 employees globally. Previously, Nikesh was President and COO of SoftBank, where he worked alongside Masayoshi Son and helped shape the firm's technology investment strategy.  AGENDA: 00:00 Why AI Token Prices Will Fall 90% — And Why That's Bullish for AI 07:40 The Frontier Model Problem: Breadth vs Depth in AI 11:30 Most Enterprises Are Using AI Completely Wrong 13:10 Why AI Could Cut Marketing, HR & Finance Teams in Half 16:00 AI Applications Will Have Opinions — SaaS Never Did 20:00 OpenAI, Anthropic & The Most Important Valuation Question in Tech 24:00 The Real Business Model of AI: Transaction Revenue Beats Advertising 25:10 Why Token Prices Must Collapse 28:20 Where Value Actually Accrues in AI: Models, Memory or Apps? 29:00 Why Memory Becomes the Biggest Moat in AI 32:00 Why Every Enterprise Should Be Scared Right Now 33:15 Should Governments Regulate Frontier AI Models? 37:10 Why Brian Armstrong's AI-First Playbook Doesn't Work Everywhere 40:00 The Biggest AI Mistake CEOs Are Making Today 42:00 How Nikesh Creates Darwinian Competition Inside Palo Alto 43:00 Do AI Companies Really Need Forward-Deployed Engineers? 45:00 Why Enterprise AI Products Still Aren't Ready 52:00 Systems of Record vs Systems of Intelligence: The Future of Software 54:00 Why AI Applications Will Replace Traditional SaaS Workflows 58:00 What Nikesh Learned From Google That Still Matters Today 1:04:00 From $200 and Two Suitcases to Running a $225B Company 1:10:00 Happiness, Gratitude and Why Tomorrow Matters More Than Ten Years From Now    

This week, Ben Jones and Karl Floersch join the show to discuss what happened to the L2s. We take a deep dive into Optimism's new strategy for 2026, the current state of Ethereum, why companies need to launch a chain, having a token, and more. Enjoy! -- Follow Karl: https://x.com/karl_dot_tech Follow Ben: https://x.com/ben_chain Follow Jason: https://x.com/JasonYanowitz Follow Empire: https://x.com/theempirepod -- Robots will soon outnumber humans onchain. peaqOS turns them into a new trusted liquid asset class, with yield tied to real-world workloads. It gives robots all they need to do business on any chain — and lets humans earn from automation. Explore the Machine Economy: https://peaq.xyz -- Timestamps: (00:00) Introduction (03:43) What L2s Got Right vs Wrong (12:46) peaq Ad (13:42) Optimism's Strategy in 2026 (32:36) What's Optimism's Moat? (40:02) Who Needs To Build a Chain? (51:20) The Current State of Ethereum (59:39) Launching a Token (01:03:10) What Defines Success in Crypto? -- Disclaimer: Nothing said on Empire is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Santiago, Jason, Rob and our guests may hold positions in the companies, funds, or projects discussed.

Jordi Visser is a veteran macro investor with 30+ years of experience and the author of the VisserLabs Substack. In this conversation, we discuss the AI pivot happening with hyperscalers, the rise of open source models, what the Mythos/Fable Five situation means for governments and investors, Kevin Warsh's first Fed press conference, where inflation is actually headed, and why bitcoin is still in a bear market and what needs to change.====================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp====================Arch Public is an agentic trading platform that automates the buying and selling of your preferred crypto strategies. Sign up today at https://www.archpublic.com and start your automated trading strategy for free. No catch. No hidden fees. Just smarter trading.====================Looking for a better place to trade? BloFin gives traders access to deep liquidity, advanced futures products for crypto AND TradFi assets, fast execution, and a clean, intuitive interface—all in one platform. To celebrate their partnership with us, they're giving away $100,000 in Deposit & Trade Rewards. Deposit, trade, and earn rewards based on your activity during the campaign.====================0:00 - Intro0:57 - AI pivot & hyperscaler weakness5:47 - Open source models & US vs China AI race7:19 - Token demand, Jevons Paradox & AI adoption trends14:22 - When does the CapEx spending become a problem?17:59 - Open source vs closed AI models — who wins long term?19:25 - Agency & what it means for individuals24:34 - Is AI & energy the only thing holding the market up?28:32 - Kevin Warsh's first Fed press conference31:36 - Inflation outlook & next CPI print37:44 - Why so many Americans feel trapped & real cost of living44:51 - Bitcoin bear market & what needs to change

Get double the episodes, and keep FUT Weekly going (for just £3 a month) by becoming a Patreon over at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠bit.ly/morepod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. This includes an exclusive supporter podcast this week! Game Designer Seb is on his second podcast of the week! After 20 minutes of World Cup chat, he goes through why EA may have added the token system and what it could mean in the future. Chapters (please note, as Spotify inserts ads into run time, these timestamps will usually be behind when the topics starts): 00:00 Week 1 of the World Cup Reviewed 21:14 What does Tokens mean for Ultimate Team long term? 33:04 Is Ultimate Team just for rewards? 40:11 Randoms Reds vs Weekly Pick of 3 51:05 Why are EA scared of repeatable gameplay grinds? 54:29 Have EA got power curve rubber banding right? 1:00:18 The biggest problem with Tokens 1:03:11 How Star Performers work 1:07:11 The future of Playstyles Lab Learn more about your ad choices. Visit podcastchoices.com/adchoices

Ready for the AI buzzword for the rest of 2026? Superapps. No, not China's WeChat. The AI Superapp era is much different, and it's about to hit the business world hard. So, if you aren't sure what an AI Superapp is or if your company should be using one, this is an episode you can't miss. AI SuperApps: Why Every Company is Racing to Create One and What They are — An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:AI Super App Race: OpenAI, Anthropic, MicrosoftWhat Is an AI Super App? ExplainedAgentic Shift: Chatbots to Autonomous CoworkersSuper App Harness vs. AI Model as MoatThree-Pane Super App Interface InnovationCodex vs. Cursor vs. Claude BenchmarksEnterprise Desktop Integration and Super App StrategySuper App Security, Risks, and Best PracticesTimestamps:00:00 Super app race and ChatGPT integration06:04 Emergence of desktop super apps08:41 Codex as the leading super app11:22 Shift to AI desktop super apps14:13 The AI super app's proactive updates17:26 Token efficiency in super apps21:29 Future of AI model usability27:03 Anthropic's role in AI development30:19 Google's Gemini 3.5 and Anti-Gravity Launch33:13 Risks and responsibilities with AI apps34:31 Cautionary advice on AI usage38:03 Introduction to AI super appsKeywords: AI super app, AI superapps, super app era, desktop super app, agentic AI, autonomous coworker, agentic context carry, agentic work future, AI execution layer, super app harness, model moat, code interpreter, Codex, OpenAI super app, Microsoft super app, GitHub Copilot, Anthropic, Claude Code, Claude Cowork, Google anti gravity, Gemini 3.5 Flash, Cursor, desktop agentic coworker, unified memory, files automations, approvals and automations, browser control, computer use, three pane interface, context engineering, prime prompt polish, token efficiency, user experience, read-write access, autonomous workflows, desktop AI companion, schedule automations, approval workflows, cross-app integration, enterprise adoption, permission controls, role based access, sandboxing, expert-driven loop, AI safety, risk management, computer automation, enterprise AI strategy, AI model integration, productivity automationSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

The drama around Anthropic's Fable 5 model clogged our collective attention spans.

Jordi Visser is a veteran macro investor with 30+ years of experience and the author of the VisserLabs Substack. In this conversation, we discuss why bitcoin is down 50% and whether the bear market is over, why he's still buying through the dip, how AI agents will drive bitcoin adoption, and why the rotation from AI hardware to human software is the biggest investment opportunity right now.=======================Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan, allowing you to borrow against your BTC, ETH, or SOL with 12-month terms, 8.91% interest rates, and no prepayment penalties. Or check out Democratized Prime (https://figuremarkets.co/pomp) and earn ~9% APY on real world assets, paid hourly. Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp Figure Lending LLC dba Figure (NMLS 1717824). Loans subject to approval. Crypto collateral may be liquidated. Terms apply - see full disclosures at figure.com/disclosures/=======================Arch Public is an agentic trading platform that automates the buying and selling of your preferred crypto strategies. Sign up today at https://www.archpublic.com and start your automated trading strategy for free. No catch. No hidden fees. Just smarter trading.=======================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp=======================0:00 - Intro0:45 - Why bitcoin is down 50% & is the bear market over?6:48 - What would convince Jordi to sell his bitcoin?9:07 - Bitcoin as the S&P 500 of crypto14:02 - Why bitcoin is safer than any company past 203017:45 - Bitcoin volatility vs. the stock market22:22 - The five-layer AI stack & where revenues are missing26:22 - Token budgets & the shift to specialized AI35:10 - Are LLMs now commoditized?40:30 - Peptides as the API key for the human body49:24 - Healthcare, entitlements & the future outlook