Podcasts about ARR

Six years after Southward Chronicles, Jeremy Kroeker and Elle West are setting out again—this time heading south through Africa by motorcycle. Despite years of travel experience, they begin feeling unprepared, underfunded and more apprehensive than ever. Backroads of Africa follows their journey as it unfolds.

Clément Houllier a 37 ans, un diplôme d'ingénieur et un début de carrière… en marketing chez L'Oréal. À 30 ans, il quitte le confort d'un grand groupe pour prendre la direction de l'innovation d'une ETI industrielle de 50 ans, sans budget.Sa réponse : un start-up studio, et un premier projet, AUUM, pour « Arrêtons l'Usage Unique Maintenant ».Le pari : une machine de la taille d'une cafetière qui nettoie et désinfecte un verre en une vingtaine de secondes, à la vapeur sèche à 140 °C, sans produit chimique et avec très peu d'eau. Trois ans de R&D plus tard, AUUM arrive sur le marché en septembre 2021, portée par la loi AGEC… et par le Covid. Aujourd'hui : plus de 1 500 machines en parc, 150 000 utilisateurs chaque jour, plus de 15 M€ de chiffre d'affaires cumulé, une série B et une expansion en Europe, jusque sur les chantiers.Début 2026, Clément quitte AUUM pour lancer SUUN.Nouveau terrain : le solaire. Son constat : le panneau ne pèse que 20 % de l'investissement d'un projet, le reste, c'est l'infrastructure. SUUN repense donc les ombrières comme des ouvrages d'art : des piliers en béton fibré ultra-haute performance (BFUP) espacés de 30 à 40 mètres, des câbles tendus, les panneaux posés dessus. Moins d'ancrages au sol, un déploiement plus rapide, et déjà une quinzaine de projets validés chez des industriels en autoconsommation.Au programme :Quitter L'Oréal à 30 ans : pourquoi le confort est le vrai risquePourquoi l'intrapreneuriat salarié ne marche pas sans la peur et le gainLa vapeur sèche expliquée : le cercle de Sinner, 40 buses et un verre standardiséLoi AGEC + Covid : quand le contexte rattrape la vision« La dernière roue du carrosse » : le sort d'un produit jugé anecdotique quand les budgets gèlentSUUN : des ombrières pensées pour la recharge des poids lourds, le stockage d'énergie dans les fondations et la loi APERLa marque, angle mort des startups d'ingénieurs et de leurs investisseursUn épisode enregistré lors du lancement de l'espace innovation construction de NGE et Contech France, à Issy-les-Moulineaux.Pour aller plus loin :Clément Houllier sur LinkedIn

Pendant l'Occupation, certains résistants transportaient des messages, d'autres sabotaient des voies ferrées ou recueillaient des renseignements. Raoul Minot, lui, choisit une arme beaucoup plus discrète : un appareil photo.Né en 1893 à Montluçon, Raoul Minot est un ancien combattant de la Première Guerre mondiale. Dans les années 1940, il travaille au grand magasin du Printemps, à Paris. Passionné de photographie, il décide, après l'entrée des Allemands dans la capitale en juin 1940, de documenter ce qu'il voit autour de lui.Son appareil est modeste : un petit Kodak Brownie, facile à dissimuler. Mais son geste est risqué. Les autorités allemandes interdisent rapidement de photographier librement les installations militaires, les soldats ou certains lieux publics. Être surpris en train de prendre des clichés peut entraîner une arrestation.Malgré cela, Raoul Minot photographie Paris pendant plusieurs années. Il saisit les soldats allemands dans les rues, les véhicules militaires, les affiches de propagande, les bâtiments réquisitionnés, mais aussi la vie quotidienne des Parisiens sous l'Occupation.Son travail ne se limite pas à prendre des images. Minot note souvent avec précision le lieu, la date et parfois l'heure de ses photographies. Il ajoute également des commentaires ironiques ou hostiles à l'occupant. Ses clichés constituent donc à la fois un témoignage historique et potentiellement une source de renseignements.Grâce au laboratoire photographique du Printemps, il peut faire développer ses pellicules. Certaines images circulent ensuite par l'intermédiaire de connaissances liées à la Résistance.Mais cette activité clandestine finit par attirer l'attention. Raoul Minot est dénoncé. Arrêté en 1943, il est emprisonné à Fresnes, puis interné au camp de Compiègne avant d'être déporté en Allemagne.Il passe notamment par le camp de concentration de Mauthausen puis par celui de Buchenwald, où il est soumis au travail forcé.En avril 1945, alors que le régime nazi s'effondre, Raoul Minot est finalement libéré par les forces américaines. Mais il est extrêmement affaibli par la déportation. Il meurt quelques jours plus tard, le 28 avril 1945.Pendant des décennies, son nom reste largement oublié. Ce n'est que bien plus tard que son rôle est redécouvert et que ses photographies peuvent être attribuées avec certitude.Raoul Minot laisse ainsi un témoignage exceptionnel : celui d'un homme ordinaire qui, au risque de sa vie, décida de conserver des preuves visuelles du Paris occupé. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Melvyn Peignon est Product Management Director chez ClickHouse, la base de données en temps réel utilisée par Deliveroo, Uber, Qonto ou Accor, mais aussi par de nouveaux géants comme OpenAI, Anthropic et Tesla.Avec l'accélération de l'IA et l'explosion des besoins temps réel, l'entreprise a connu une croissance exceptionnelle ces dernières années.Ils ont atteint une valorisation de 15 milliards de dollars après une levée de fonds de 400 millions de dollars en 2026, comptent 4 000+ clients et réalisent 250+ millions de dollars d'ARR.On aborde :

Bango Plc. CEO Paul Larbey joined Steve Darling from Proactive to discuss the company's strong first-half results, highlighting continued momentum in its rapidly growing subscriptions business and reaffirming that trading remains in line with full-year market expectations. Larbey said growth in Bango's subscriptions segment continued through the first six months of 2026 and has carried into the second half of the year, supported by increasing adoption of the company's Digital Vending Machine (DVM) platform. The platform enables telecom operators and other businesses to package and sell multiple subscription services—including streaming, entertainment and digital content offerings—through a single bundled customer experience. The company secured eight new DVM customers during the first half of the year, with six already signed under contract. Larbey noted that customer demand remains strong, supported by a healthy sales pipeline despite ongoing macroeconomic uncertainty. Bango also continues to execute a strategic restructuring of its lower-margin payments business. The company is streamlining certain payment routes, a process that is running ahead of schedule and is expected to be completed before year-end. While the rationalization may reduce reported revenue by a low single-digit percentage, management expects little impact on profitability and believes it will improve the overall quality and margin profile of the business. For the six months ended June 30, Bango reported revenue of $25.9 million, a 3% increase from the same period last year. The growth was driven primarily by the subscriptions division, where revenue climbed 13% to $12.3 million. Payments revenue declined 5% to $13.6 million as the company continued its planned restructuring of the lower quality revenue routes. Profitability improved significantly across the business. Adjusted EBITDA increased 34% year-over-year to $9 million, with the subscriptions segment playing a leading role. EBITDA from subscriptions more than tripled to $3.2 million, underscoring the growing scalability and operating leverage of the platform. One of the most notable achievements during the period was the company's turnaround in cash generation. Cash EBITDA improved from a loss of $0.7 million in the prior-year period to a positive $3.7 million, surpassing the total cash EBITDA generated during all of 2025 in just the first six months of 2026. Recurring revenue metrics also continued to strengthen. Annual recurring revenue (ARR), which measures the annualized value of contracted subscription income, rose 31% to $20.4 million. Net revenue retention improved to 119% from 108%, indicating that existing customers are spending more over time and expanding their use of Bango's platform. #proactiveinvestors #bangoplc #aim #bgo #otcqx #bgopf #DigitalVendingMachine #Subscriptions #Telecom #StreamingServices #SaaS #RecurringRevenue #ARR #Fintech #DigitalCommerce #TechnologyStocks #GrowthStocks #BusinessTechnology #SteveDarling

Vous ne manquez peut-être pas de temps mais de limites.Dans cette vidéo, je vous explique pourquoi les urgences des autres, la peur de déplaire, le besoin de tout contrôler et l'excès de gentillesse peuvent détruire votre organisation, même avec le meilleur agenda du monde.Nous allons voir comment dire non, poser des standards, déléguer réellement et arrêter de porter des responsabilités qui ne vous appartiennent pas.

Anthropic's IPO prospectus finally surfaced: a $42B net loss on $4.6B in revenue, a quarter of it from two customers. OpenAI scrapped GPT-6.1 Astra over safety, Oura postponed its IPO, and I wondered whether intelligence is becoming a commodity. ⁠THIS IS THE YOUTUBE VIDEO OF MY RANT⁠ IPO prospectus: Anthropic reports a net loss of $42B in 2025, with operating losses of $8B+; revenue grew 12x to ~$4.6B, ~25% of which came from two customers (Reuters) Anthropic formally warns investors its technology may pose "existential risks to humanity," devoting almost a third of its S-1 to risk factors including AI manipulation and blackmail (FT) Anthropic's IPO filing creates a "Founder LLC" of its seven co-founders, whose majority vote directs a single Class F share with 50.1% of voting power, while the company stays a PBC (Reuters) OpenAI scraps plans to publicly launch GPT-6.1 Astra, saying it didn't quite meet its safety bar during internal testing, after targeting an October release (WSJ) Oura says it is delaying its Nasdaq IPO due to uncertainty in the market, despite "strong demand" and a strengthening of its business since the process started (CNBC) Sources: OpenAI's ARR is nearing $70B, growing 70%+ since the beginning of Q3, with B2B revenue up 100%+; it added more consumer revenue in Q3 than all of 2025 (Axios) Claude Code vs. OpenAI Codex ARR: Codex never slowed after Claude Code's crossover while Claude Code appears to have plateaued, and Opus mentions on GitHub spiked after Opus 5.5 as GPT-6 mentions dropped (TickerTrends) THIS IS THE YOUTUBE VIDEO OF MY RANT

We are excited to have Anthropic share their latest AI x Finance work at AI Engineer New York, coming up in 2 weeks!In case you've been under a rock, here's a non-exhaustive list of what Anthropic has been shipping since closing the largest fundraise of all time in May at $47B ARR:* June: Launched Claude Tag and Sonnet 5 and Fable 5* July: Opus 5, /checkup. crossed $65B ARR* Last month: Fable/Mythos 5.1, and EFS (upcoming pod)* IPO target $2T, end 2026 ARR estimated $100B* Cowork/chat merged before did* Claude Mods* Dario endorses the same Pacing the Frontier message cosigned by all labs* Last week: Opus 5.5, Plugins portal, Cloud Sessions/Claude Projects* Today: Sonnet 5.5!Today's episode should catch you up, with Thariq Shihipar, the explainer-king of Anthropic, who we last caught up on Fable launch day with The Field Guide to Fable:The Future of Mutable SoftwarePay special attention to Claude Mods (especially the cheatsheet):In general this is also the inverse of the other viral tweet from Thariq:Cloud Brain, Local HandsAnd give a try to Claude Projects:The “hands” terminology is not just an analogy for the local/cloud paradigm that is being built up at frontier coding agent companies like Cognition, but is ALSO particularly relevant to the safety systems discussions that we'll be discussing with Anthropic in an upcoming episode as they prepare to pace to frontier with responsible AI deployment.For those who want Thariq's writing tips we teased at the start of the pod, watch the full video here:From the rapid rise of Claude Code to a future where agents can rewrite their own harnesses, collaborate across teams, and operate across cloud and local environments, the way we build software is changing extraordinarily fast. In this episode, Anthropic's Thariq Shihipar joins swyx and Vibhu to unpack how power users are actually working with Claude Code today, why prompting remains a high-skill discipline, and where Anthropic thinks the agent harness is headed next.We go deep on Claude Code's evolving interface: Ask User Question and elicitation, artifacts as persistent generative interfaces, Claude Tag for multiplayer agent workflows, Projects, model effort, implementation notes, and the new Claude Mods system for customizing the harness itself. Thariq explains why Claude.md may eventually disappear, why the smartest model could also become the cheapest model for many tasks, and why mutable software could become a new paradigm for how applications are built and customized.The conversation then turns to agent security and Anthropic's “Pacing the Frontier” argument. Thariq walks through recent incidents where agents discovered unexpected ways to communicate, exploit infrastructure, reverse-engineer benchmark scorers, and chain vulnerabilities together. We discuss sandboxing, prompt injection, autonomous agents, interpretability, constitutional classifiers, probes, fallbacks, Auto Mode, and why securing increasingly capable agents may become one of the defining engineering problems of the next few years.We discuss:* Why agentic coding went from controversial to the default in less than a year* Why prompting is still one of the highest-leverage skills for working with Claude Code* How expert users build a mental model of Claude and what it can reliably one-shot* Why discovering your “unknown unknowns” matters more as agents become more capable* Artifacts as persistent, generative interfaces between humans and agents* How Claude could split into a cloud-based “brain,” local or remote “hands,” and dynamic interfaces* Claude Tag, Projects, and multiplayer agents and how collaborative agent workflows could evolve* Why spending more time on the initial prompt can dramatically reduce wasted agent work* When to use low, medium, high, or max effort for different engineering tasks* Why frontier models may eventually outperform smaller models on both intelligence and token efficiency* Why implementation notes can expose decisions the model considered but chose not to make* Why Claude.md may eventually disappear — and why starting without one can sometimes be better* Claude Mods: customizing the execution loop, UI, subagents, routing, and behavior of Claude Code* Model routers, forked agents, and supervisor agents that automatically improve agent workflows* Why Claude Mods may be an early preview of “mutable software”* The bitter lesson of harness engineering and why agent architectures go out of date so quickly* How Claude Tag is becoming an organizational harness for multiplayer work* Why giving agents access to company data creates an enormous new security surface* The Exploit-Bench incident where agents discovered ways to communicate and collaborate* Why agents hacked Hugging Face for scorer code rather than benchmark answers* How agents chained sandbox and infrastructure vulnerabilities in unexpected ways* Why increasingly capable agents make traditional security assumptions harder to maintain* The argument behind Anthropic's “Pacing the Frontier” proposal* Why software engineers are increasingly doing two jobs: engineering and keeping up with AI* Constitutional classifiers, probes, and fallbacks and what interpretability looks like in production* How Auto Mode checks whether an agent's actions actually match the user's permissions* Why Thariq can see serious AI risks while still having a relatively low p(doom)Thariq Shihipar* X: https://x.com/trq212* LinkedIn: https://www.linkedin.com/in/thariqshihiparTimestamps00:00:00 Introduction00:04:12 Ask User Question and the Future of Agent Interfaces00:08:29 Artifacts, Projects, and Multiplayer Agents00:15:37 Prompting as the Core Claude Code Skill00:21:52 Context, Effort, and Smarter Model Usage00:28:10 Is Claude.md Going Away?00:32:49 Claude Mods: Customizing the Claude Code Harness00:36:35 Model Routing and the Rise of Mutable Software00:44:40 The Bitter Lesson of Harness Engineering00:50:49 Claude Tag as an Organizational Harness00:55:59 Pacing the Frontier and Autonomous Agent Security00:58:22 Agents Hack Hugging Face for the Scorer01:05:34 What Happens When Agents Need More Compute?01:10:32 AI Coding Is Changing Faster Than Engineers Can Keep Up01:17:17 Probes, Fallbacks, Interpretability, and Auto Mode01:28:32 AI Risk, p(doom), and Closing ThoughtsTranscriptIntroduction: Life at Anthropic and the Pace of ChangeSwyx [00:00:00]: We're here in the studio with our friend Thariq from Anthropic, and I guess generally the Claude Code, I-- there's, there's so much, merging of boundaries and you've been so on top of everything since you joined Anthropic. You have been early to Claude Code itself, but then also, and you've told that story in other podcasts, and you've also been talking about seeing like an agent. Most recently you did the top AIE World Tour talk, Field Guide to Fable, which obviously you guys launched Fable, so that was-- that's cheating. And mostly you most recently also launching Claude Tag, and we're also gonna be talking about Pacing the Frontier. There's a lot going on in Anthropic. I guess top of the question is, what's it like being at Anthropic when there's so much going on?Thariq Shihipar [00:00:48]: I think that It is, like. I think you can get whiplash sometimes. I think, like, going. When I joined Anthropic, I joined because of Claude Code. Like Claude Code had just come out and I was like, “This is so good.” And Opus 4 to me was like just, I could not imagine, like, how good it was? And that was, like, a real moment for me. But I was, like, trying to convince, like, my startup friends to use agentic coding, and they're like, “Oh, no, like, our engineers don't think it's good enough,” or something. And I was like, “That's insane.” and now you, like, fast-forward, 12 months, less, and, like, it's just like, yeah, the default way that everyone codes, right? And I think that, like, just having to go from, like, selling it to, like, now, teaching people how to be. make the most use of it and be more efficient and things like that is just like a big, like big change. And, yeah, I think, like, it's just hard to stay on top of everything as a human? Like, I think things happen so fast and likeSwyx [00:01:51]: You just throw more agents at it.Thariq Shihipar [00:01:52]: Yeah, like that's like the agentic stuff scales much better than the, like, human stuff where it's like, oh, like, there are three things happening right now and, like, they're all emergencies and, like, how do you, like, respond to it? Yeah.Teaching People to Use Claude CodeVibhu [00:02:05]: What do you split your time on? You do a lot of technical writing, engineering work.Thariq Shihipar [00:02:10]: Yeah, so I think that, like, when I joined the Claude Code team, I wanted to teach people how to use Claude Code and I think that, like, that has been something that, like, I thought, like, maybe I would spend a little bit of time on it or, like, I'd, like, do. I was spending some time on the agent SDK first, and I wasn't exactly sure, like, how the bitter lesson would go, when it comes to, like, harnesses, right? Like, I think sometimes we were like, “Oh, like, what's after Claude Code?”? And so initially I was like, I just wanna teach people how to use Claude Code and make it easier to use Claude Code. And I think that has just, like, as the harnesses have gotten better and better, that's like the dominant problem now is, like, how do you use the agents, right? Like, it's like such a high skill expression thing. So I do that and then I do engineering work. I give talks, but I think, like, when I'm doing engineering work, my goal is to take that feedback that we get from users and also, like, then be able to talk about, like, hey, how to use Claude Code to do engineering. So there's like a good loop there. Yeah.Swyx [00:03:07]: Yeah. I'll-- For listeners, we'll attach, the talk that you did with Sarah for the Dev Writers, meetupThariq Shihipar [00:03:13]: Oh, yeahSwyx [00:03:13]: Which we talked a little bit about, well, first you do the work and then you talk about the work.Thariq Shihipar [00:03:16]: Right.Swyx [00:03:16]: Something like that.Thariq Shihipar [00:03:17]: Yeah.Swyx [00:03:17]: It's sow and reap orThariq Shihipar [00:03:19]: Yeah, reap and. Sow and reap.Swyx [00:03:21]: Something like that. Something like that. Yeah, so, and then just to preview a little bit, we are gonna talk about the evolution of the harness. It has come a long way from just being a CLI. We're gonna talk about, Claude Mods, which is starting to leak today, because you couldn't keep it secret.Thariq Shihipar [00:03:36]: Yeah. yeah.Swyx [00:03:39]: Yeah, there's, there's a lot, there. I think you started off with, like, adding ask user question tool, which people love and hate.Thariq Shihipar [00:03:48]: Yeah.Swyx [00:03:48]: Like, I thought it was, like, very innovative, and then now I have, like, my own version. You have your Interview Me version.Thariq Shihipar [00:03:55]: Yeah.Swyx [00:03:56]: And, yeah, everyone just has, like, their own stuff. And, like, it no longer matters ‘cause now you're supposed to, write prompts that create other prompts and loops and all these things.Ask User Question and Human-Agent InteractionThariq Shihipar [00:04:05]: Sure, yeah.Swyx [00:04:06]: So what's the state of the art, today? Like, what are people. what are you, like, telling people to do today?Thariq Shihipar [00:04:12]: Yeah, ask user question was the first time that the model was good at elicitation. I think this was, like, an emergent behavior that I, like, wanted to see if the models could do. I have, like a human-computer interaction background, so I, like, did that in undergrad and grad school. And so this was like. I think it's like human-agent interaction to me, like, trying to figure out, like, how can the agent communicate with you and extract, the requirements, right? I think that, like, one of the things about, like, that's difficult as Claude Code has gone broader and broader is that everyone has, like, their own way of using it, and it's very hard to, like, change the default behavior. So for example, like, if someone asks Claude Code to do something,Thariq Shihipar [00:04:59]: Sometimes they just want them to do the work, ‘cause they're, like, maybe a very good prompter, and sometimes they want. like, are not good at prompting? And you need. like, the agent needs to, like, clarify? And so that's, like, a good split. Like, and the ask you the question tool like, splits along that side where, like, are-- do you feel like you're good enough to instruct the agent as it is, or is the agent able to, like. does the agent need to, like, pull out more requirements and, like, collaborate with you more and really understand your preferences?Thariq Shihipar [00:05:27]: I, on the whole, believe that pretty much everyone is more on the latter than the former, that they, like, have more ambiguity and they know less than they want, than they, like, think they know about the problem. but, like, it's like a interface design problem to make that easy? And so, like, if you're designing a problem, like, or if you're going through a problem, like, things like what's the schema or, like, what's the call stack and things like that are really important. like, the details in the design are important. Ideally, you want to figure out some of these, like, hard problems ahead of time before starting implementation. And yeah, that's why they call, like, unknowns, right? And so I think that this will forever be, like, a skill in agentic coding is, like, figuring out your unknowns. So, like, because even if the model is, like, super intelligent- It, like, needs to know what you want? And, like, you have preferences. like, you need to like, pull the, pull that out. and so that's, like, I think how I'm, what I'm pushing. the question then is, like, how does the agent interact with you? And I think that has been HTML, has been, like, the big way of doing that. And we've recently added artifacts, right? And artifacts, I think we've done a bad job of, like, or, like, I've done a bad job of, like, explaining how to use them fully. We have a lot of property capabilities. They have a database associated with them? And so every artifact can store and write persistent data. They can, like, feed back into Claude? And so, like, one thing that, like, people are not doing yet that I'm trying to, like, encourage is, like, this idea of a dashboard artifact. So you have, like, Claude working on a project long-term. Maybe it's like a kanban or something. it can store that kanban data in its database. Multiple Claudes can access that data via, like, the artifact MCP, and, like, that artifact can, like, talk to those Claudes as well. And so, like, the. We're building the primitives for you to be able to have this, like, generative interface via artifacts that will, like, let you surface more of that rich detail from the agents. And I think that, like, almost everything with agents right now is, like, this problem of, like, you think what you want, but you don't really know what you want, and, like, the agents need a lot of detail, and collaborating with them in the loop is really important. And so artifacts are, like, the, like, way that we're trying to evolve there. But there's a lot of work to do because it's so much more complicated than, like, a multiple-choice question? there's a lot more, like, detail in terms of, like, diagrams and code snippets and schemas or, like, whatever it is for that problem. But, like, artifacts is, like, the mo-more AGI-pilled way of, like, doing ask user question. So yeah.Artifacts as the Interface to the HarnessSwyx [00:08:15]: I think one thing that's unclear to me about these, the artifact stuff is, like, what feedback should go in through the artifact and what feedback should go through a Claude, a chat? Because the more AGI-pilled one is to just feed everything to the Claude.Thariq Shihipar [00:08:29]: I think the more AGI-pilled one is to go through the artifact. Like, and I think that, like, we imagine in the limit, I think that artifacts will be your interface into the harness? You can, like, comment on this, like, live, like, document of your plan, of the work. you can see maybe, like, multiple agents and different agents are doing this, and that artifact is built for the current work that you're doing, right? And so, like, each one has, like, slightly different. I think we're still, like, getting there from, like, an infrastructure perspective. But yeah, I think, like, on-the-fly interface for your harness is probably where things are headed.Vibhu [00:09:03]: Is there a version of it that's an abstraction from CLI or chat and you. Because right now, a lot of it is, okay, you're interfacing with Claude Code, you're having HTML given back for a mockup. It's pretty rich. There's diagrams. Artifacts are ways to connect these together. Why not just do everything that way?Separating Brain, Hands, and Surface UIThariq Shihipar [00:09:22]: Then it becomes, like, separating out, like, where is the inference happening? Where is the intelligence happening? Where is the work happening? like, I think this is like, difference between, like, or, like, some of the distinction between local and cloud, right? And so, I think right now, if you use Claude Code, it's, like, local and, like, you can spin off remote control, for example, to get some cloud behavior, or you can spin off Claude Code in the cloud, right? We're moving towards a place where instead of Claudes, like, you message a local Claude, it starts a session locally and it executes, to more like you have a Claude that you message that's in the cloud that's running. it can run, like, local, or, like, cloud sessions. This is how Claude Tag works. But, like, over time, we'll add, like, local hands as well. And so, like, local hands will be the ability for that agent to access your computer if it's online, and be able to, like, work there. And so it can spin off many different subagents. It can, like, commu- those subagents can communicate with each other, and that's where the artifact comes in to display all of that work. So you can imagine, like, the. You're separating out these things. So there's, like, the surface UI display that's an artifact and hosted somewhere and has a database and everything. There is the inference intelligence, right, that's happening on the cloud, and you don't have to worry about shutting off your computer or whatever, right? and then there's the, like, hands. Like, and it can be local, it can be in, like, a remote sandbox or wherever you need your work to be done. That's like unpackaging, like, the Claude Code experience right now where, like, right now it all happens in one place, right? So.Multiplayer Agents, Claude Tag, and ProjectsVibhu [00:11:00]: How do you see, like, the multiplayer side of that? So say teams want to work in this way. Right now it's very individual, but how do you see the future of multiplayer? Like, right now, I guess there's Claude Tag, which is a version, but.Thariq Shihipar [00:11:12]: We're launching projects. And so projects is the, like, this abstraction that's like Claude Tag, but on our Claude products, right? So you can message it and, like, it will do the Claude Tag-like stuff, like spinning off subagents. So We think with multiplayer. Like, Claude Tag is, like, a little bit more native multiplayer because it's just, like, in your Slack and the permissions are all figured out and stuff like that. But I do think multiplayer is, like, an important part of the story and, like, that will need to get tied together more. Like, you can imagine how complicated it gets when you're like, oh, you have hands, but now you have other hands in other people's computers too, and, like, you need to, like, permission them or, like, you have, like, your MCP and someone else's MCP, and how do you figure out how to use them, right? It gets, like, quite complicated. And Claude Tag does a good job of, like, sanding down all of these issues, right? So that, like, when you have, yeah, Google Docs, how does it access Google Docs, right? Like, it accesses through the shared Claude MCP, or it can access through your local credentials as well if it doesn't have access. But yeah, I think Claude Tag is our multiplayer, product, and it's really useful for these, like, things that are inherently multiplayer. Like, okay, like on-call, for example, incidents are inherently multiplayer. You want to tag Claude, you want multiple people to log in, you want it to be able to find context. I think whenever I'm, like, working on something and I want, like, privacy or security or, like, I want other people to review it's really nice to, like. I'll have a channel per project and I'll, like, at legal, for example, be like, “Hey, like, I want to ship this. Can you, like.” Like, here's. Like Claude knows everything, just chat with it. And that way legal gets precise answers, on like what exactly is shipping into the code, and I don't need to be in the loop, right? So I think like multiplayer is getting like more and more like, yeah, everyone can participate with Claude. I think Claude Tag is like that product and like projects will start off single player and will like, expand.Swyx [00:13:14]: I think there's a question about like maybe dual questions about identity and the unit of isolation.Identity, Permissions, and IsolationThariq Shihipar [00:13:20]: Yeah.Swyx [00:13:20]: Claude Tag, you specifically chose to make it its own identityThariq Shihipar [00:13:26]: Yes.Swyx [00:13:26]: Which is like, a controversial choice. There's, there's other ways to do it.Thariq Shihipar [00:13:30]: Yeah.Swyx [00:13:30]: Claude Projects probably it sounds like, if it's anything like ChatGPT Projects, it is, the isolation is that artifacts, that cloud instance, everyone's collaborating on this. It'll. It sounds like, it should be like if you're, if you're collaborating with legal on a thing, like that channel should be a project, right? Like it's not yetThariq Shihipar [00:13:50]: Yes.Swyx [00:13:50]: But it. that's the natural next step.Thariq Shihipar [00:13:53]: Yeah, like I think in Claude Tag, it's effectively. Like Claude Tag, you have to do your own arrangement. And so Claude Tag, yeah, each channel is like you can name it as you want, and I nameSwyx [00:14:04]: Yeah.Thariq Shihipar [00:14:04]: Like each featureSwyx [00:14:06]: Yeah.Thariq Shihipar [00:14:07]: As a channel.Swyx [00:14:07]: And, but I think like there is some trans- like it's unclear when there is transference, because let's say it is. if you have a coworkerThariq Shihipar [00:14:14]: Yeah.Swyx [00:14:14]: Who is tagging on all these things, yes, there is transferThariq Shihipar [00:14:16]: Yeah.Swyx [00:14:16]: Because it's the same person. but with Claude, it's unclear if it's like necessarily like, well, no, you don't know any of. you don't know about the other stuff. You should only use this stuff.Thariq Shihipar [00:14:25]: It's like the tip of the iceberg meme, right, where you can like. This is what we spend so much time onSwyx [00:14:31]: Yeah.Thariq Shihipar [00:14:31]: Is like there is like infinite surface area of like, okay, you want Claudes to. Not infinite, but like there's like surface area, a lot of like, surface area to figure out of like permissions and visibility and like how can you let Claude operate as well as you can, as safely as you can? And obviously, this is very important to us because like security for our code base is very important. And so we've put a lot of time into this. Yeah, there's so many like edge cases you can figure out where it's like, oh, like, yeah, this Claude in this channel has different permissions, but it can message another channel, and can't it exfiltrate data that way? Or like can you like. What if it uses your MCP and then messages someone else? Like there's like so much, and we've like really put a lot of work into sanding it down.Swyx [00:15:14]: Yeah. Lots of work. okay. Fable?Fable and the Meta-Skill of PromptingVibhu [00:15:18]: Fable, you wrote two good articles. you've written many good articlesThariq Shihipar [00:15:22]: Yeah.Vibhu [00:15:22]: But on, Field Guide to Fable, Building Claude Code. I'm curious from what you've seen, is there any common patterns that you see in like top users at Anthropic externally? Like what are best practices for getting the most out of Claude Code?Thariq Shihipar [00:15:37]: The like meta skill I say is like prompting is like very important? And like that. Like I think this is like not trivial to say because I think a lot of people are like, “Oh, prompting doesn't matter. It's just like I can just say a sentence and Claude will do it.” And I think prompting is really this like, this. It's like public speaking, like, or writing or something, and for a specific audience, and that audience is Claude. And you need to like build a mental model of Claude and how it thinks and how it works, right? And so that's like the most important skill in working with Claude Code is like having this mental model, right, of Claude and like what it can do well, what it can one-shot, what it can't. And so many people when you see prompting, they're just like, they're short prompts, but they have such a good mental model of Claude and of like the code base and things like that like it's effortless? But it's like high skill ceiling. So like that work of like, spending a lot of time prompting and building mental models of how, and intuition for how the agents work is really important. And then I think like the next thing is like the unknown stuff we talked about earlier, where it's like being able to find out like your, what you don't know or what you haven't written down, learning about like different things. I think as Claude can do more and more things, the likelihood of you doing something out of distribution for you and like you have low domain knowledge on is very high? And the more you can like learn the vocabulary to be able to prompt Claude, it becomes really important. And so like I think the most important unknowns are the unknown unknowns, where you're like, I just like don't even know that this exists, right? Yeah, exactly. I think that's like a illustration of like the map and the territory, right, where you're like, “Okay, this is my prompt,” and the territory is like the actual like work that the agent needs to do, right? And if you are like very precise, you can give more precise things, right? So like for example, in design, I'm not very precise. I'm not a designer, so I say like, “Give me like eight different mock-ups.” But if I was a designer, maybe I'd be like, “Oh, hey, here are some reference sites.” Like, “I want this type of font and this type of like look to it, and here's like a few different components to like visualize. Here's a Figma MC board to bring in,” like. And so you can just be so much more precise with that language. And if you're not a designer, you just need to like try and learn the language or learn the unknown unknowns. And this is true of like everything, I think. Like the more, like you can work with Claude to learn like how things work, the better your prompting will be. I think another good example of this is like game design, like where a lot of people are like, “Oh, like I can vibe code a game now.” And they're like, “It's not fun.” And like it's just like the thing about game design is like every one of these choices has like a lot ofTaste, Domain Knowledge, and Learning the VocabularySwyx [00:18:25]: Variations.Thariq Shihipar [00:18:25]: A lot of like craft to them. So it's like, oh, okay, like when you're making a flying game, the feel of the plane and the like, way it responds to your controls has a lot of like. Like, a game designer would spend like days on that. Do? and likeSwyx [00:18:44]: To me, that's what taste is, right?Swyx [00:18:45]: Like it is like from the possible space of one thousand mathematically valid answersThariq Shihipar [00:18:49]: Yeah.Swyx [00:18:49]: Here's the one that is the humans will like.Thariq Shihipar [00:18:51]: Yes. Yeah.Thariq Shihipar [00:18:52]: I think with taste, I'm like torn on this word ‘cause I think you're right, but everyone has different definitions, and it sounds kind, sounds like low skill or like elitist almost, where you're like, oh, like there are certain people with taste?Swyx [00:19:06]: It's like taste is what I call taste.Thariq Shihipar [00:19:07]: Yeah, exactly.Swyx [00:19:08]: And it's like these guys don't have taste.Thariq Shihipar [00:19:09]: Yeah, exactly. Oh, like an engineer doesn't have taste. Like I, the like founder, have taste.Thariq Shihipar [00:19:14]: ? And I think that's not true. Like I think like the engineers have a lot of taste for these particular like problems? And I think everyone has taste for particular problems. I think like Jason Liu, like say like in order to, yeah, have taste, you have to eat?Thariq Shihipar [00:19:32]: And I really like that, where it's like, okay, you have to like do a lot of things. You have to like iterate and figure out what you want, what you like, and, like build that like domainSwyx [00:19:41]: YesThariq Shihipar [00:19:41]: Domain vocabulary. And then when you're prompting, you're like synthesizing all of that for a product.Swyx [00:19:46]: Isn't it annoying when someone else says it better than you?Swyx [00:19:48]: It's just like, f**k, I have to quote this guy forever.Vibhu [00:19:51]: Having to quote Jason Liu forever.Vibhu [00:19:53]: He's gonna love this.Thariq Shihipar [00:19:55]: So I get prompts, more than that.Vibhu [00:19:57]: And sometimes it's not even that. Sometimes it's just intuitive, right? Like you don't realize you even want something till a model puts it out, and you're like, “Oh, this just feels immediately better,” right?Voice Prompting and Information DensityThariq Shihipar [00:20:07]: Yeah, exactly.Swyx [00:20:09]: One thing I go back and forth on is I feel like the way I prompt half the time, let's say I use voice.Swyx [00:20:16]: Did I say voice? Other people have voice. that is the opposite. That is just like me rambling for like two minutes Pressing down the function key and then let go, and then like hopefully it figures it out. And oftentimes it does.Thariq Shihipar [00:20:26]: Yeah.Swyx [00:20:26]: But it's not as thoughtful as like a structured prompt with like Well-run communication as though it's a PRD or a memo. Is that in line with how people do this? There's like bimodal prompting where there's some prompts where you spend a lot of time upfront and other prompts you just dash it off?Thariq Shihipar [00:20:43]: I don't think the voice is necessarily low. Like I think it's like more like how much information is in the prompt. like the model can. Like you can and like add some sentencesSwyx [00:20:53]: RightThariq Shihipar [00:20:53]: And be like, “Oh, like I changed my mind,” like in the middle of the prompt, and it will be able to follow that perfectly? So I think the like actual format of the text is less important, but then like the ability to. Like how much information is in it, right? And I think for voice, a lot of times, going back to like human-agent interaction and like for a lot of people, it's just way easier to talk than to like type? and I. If that gets more information out of you, like that's better.Vibhu [00:21:21]: At some level, it feels like just giving the model as much contextThariq Shihipar [00:21:24]: YesVibhu [00:21:24]: Over prompting before you kick off is a best practice. I don't know. A lot of the times, like when I was first trying out Fable, I spend a solid 30 minutes like really crafting a long prompt. This, I think, is a response of models running for longer and longer, right? It's still a little difficult to nudge them as they're in like, in the loop, but I just like intuitively spend more time kicking off that first prompt and working with it a lot.Spend More Upfront, Iterate LessThariq Shihipar [00:21:52]: My personal opinion is that if I was a software engineer, if I was like, just running my own startup, for example, I think I would mostly fit, stick to a max 20x? like maybe verification and so code review are like separate things. But I think like what I see a lot of times is people hit rate limits when they're doing this like, oh, like it did a lot of work and you're like, “Oh, I don't like this.” Like, “Can you like undo this and redo it?” And then you're like iterating on this like thing that the model could have done if you had like spent more upfront time or given it better context? And instead it's like you're like, “Nope, don't like that design. Try this.” Or like, “You messed this up,” or something like that. And then that just eats up so much more of like, your usage. And so that's like, I think maybe like a key like tip both for like efficiency as well, right? And yeah, I think like context, and not just like context on like what the goal is good, right? Like are you building a prototype or is it like a production thing? Like where can you spend compute or when, where can you not spend compute? Like I think you have to give the model permission or like not permission to do things sometimes where, like it doesn't know intuitively how much you want to spend on this task, right? And you can use effort for this. So I did-- I'm working on a blog post about that where it's like, if you want. For like we see that effort scales with the complexity of the task. So for security, effort gets like way more results. Like high effort versus like low effort gets, like changes the evals a lot. But for software engineering, it doesn't change it a huge amount because effort is mostly spent on the verification and the like edge case testing and things like that. And so like being able to like give the model that guidance of like, “Hey, this problem is something that I think I want you to spend a lot of time verifying and edge case testing,”?Effort, Model Choice, and VerificationVibhu [00:23:43]: How about model in the mix? So, there's Opus and Fable with effort.Thariq Shihipar [00:23:47]: Yeah.Vibhu [00:23:48]: There's also Haiku in there.Thariq Shihipar [00:23:49]: Yeah. It's not quite true yet, but it's very close where I think the frontier models will be Pareto dominant over like almost everything. like maybe. And sometimes I think Opus might be Pareto dominant. Do? Like I think depending on like how things, like shake out if it's like a newer version of Opus. But I think that like increasingly it's just going to be like the smart model is going to be able to like do the simple task for less tokens than the like the other models because of verification. With verification, in the limit, your model doesn't need to verify, right? If it's a perfect model, it just does the work once and it's like, okay, like you, I did it? And increasingly with Fable, I'm like, I'm like, “Dude, you don't need to spin up Chromium and screenshot all of these things.” Like I see it. Like you did it, right? And so a lot of the. At higher effort, you spend more of those tokens verifying. But if you're working on simpler problems, and a lot of software engineering is like well, like in Fable, like low and medium stability, it can spend less tokens verifying. And as the models get smarter and smarter, they will just be able to like, “All right, done.”? Like, I can run the lint for sanity's sake, but, like, I, like, know it lints? Like, you don't even need to do that. And that will be so much more token efficient than, like, the smaller models. Yeah.Swyx [00:25:15]: Is there a good, practice on our side that we can use to see if we're using too much effort? Like, I freakingThariq Shihipar [00:25:23]: YeahSwyx [00:25:23]: Hate wasting time on that stuff.Thariq Shihipar [00:25:24]: Yeah. I know what you mean. I think, like, so in this blog post, my rough distribution is, like, code review and security should be, like, high or max and, like, software engineeringSwyx [00:25:37]: You said recommend mix settings per domain.Thariq Shihipar [00:25:37]: Yeah. I think, like, if you're doing, like, UI or something like that, like low and medium, I think is you're building, like, an API and you want to make sure, like, you cover enough edge cases? And so I think building, like I said, that mental model of, like, how things work across these distributions is, like, yeah, part of the job.Implementation Notes and Decision LogsVibhu [00:25:56]: This is more intuition-driven or eval? Because I'm guessing this would change as you go.Swyx [00:26:00]: He has evals.Thariq Shihipar [00:26:01]: Yeah. So what I did in the blog post is I go over all of the terminal bench evals. So there are, like, 70 problems and I'm show that, like, okay, like, in the security problems it does more. and then I also, like, look at some of the transcripts just in terms of, like, how-- what does it answer, what does it forget or something. And a lot of times, this is another prompting tip I have, is, like, asking it to make decision notes or implementation notes because, in every eval problem that it faces, it thinks about the correct solution, and decides not to do it. it's like, oh, like, here is the answer. What if I did this? And then it's like, oh, probably not? and then keeps going. And this is, like, the majority of the failures, at, like, a higher max level. It's very rare that the model just doesn't know how to do something. If you just have these implementation notes, then you can review and you can be like, “Oh, I want you to do this thing that you didn't do.” The models are getting better at surfacing that overall. Like, I see in the transcripts of Fable 5.1, like, when it does this output, it will call out its decision-making as well. but making this more explicit in the harness is better. And now we're, allowing ways of you modifying the harness so you can, like, add someVibhu [00:27:23]: Ooh.Thariq Shihipar [00:27:24]: Calculate with there. Yeah.Swyx [00:27:25]: Yeah. So I do wanna call out two things that you mentioned that I think exist outside of prompting. One is like, let's, let's call it the prompt that is so important that it shouldn't be in a prompt. It is in Claude.md or Agents.mdThariq Shihipar [00:27:38]: YeahSwyx [00:27:38]: Which is like goals, right? Like your situation, your goals, the things that you want, the thing. and then second of all is the decision log or the experiment log or whatever log of traces that you might want to survive the current session to do those things. Those are, like, externalities that there's no standard. There's no-- It's not like skills. It's not like MCP. There's no standard. It's, it's just like it's a markdown file. first of all, is that right? Is Claude.md going away? You have a documented dislike of, Agents.md, but you're gonna do it?Claude.md, Agents.md, and Model-Specific InstructionsThariq Shihipar [00:28:10]: Yeah. Okay. So Agents.md, yeah, like, we're, we're gonna do it. I think it's just, like, different models are very different from each other? But I realize that it's, like, such a pain to, like, maintain different ones? And yeah, like, as the models get better and better, the floor of how they accomplish the simpler task is better. And so I do think in the limit, Claude.md goes away, and maybe not even, like, that far. Like, I think, like, I think that right now it might be better to start a new project without a Claude.md.Swyx [00:28:44]: Yes.Thariq Shihipar [00:28:44]: I think that, like, maybe if you see very repeated failure modes, you add them to your Claude.md. The really tough thing is that this changes per model. And so, like, if you've added a bunch of failure modes or, like evenSwyx [00:28:57]: So you need Fable MD, you need Opus MD.Thariq Shihipar [00:28:59]: Or well, even Fable 5.1 versus Fable 5.Swyx [00:29:03]: Yeah.Thariq Shihipar [00:29:03]: Like, it is annoying. Like, I'm not like,Swyx [00:29:05]: YeahThariq Shihipar [00:29:05]: Like, we don't, like, do this on purpose? It's just, like, how the models work, right? And so, like, maybe, like, Fable 5 had this, like, failure mode that Fable 5.1 doesn't. And if you keep this context, this running log of a bunch of different failure modes, they will probably over constrain Claude? And so this is like. we just added evals plugins for skills.Swyx [00:29:28]: Yeah.Thariq Shihipar [00:29:29]: And so now you can eval if a skill is better. I think Daisy on our team did this. And so, yeah, this is like we're trying to work on this. We know it's, like, you still have to spend tokens on it and, like, it's not, it's not perfect, but it's, like, we're trying to help out with this problem.Swyx [00:29:44]: And so, and as far as prompting goes, the one tip I wanna offer is, something I have told people a lot is sufficiently advanced prompting is indistinguishable from sufficiently advanced executive communication. So I've referred to-- This is an executive comms workshop from Heavybit that is the best I've ever seen in my career. And they teach this thing called the SCQA model. Just Google it. It's a, it's a thing. Like, people have done prompting for decades. It's just called executive communication. It's like when one person has to communicate to thousands of people down the org chart, this is what you do. so situation, complication, question and answer, is how you write the memo. but obviously sometimes you don't have the answer, but you can at least list out the SC and Q, and then they have some examples in there. So just leaving breadcrumbs for people if they want to explore.Underrated Prompting Patterns and ELI5Vibhu [00:30:31]: Before we move on, I wanna ask you, any other underrated tips, ways people could get a lot of value from Claude Code that they're not using?Thariq Shihipar [00:30:41]: Yeah, I think a lot of them are in the, this unknowns, like, doc. Like, I give a bunch of example prompts, like, using it for brainstorming, using it to quiz you after. we added this, like, explain it like I'm five skill which is a very short prompt. And it doesn't even say explain it like I'm five. It's like the key word of this prompt is big pictures, few words. like, that's like the main thing. And it is shockingly good? Like, you, like, I think I tweeted about this and it's like /eli5, and, like, you can install it as a plug-in. But yeah, it's, like, way better at just cutting through the BS and being like, yeah, exactly right here. So the diagrams are, like, quite clear. I think one of the things that is true with artifacts is, like, they put too much text in and people are not reading the artifacts? And so, like, this simplifies it a lot more. And, yeah, this came out of, like, just people at Anthropic, like, going through very complicated incidents and being like, “What is happening?”? So, this one I think is great, yeah.Swyx [00:31:47]: My version of this is the, it's like test your understanding. Give you a few choices and then, like, if you get it wrong, you have a mismatch between what you think is happening versus what's happening.Thariq Shihipar [00:31:58]: Yeah. I think this is one of those things that everyone loves talking about, and then very few people really do. Like, I thinkSwyx [00:32:05]: Really helpful.Thariq Shihipar [00:32:07]: Yeah. But most people just don't want to get quizzed about something? Unfortunately, I think this is one of the, like, things that we need to, like.Swyx [00:32:16]: What's the opposite of ask you the question or ask you the question before the thing?Thariq Shihipar [00:32:19]: Yeah.Swyx [00:32:19]: This is after the thing.Thariq Shihipar [00:32:20]: Exactly. Yeah.Vibhu [00:32:21]: It's a good way to stay grounded of, like, do you even know what you're doing, right? The worst case is when people send you slop and they haven't understood what they're asking for or what the output is, and it's like, “Dude, I don't wanna read this. Do you even know what it is?” So, you make it a rule for yourself that before you send stuff, you should at least know what's implemented.Claude Mods: Customizing the HarnessThariq Shihipar [00:32:41]: Yes, but so you could make this a mod and you could build your own mod to, like, make sure you test it. So yeah, you can do that.Swyx [00:32:49]: All right. Let's get right into it. What is Claude Mod, and what is this diagram showing?Thariq Shihipar [00:32:54]: Yeah. Okay, so Claude Mods is you can customize the entire Claude Code harness, and we're going to. If you have requests, we will, like, let you, like, please let us know. We'll add more and more. This works for CLI, it works for desktop. maybe it will work for Claude Tag in the future. I don't know. Like, we're trying to make this very extensible. You can see this reference sheet. I don't want people to get overwhelmed by it? At a high level, you can customize both the execution of the harness, and the UI of the harness. And so, like, you say on that Tetris example from Boris, that's like customizing the UI, right? Like showing, like, Tetris in the game.Thariq Shihipar [00:33:35]: But, like, let's say that you wanted to do this thing where you had. you tested your assumptions or, like, tested your understanding after every project, right? What you would do is you would ask Claude to make this plug-in. It would spin a classifier after every prompt. And so, like, at the end of each turn, you would spin off a sub-agent or, like, a forked agent. A forked agent is, like, maintains the prompt cache, right? So it's like a, like one of those unintuitive things where you can fork and do, like, a little request, and it'll be very cheap because the entire prompt cache is, like, done. And so you can be like, “Has this task been completed?” likeSwyx [00:34:18]: This is how you do BTW and all those.Thariq Shihipar [00:34:20]: Yeah. The underlying forked agent, yes. But so you can, in the f-fork sub-agent, you can say, like, “Has this task been completed? If so, return true.” And then in your hook, or in your, like, plug-in mod, or sorry, like, in the sub-agent probably, you would say, like, “If true, give me a quiz.” give me questions and answers, and then, like, in a JSON format, and then you'd parse it, and then you display above the prompt input, this list of questions, right? And so this is something that's, like, slightly token-intensive because, like, you have to do it after every end of the assistant turn. But it's, like, a lightweight classification, and then you can, like, get this quiz, and then you'll see, like, Claude will always do it for you. You don't need to remember to do it. There are lots of these, like, tips that we've talked about, right, where it's like, oh, implementation notes. You can also add a tool for implementation notes now. And so, like, this tool that I'm adding is, like, register, like, I think assumption is what I'm calling it, but, like, maybe I'll change it around. And this is a mod. And so, like, you give it a register assumption tool, and then it will keep a list. It'll. Every time it does it'll keep a, like, add to the list, and then at the end it will display those assumptions? Another mod I'm working on is a model router. And so, like, internal, like, Claude model routing, right? So it's. This is, I want to say the reason we don't do model routing by default is, like, it's a hard problem? And likeForked Agents, Assumption Tracking, and Model RoutingSwyx [00:35:51]: You will get it wrong.Thariq Shihipar [00:35:52]: Yeah, you, like, yeah, you will, like, accidentally use, like, Fable for a hard problem or Sonnet forSwyx [00:35:57]: Yeah, if you have auto approve, but you don't have auto mode.Thariq Shihipar [00:36:01]: Well, you will have auto. Like, you don't have, like, auto routing or something.Vibhu [00:36:04]: You don't have auto mode for model picker.Thariq Shihipar [00:36:06]: Yeah, exactly. SoVibhu [00:36:07]: I'm getting the rough question of, like, how much do you open this up and how much do people have to think about this? Like, when you talk about prompt caching and building a router, it seems like you could easily build a mod that routes per query, and I'm just killing my plan very fast, right? I guess my question is more so, like, what is, like, a product talk like this look like, right? Who is it for? Is it for power users? Is it everyone should be able to go throughSwyx [00:36:33]: Oh, definitely power users, right?Thariq Shihipar [00:36:35]: Yeah, I think it is power users, but, like, the nature of Claude Code is that so many people are power users? Because it's easy to share things, like you can. Like, one person can make a good model router thing that doesn't break prompt cache all the time, and then you can, like, compose them. Another cool thing about the plug-ins is that they can hook into and compose with each other. And so I have, like, a mod that will, like, create a mode selector at the top, and any plug-ins can register to be a mode. And so, like, the auto router can be a mode, right? Or, like, you can have a mode that's, like, artifact mode, where it's like it primarily talks to you in artifacts. like, you can toggle between plan mode? And so, like, you can create more and more of these modes. But the ability to create modes is in it itself a mod? And so there's a lot of richness here, but we do want to make it fairly easy. We want to be-- make it so that you can just, like, install someone else's. You can ta-- you can chat with Claude and, we'll, like, make sure that it understands the nuances of things like prompt caching and stuff, so it can, like, warn you. This is, like, not extremely complicated behavior for Claude, I think, but we should have just a good skill on how to make mods. and yeah, we'll see how we go. But I do think that this is, like, a preview of, like, mutable software, and, like, how, like, generative software, just like you can customize safely. If enabled, you could customize any piece of software. And I think that more and more apps ideally do something like this?Power Users, Modes, and Mutable SoftwareSwyx [00:38:13]: And by the way, you, we have, you have another cool tweet about how, there's the infinite money button, which is like make your SaaS, consumable by agents. I think mutable software is interesting and, other people have also tried to do it. I think the hurdle comes when you can do everything, then people, users get, tend to get confused. So usually the stuff that works is just like one opinionated flow. This is in the side of less opinionation. It's just like, well, more power to power users. And I think probably unlocked by AI, where, like, you can just prompt for whatever the thing is.Thariq Shihipar [00:38:47]: Yeah, or there can be a skill that gives the opinions?Mods vs. Hooks vs. ArtifactsSwyx [00:38:50]: Yeah.Thariq Shihipar [00:38:50]: And then, yeah.Swyx [00:38:51]: So knowing a little bit about, like, TypeScript and build systems and all these things, the closest-- I'm very curious that the team who worked on this, if, I don't know how close you were to them, if they drew any inspiration from build systems like Babel, Webpack, all these, like, old school things. Because it sounds very similar, like the plug-in ecosystem of those things where they can compose with each other.Thariq Shihipar [00:39:11]: Yeah, I'm not deep in the technical details, but I do know it was a collaboration with someone on the Bun team and someone on the Claude Code team.Swyx [00:39:17]: Yeah, it's a build system mecca.Thariq Shihipar [00:39:19]: Yeah. Exactly. It's, it's very exciting. But yeah, like, agents can just do this very complicated like, extensibility into your software now. And so, yeah, like, another reason to, like. If you run a startup, like, you can just prompt Claude and be like, “Hey, like, could we make an extension system? Like, what would that look like?”?Swyx [00:39:37]: Yeah.Swyx [00:39:38]: And I just really wonder, like, you had hooks in the past and plug-ins, all these things. So what specifically will mods be able to do that those things could not do?Thariq Shihipar [00:39:47]: Internally, we were originally calling this function hooks. And so, like, that's, like, gives you a little bit of an idea where, like, hooks register a, like an event to happen and then, like, a script to call. And this inside of the, like, TypeScript runtime is running things. And so, like, you get some benefits of just, like, it has a bunch of things in the Scope with, like, for example, like how many turns is in this conversation, right? Like, how many tokens have been used? Like, et cetera. Like, what are the messages? Things like that. So it has a bunch of messages that can be used. And then it's just, like, a lot more hooks. So we have, like, or a lot of, lot more, like, things you can register on. And then you can do because of the. because it's all happening in process, you can, spawn sub-agents, with four contests and contexts and stuff. And, like, that will return. You can parse the results of those. You can use structured output to like, return them. and then you can modify the UI, which you can never do in hooks. So, yeah.Swyx [00:40:50]: Yeah. Yeah. So modify UI, this is why you showed the Tetris example. Does it also ex-extend to artifacts? I assume it does.Thariq Shihipar [00:40:57]: You-- Like, artifacts are like a different way of customizing it. like, you can definitely. One of the mods I'm working on is, like, this dashboard mod, which will, like, prompt Claude to maintain a dashboard, that's an artifact. But they're like, slightly orthogonal, or not orthogonal. They compose with each other in different ways. Like, mods are, like, a little bit more, like, in your Claude Code harness, changing the agent loop? And, like, the UI is, like, an added benefit. and then artifacts are just like you want to, see things at a high level, very inter- highly interactive. like, the affordances can be a lot bigger than, like a TUI or even in our desktop.Next Steps, Supervisors, and Persistent GuidanceVibhu [00:41:40]: I'm guessing you'll have a good blog post on the differences, because right now you can also, make a loop that outputs to an artifact that's an interactive dashboard, but you can also do it with a mod. There's just some thinking about making a hacking on a harness when we don't know much about the harness, right?Thariq Shihipar [00:42:00]: Well, something I'm excited about with mods is, like, there's so much things with Claude Code that you just have to remember? You're like, “Oh, like, let me do this, and then let me call the dashboard skill that does the loop,” and things like that. And, or like, “Let me test my assumptions afterwards.” And I think, like, if you do all of these things using these little classifiers and stuff, and you're like, “These are the things I care about. This is what I want to do,” you can, like. You don't have to remember as much. One more, like, mod I'm working on is a next steps mod thatSwyx [00:42:28]: I have-- I was gonna say, I have a next step skill. I always run next steps.Thariq Shihipar [00:42:32]: And does it have access to your skills? Like, this is one of those things where I'm like.Swyx [00:42:37]: I think so.Thariq Shihipar [00:42:38]: Okay. Yeah, probablyVibhu [00:42:39]: Do skills need specific access toThariq Shihipar [00:42:41]: Well, I think there'sSwyx [00:42:41]: Don't they always haveThariq Shihipar [00:42:42]: I think there's, like, specific prompting, I guess, to, like, know your skills. Like I think Claude forgets them sometimes throughout, like, the thing. But anyways, the idea of, like, yeah, next steps that also are like, “Oh, hey, this has happened. Use the explain skill to explain to you what happened because this seems, like, quite complex,”? Or, like, yeah, “Use your unknown skill. It looks like you are, like, asking the model to, like, iterate on these small changes. It seems like you could prompt better.” like, “What if you did this?” Right? So, I think, yeah, like spending more compute there. Yeah.Swyx [00:43:20]: And it should always come out as multiple choice. we have, I haveVibhu [00:43:23]: We have his skill.Swyx [00:43:24]: My next step skill is like this.Thariq Shihipar [00:43:26]: Okay, perfect. Yeah.Swyx [00:43:27]: You can steal it.Thariq Shihipar [00:43:28]: Yeah.Swyx [00:43:29]: Like, but like, for me, it's all-- I think models really always need to be reminded, what are you trying to do here?Thariq Shihipar [00:43:35]: Yeah.Swyx [00:43:35]: Look at the whole transcript and go like, oh, was this original goal? Did your solution solve it? Were you lazy? If you're lazy, maybe there's a reason. Maybe you needed approval from me. Maybe you needed, there's two things you wanna suggest. So it's, it's a little bit like the modification of the ask user question or interview me skill. so it's next steps.Thariq Shihipar [00:43:55]: Yeah, exactly. And again, the benefit of doing it with mods is you can do it as a fork sub-agent, and so it doesn't remain in the context afterwards. So you have this, like, idea of like, okay, the model is doing its execution and you have this almost like supervisor, like, that is like making sure that you can do like the next steps well. So yeah.Swyx [00:44:15]: Yes. I do have two panels and like I often try to have a supervisor thing, keep the high-level context and then the implementationThariq Shihipar [00:44:21]: YeahSwyx [00:44:22]: Detail in another agent.Vibhu [00:44:23]: I feel like a lot of this abstracts away as models change? The, like, half an hour ago you said bitter lesson of harness engineeringThe Bitter Lesson of Harness EngineeringThariq Shihipar [00:44:31]: YeahVibhu [00:44:31]: And we're on the other extreme right now, I feel.Swyx [00:44:33]: Well, so yeah, exactly. If everything's customizable, what is Claude Code, right?Thariq Shihipar [00:44:37]: Yeah.Swyx [00:44:37]: And which I talked to you about last night.Thariq Shihipar [00:44:40]: Yeah, I think that this is. I think the bitter lesson is unintuitive? In terms of like. Also, like we're misusing a little bit of the bitter lesson here where it's like, it's more about like scaling and compute and stuff. But like, I think there is something where it's just like. I think I use it as an approximation here to say that harnesses go out of date very quickly? And like how, but how they change is unintuitive? And so like the big obvious example is like from chat to like agents where you had to give them entirely new tools, right? But like, I think this new version of like, oh, it can modify its own harness, right? This is like, an own harness loop is like a way of using its capabilities, right? Or like it can build an artifact. And like, I think the way I think about it is like the models have more and more intelligence, and they're like so much more intelligent now than like the average software engineering task. Like, you look at the like terminal bench ones and they're like solve like the Jacobian conjecture. Not really, but like, it's like they're, they're quite complex. Like, I would not have been able to do this really as a software engineer.Swyx [00:45:42]: And you said TB4 or TB2?Thariq Shihipar [00:45:43]: TB3. TB3.Swyx [00:45:44]: TB3.Thariq Shihipar [00:45:44]: Yeah. They're quite complex, but the goal is still to deliver user value, right? And like you said, there's like this infinite space of things to do. And so the ways like you spend compute are to keep the user in the loop and make sure that like you're getting to the right decision in the end of the day and like the right output. And artifacts and mods are this way of like spending that intelligence. and I think that's like, yeah, the next step. And so, yeah, I think Claude Code is like, has the core things of agent loop which are, have gotten more complicated. It's like, it needs a sandbox to operate safely. It needs auto mode to like make sure like the permissionsVibhu [00:46:21]: Approvals.Thariq Shihipar [00:46:21]: Yeah, approvals. it needs computer use and MCPs and like all of these like ways of accessing your data, and it needs web search and web fetch. And like, so the-- as the models can do more and more, the core harness has to be like quite complex and very secure. But then like how you interact with it can change quite a lot.Vibhu [00:46:42]: What other harness engineering best practices have you, from the Claude Code team itself? I feel like, there was a phase of plan mode, which is not as used. We now have auto mode. at a point you cut the majority of the system prompt, you got rid of examples. What other best practices are there for harness engineering?Core Harness Primitives and Managed AgentsThariq Shihipar [00:47:02]: I think there is like a forking path where at some point, eventually, yes, the model will just be able to like vibe code the exact version of Claude Code, even describing all this complexity that I've talked about, right? Like auto mode and computer use and stuff. Eventually, the models will just be able to do that in one shot. But I think they can one shot simpler harnesses? And so like, I think some people. Sometimes you don't need this full, like if you don't need computer use or like all this like more complicated stuff. I think before we, you had to use things like the agent SDK, which was like Claude Code wrapped, in order to like. And I would, like suggest people do that because there was so much complexity into building a harness. And now as that's got more abstracted, we have like, Claude managed agents, which lets you have that complexity, but still like, right, like a very bare bones like harness that's scoped to your task. Yeah, I think there's like this barbell effect where like for like very complex, for like coding task and like these like complex things, you should use our harness. And then for like a lot of like simpler or like, more domain-specific things, you can build your own harness because Claude has gotten better at building harnesses, and we have these harness primitives like managed agents. So yeah.Swyx [00:48:18]: Yeah. Is there a general progression? Let's say chapter one was ultra code dynamic workflows, then chapter two was cloud mods. Where is this going?Swyx [00:48:29]: Where you're, you're, you can customize the thing on demand.Thariq Shihipar [00:48:36]: Yeah. I do think that like this evolution of projects and like artifacts and splitting out like brain and hands and, surfaces is like where things are going more. And like, I think it's like not all quite there. partially it's like a, it's just like more token expensive? And like, I think likeProjects, Local Hands, and Cloud-to-Local HandoffsSwyx [00:48:59]: Why would projects be more token expensive? I understand mods would be slightly more token expensive. No, not something I'm worried about.Thariq Shihipar [00:49:06]: Yeah.Swyx [00:49:06]: But whatThariq Shihipar [00:49:07]: You're asking Claude to do. It's like creating loops. Like you're asking Claude to do more work for you. And so like it's managing the sub-agents and reviewing it, versus where you would be doing that work normally. And so that's like gonna be a little bit more intensive, like. Outputting to an artifact is gonna be a little bit more token-intensive than, like, outputting normally. I don't think it's too much more, but like, it's like combining all of these together well, like I think we're, we're still working on like local hands and things like that, I think is like, yeah, where things are headed, yeah.Swyx [00:49:37]: Yeah. Claude and local is, handoff is very interesting. I was thinking about this as reverse cloud remote.Thariq Shihipar [00:49:44]: Yeah.Swyx [00:49:45]: Because it's like remote, it's you're handing off to cloud, but here the cloud is handing off to local, right?Thariq Shihipar [00:49:49]: Yeah, exactly. Yeah, remote control is also another way of doing it. And I do want to say this is like how I think about it and like what the things that I'm most excited about this, but like there are, just like lots of different ways to work with Claude. Like some people use remote control a lot, some people use Claude Code on the web a lot. Obviously, like at Anthropic, we use Claude Tag a lot, and like what's great about Claude Tag is we set up all this stuff for our own execution. And I do think if you're an enterprise, that's still the best way to go. but if you're like an individual, Projects is this way of like, getting some of that like niceness of Tag, which has like that like supervising agent and yeah, adding artifacts and stuff, but like without having that whole like admin setup. And so there will be many ways to use Claude, I think. I think it's probably not just one like single.Claude Tag as an Organizational HarnessSwyx [00:50:36]: You had the multiplayer thing here. Let's, let's just check in on Claude Tag. it's been about two-plus months. Lots of, public, adoption and trying it out.Thariq Shihipar [00:50:45]: Yeah.Swyx [00:50:45]: What's new? What's, what have you found since the launch?Thariq Shihipar [00:50:49]: Like, Claude Tag is how we useSwyx [00:50:51]: It's like 80% of your

Alex Mashrabov is the Founder and CEO of Higgsfield, the third fastest scaling company to $1BN in ARR behind OpenAI and Anthropic. Reports suggest their latest funding round could place an $8BN valuation on the company. Prior to Higgsfield, Alex sold his prior company to Snap Inc for $166M. Alex was a competitive programmer as a kid, reaching third best in the world. AGENDA:  00:00 The Programming Prodigy Who Sold to Snap for $166M 09:00 Burning $10M: The Pivot That Saved Higgsfield 12:00 A $1B Revenue Run Rate in 18 Months; How Real Is It? 16:00 Will OpenAI and Google Wipe Out $20 AI Subscriptions? 21:00 Are AI Labs Gaming the Benchmarks? 28:00 Spending $4M a Month on AI; Genius or Insanity? 36:00 Are AI Moats Bullshit? The Great "Wrapper" Debate 43:00 One Full Day With His Son in Three Months: The Cost of Ambition 54:00 Quickfire: Is Snap Broken—and Will HubSpot Survive AI? 01:02:00 $10B in the Next 12 Months? Alex's Audacious Growth Bet  

Invitée: Eva Blanck. En Suisse, les arrêts de travail ont augmenté dʹenviron un tiers en quinze ans, selon lʹOffice fédéral de la statistique. Cette hausse sʹexplique en partie par les cas de troubles de santé mentale, qui ont augmenté dʹenviron 60% en dix ans. Selon une autre étude de Travail Suisse, plus de 42 % des personnes interrogées se disent souvent ou très souvent stressées au travail et 17% affirment avoir déjà subi un burn-out. Est-ce que le monde du travail est devenu plus difficile quʹavant? Est-ce que les employé.es sont plus fragiles? Est-ce que les médecins sont trop complaisants? Tribu accueille Eva Blanck, qui signe ce livre, "Arrêt de travail", aux éditions Les Léonides.

Lorsque le mental s'emballe, un léger déplacement de l'attention peut ouvrir un nouvel espace. Cette méditation guidée vous accompagne vers la zone située derrière la tête afin de retrouver une présence plus large, plus stable et plus calme. Cette séance fait partie du parcours Arrêter de trop penser, une série de cinq méditations consacrées à l'anxiété, aux ruminations mentales, aux tensions corporelles et au retour au présent. Parcours complet Arrêter de trop penser Prenez le temps de vous installer confortablement et choisissez un environnement calme pour vivre cette pratique. Voir la vidéo Votre mental s'emballe ? Méditation 15 min Podcast Votre mental s'emballe ? Méditation 15 min #MeditationGuidee #CalmerLeMental #MomentPresent

Bienvenue dans la traque de Carlos Ghosn, l'un des patrons les plus puissants et controversés de l'industrie automobile. Arrêté au Japon pour des accusations de malversations financières, l'ancien patron de Renault-Nissan se retrouve au cœur d'un véritable feuilleton judiciaire. Assignation à résidence, surveillance, procès… puis une spectaculaire fuite du Japon, soigneusement préparée dans le plus grand secret.  Découvrez cette nouvelle traque, prochainement disponible sur toutes les plateformes d'écoute. Learn more about your ad choices. Visit megaphone.fm/adchoices

Arrêtez tout ! On connaît les meilleures frites du monde !

Arrêtez tout ! On connaît les meilleures frites du monde !

Oblideu el típic legionari romà de les pel·lícules amb el seu escut rectangular i l'espasa curta. A les acaballes de l'Imperi Romà d'Occident, les legions van viure una transformació militar radical per poder sobreviure a un món cada vegada més hostil. L'exèrcit del Baix Imperi era realment una força decadent i abocada al desastre, o estem davant d'unes tropes d'elit perfectament adaptades a les noves amenaces? En aquesta primera part sobre l'exèrcit tardoromà, ens acompanya l'historiador Adrià Hernando per desmuntar el mite de la decadència militar de Roma. Descobrim com es va reestructurar la defensa de l'Imperi, analitzem per què les legions van reduir els seus efectius, l'abandó del clàssic gladius en favor de l'espasa llarga, i com la cavalleria vestida de ferro de cap a peus va començar a dominar els camps de batalla, sent la clara avantsala dels cavallers de l'edat mitjana. Escolta'ns per descobrir la veritable cara de la màquina de guerra romana al Baix Imperi! Si t'agrada la història antiga, no oblidis subscriure't i compartir el pòdcast. Enllaços del programa: https://linktr.ee/portesdetroia Moltes gràcies als nostres mecenes: Carles Siscar, Marc Sancho, Arístides Gutiérrez, Dani Vallés, Josep Raya, Patrick Urbano, Noè Merles, Pol Garcia, Raul Martínez, Esclàput, Alex Garcia Manzanera, Roser O. M., Pere, Víctor Martínez, Josep Sanchis, Ferran Marro, David Piedrafita Farràs, Gontzal Zubizarreta, Alvaro Buitrago Hondarza, Roser Mora, Magí, Salvador, Jordi Martorell, Núria Arràras, sapcat7, Gloria M. Pujol Carmona, Info Quagga, caquiroga, Carles Bonas, Pol Moix, Sergi Jubany Planas, Xavier Aldeguer, Jessica Romero Plasencia, Joan Blasco Fortuny, Jordi Guillaumet, Marc Llurba Pont, Geòrgia Costa Villaró, Jaume Perello, Núria Arràras, Carles Pérez, Marc Rodriguez-Estivill, Jaume Perello, Geòrgia Costa, Carles Pintó, Jamue MB, David Solsona.

Arrêtée le 7 août à l'aéroport de Louisville alors qu'elle partait à New York avec son équipe universitaire du Kentucky, Aminata Seck est depuis détenue par la police américaine de l'immigration. Après plusieurs publications de l'une de ses avocates sur Instagram alertant sur son état de santé, les appels à sa libération se multiplient sous le hashtag #FreeAminata, mais aussi à travers des vidéos réclamant l'implication des autorités sénégalaises. Avec Jessica Taieb, journaliste à Appels sur l'actualité sur RFI.

Google DeepMind Chief Architect Koray Kavukcuoglu talks with Jessica Lessin about recursive self-improvement and AI agent autonomy. Then: TITV Host Akash Pasricha talks with The Information's Stephanie Palazzolo and Leo Schwartz about SAFA, a proposed safety body from Google, OpenAI, and Anthropic; Cory Weinberg about Anthropic co-founders seeking voting control ahead of their IPO; Asia Bureau Chief Jing Yang and Asia Reporter Juro Osawa about DeepSeek's $1 billion ARR; Kristy Loke about why America's AI ambitions face headwinds compared to China. Finally, we get a peek at The Information Pro's newest tool, which identifies emerging AI trends with Eric Bellomo, The Information's Head of Research.Articles discussed in today's show:https://www.theinformation.com/articles/google-openai-anthropic-ai-safety-group-takes-shapehttps://www.theinformation.com/articles/anthropic-seeks-palantir-style-voting-control-seven-co-founders-ahead-ipohttps://www.theinformation.com/articles/deepseeks-annualized-revenue-hits-1-billion-startup-finalizes-7-5-billion-fundraisinghttps://www.theinformation.com/articles/americas-ai-dream-failing-launchhttps://www.theinformation.com/articles/introducing-ai-inflection-index-9-500-articles-say-coming-next Subscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction & DeepMind's Autonomous AI Agents02:18 - Inside AI Agenda Live: Open Source Price Wars & JEPA06:35 - SAFA: Google, OpenAI & Anthropic Form AI Safety Group11:10 - Anthropic Co-Founders Push for IPO Voting Control15:02 - DeepSeek Revenue Soars to $1B ARR at 83% Margin19:15 - Why America's AI Ambitions Face Public Backlash24:05 - Introducing The Information's AI Inflection Index

Think about the last time riding your motorcycle when something surprised you on the road or trail and you had to get on the brakes—hard and fast. What did that feel like? Was it unnerving? Did the motorcycle suddenly feel like something you were fighting to control? It doesn't necessarily have to feel that way. Maximum braking is a skill, but there are things to understand about your motorcycle before you even get to practising it. Clinton Smout from Smart Performance Centre takes us through what riders need to know to become more comfortable, confident and capable when they really need to stop.

In this episode of the SaaSiest Podcast, we sit down with Didi Gurfinkel, Co-founder & CEO of Datarails, to talk about what it takes to make a radical strategic shift while your company is still growing fast. DataRails was already a high-growth SaaS company when Didi and his team became convinced that AI was fundamentally changing their market. Instead of protecting what was already working, they made a bold call: the traditional FP&A software category was dying, and DataRails needed to evolve from a point solution into the foundation for the Office of the CFO. We dig into what happened next,  the strategic bet, the internal resistance, the impact on sales, and why Didi believes SaaS leaders need to start separating their “old ARR” from the “new ARR” that will drive their companies in the AI era. We discuss: Why DataRails declared its own software category “dead” The difference between “old ARR” and “new ARR” Why successful SaaS companies may need to reinvent themselves before growth slows How DataRails moved from an FP&A product to a broader finance platform Why AI is making the application layer increasingly commoditized What becomes the moat when building software gets dramatically easier How to get 400 employees behind a major strategic repositioning Why sales teams can become one of the biggest sources of resistance to change How far ahead of the market a SaaS company should position itself Why small changes may not be enough in the AI transition Didi also shares one of the strongest analogies we've heard for navigating the current AI shift: when the flood is coming, don't keep moving from balcony to balcony. Find the hill. A great conversation for SaaS CEOs, founders and executives asking themselves a difficult question: Is the business that got us here also the business that will take us forward?

Cette méditation du soir accompagne les moments où l'esprit imagine des conversations, des hypothèses ou des scénarios avant de dormir. Un décompte de dix à un aide l'attention à se rassembler autour de la respiration et des sensations corporelles. Cette séance fait partie du parcours Arrêter de trop penser. Elle prépare une transition douce entre l'activité mentale de la journée et un état plus disponible au repos. Parcours complet Arrêter de trop penser Prenez le temps de vous installer confortablement et choisissez un environnement calme pour vivre cette pratique. Voir la vidéo Votre cerveau invente des scénarios avant de dormir ? | Méditation du soir Podcast Votre cerveau invente des scénarios avant de dormir ? | Méditation du soir #MeditationDuSoir #RuminationsNocturnes #MieuxDormir

Dans cet épisode solo, j'analyse le parcours de Quentin Nier, CEO de GROUPE HABILIS.Son secret ? Arrêter de confondre un chiffre d'affaires qui monte avec un modèle qui tient, et reconstruire une entreprise simple, agile et rentable avant que le marché ne vous y oblige.Au programme :* Se méfier de la croissance qui masque la perte et regarder la vraie rentabilité* S'entourer vite là où l'on n'est pas bon pour ne pas devenir le goulot de sa boîte* Avoir le courage de tout déconstruire pour reconstruire un modèle simple* Responsabiliser ses équipes en leur confiant un vrai périmètre et les moyens* Faire co-construire la vision par ses équipes plutôt que la porter seulUn épisode 100% actionnable pour tout entrepreneur ou toute entrepreneure.Bonne écoute !Votre entreprise est-elle structurée pour accélérer ? Faites le diagnostic Comment t'as fait ? pour prendre du recul sur vos décisions stratégiques et vérifier si nous sommes la bonne équipe pour vous accompagner : https://diagnostic-commenttasfait.netlify.app/

In this episode, Jared Bauman talks with Besmir Bregasi, founder of ZeroRank, about what is driving LLM citations in 2026 and why Reddit, X, YouTube, and fresh off-site mentions matter so much. Besmir shares ZeroRank data on user-generated content, local AI visibility, and the on-site factors that still support citation potential. He also explains how ZeroRank's first version was built in three months, grew past 1,000 customers through AppSumo, and reached mid-six figures in ARR. They also discuss AppSumo economics, recurring revenue, referrals, affiliates, and ZeroRank's next growth phase.     Sponsor: Quiet Light Get a free, confidential valuation at https://quietlight.com/!     Be sure to get more content like this in the Niche Pursuits Newsletter Right Here: https://www.nichepursuits.com/newsletter ----------------------------------------------------------------------------------------------------------------------- Want a Faster and Easier Way to Build Internal Links? Get $15 off Link Whisper with Discount Code "Podcast" on the Checkout Screen: https://www.nichepursuits.com/linkwhisper ----------------------------------------------------------------------------------------------------------------------- Get SEO Consulting from the Niche Pursuits Podcast Host, Jared Bauman: https://www.nichepursuits.com/201creative -----------------------------------------------------------------------------------------------------------------------     Links & Resources Check out ZeroRank: https://zerorank.ai/ Learn more about LanderLab: https://landerlab.io/     - You can learn more about me and get additional website tips at: https://www.nichepursuits.com - You can learn about optimizing your site with internal links using a WordPress Plugin I created right here: https://www.linkwhisper.com   Thanks for watching and please consider subscribing to the main Niche Pursuits YouTube channel by clicking here: https://www.nichepursuits.com/youtube 

durée : 00:59:14 - Le 13/14 - par : Jérôme Cadet - À 13 h 30, nous parlons des arrêts maladie ; leur nombre ne cesse d'augmenter et le gouvernement veut les limiter. Que cachent ces arrêts ? Nous en parlons avec la sociologue Eva Blanck ; elle publie « Arrêt de travail : déconstruire les mythes et résister à la culpabilité ». - équipe : Elise Amchin, Cecilia Arbona, Aurore Mancip Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

À 10h, ce mercredi 23 septembre 2026, les GG : Fatima Aït Bounoua, professeure de français, Mourad Boudjellal, éditeur de BD, et Charles Consigny, avocat, débattent de : Arrêter de rembourser les arrêts maladie de courte durée ?

Au menu de la deuxième heure des GG du mercredi 23 septembre 2026 : "Arrêter de rembourser les arrêts maladie de courte durée ?" et "Roman écrit à l'IA : peut-on faire la différence ?", avec Fatima Aït Bounoua, professeure de français, Mourad Boudjellal, éditeur de BD, et Charles Consigny, avocat.

J'ai le plaisir de recevoir Elena Nagapetyan, humoriste et mère, qui ose dire tout haut ce que beaucoup pensent tout bas. Dans son spectacle Ça valait le coup, disponible sur Prime Video et en tournée jusqu'en novembre, elle parle sans détour de confiance en soi, de maternité, d'amour, de violences et de tout ce qu'on apprend parfois à garder pour soi.Pourquoi les femmes ont-elles autant peur d'être jugées ? Comment apprendre à ressentir ses émotions autrement que dans sa tête ? Pourquoi associe-t-on encore autant l'amour à la passion ? Et si, finalement, on cherchait moins à tout contrôler qu'à se sentir apaisée ?Dans cet épisode, Elena raconte ce que son parcours lui a appris sur la confiance en soi, les mécanismes de protection et la difficulté à accueillir pleinement certaines émotions. On parle de ce qui nous façonne, de ce qu'on garde en soi et de ce qu'il faut parfois du temps pour comprendre, accepter ou simplement laisser exister.Je vous souhaite une très bonne écoute !—Pour découvrir les coulisses du podcast : https://www.instagram.com/inpowerpodcast/Pour en savoir plus sur Elena Nagapetyan : https://www.instagram.com/elenanagapetyan_/?hl=frEt son spectacle : https://linktr.ee/elenanbPour suivre mes aventures au quotidien : https://www.instagram.com/louiseaubery/Si cet épisode vous a plu, vous aimerez sûrement celui-ci : https://shows.acast.com/inpower/episodes/camille-lellouche-je-ne-veux-plus-souffrir—Chapitrage :00:00:00 - Elena Nagapetyan00:00:32 - Miroir, Miroir00:02:13 - Oser dire ce qu'on pense00:05:00 - Arrêter de se sentir « pas assez »00:07:10 - S'affirmer malgré les autres00:09:11 - Apprendre à ressentir les émotions00:11:23 - Choisir sa vie sans chercher l'approbation00:14:10 - S'autoriser enfin à célébrer00:18:15 - Apprendre à accueillir ses émotions00:24:22 - Pourquoi la passion ne suffit plus00:30:03 - Les dernières fois d'Elena Nagapetyan00:39:43 - Dénoncer les violences avec humour00:48:11 - Échapper au piège de la mère parfaite00:51:36 - Apprendre à être mère sans s'effacer00:54:41 - Ça valait le coup ? ou pas ? Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Max Junestrand, co-founder and CEO of Legora, explains how Legora became the fastest company in history to grow from $1M to over $100M in annual recurring revenue (ARR), in 21 months. He joins Truth Works hosts Jessica Neal and Peter Clark live from Legora's office.━━━━━━━━━━━━━━━━━━━━WHO IS MAX JUNESTRAND?Max Junestrand is the 27-year-old Swedish co-founder and CEO of Legora, an AI platform for lawyers, law firms and in-house legal teams. He studied computer science and business, worked at two Y Combinator startups, and is not a lawyer.WHAT IS LEGORA?Legora is a legal AI company founded in Stockholm, Sweden and backed by Y Combinator. It helps lawyers review contracts, research case law and draft legal work. Legora serves some of the largest legal institutions in the world across Europe, the UK and the US, employs 900 people, and acquired five companies in 2026.━━━━━━━━━━━━━━━━━━━━HOW LEGORA STARTED- Founded in 2020 by a psychologist, an engineer, a physicist and a lawyer- Max joined in 2023, after the release of ChatGPT- Started with €50,000 in angel funding before Y Combinator- Rejected by Y Combinator once, accepted on the second application- Built inside Mannheimer Swartling, the largest law firm in the Nordics, for nine monthsBefore Legora, Max applied to 400 jobs and got two interviews. Both rejected him.━━━━━━━━━━━━━━━━━━━━HOW LEGORA HIRES AND SCALES- Headcount grew from 250 to 900 people in one year- 0.3% of applicants receive an offer- Max personally interviews every director-level hire- Recruiting is treated as a privilege, not an obligation- Performance reviews use a 1–5 scale with direct feedback- The company is office-first with almost no remote work━━━━━━━━━━━━━━━━━━━━KEY FACTS FROM THIS EPISODE- $1M to $100M+ ARR in 21 months- A contract review estimated at $44M was completed in 4 days- A third-party study found Legora helps lawyers catch missed errors in 71% of cases- Legora builds for where AI models will be in 3–6 months━━━━━━━━━━━━━━━━━━━━QUESTIONS ANSWERED IN THIS EPISODE→ How did Legora grow so fast?→ Why did Legora's team move into a law firm?→ How do you hire at scale without lowering the bar?→ How do you give hard feedback in a culture that avoids it?→ How do you build one culture across Stockholm, London and New York?→ Why is it becoming unethical not to use AI in legal work?→ How will AI change the work of lawyers in the next two years?→ Can legal AI improve access to justice?━━━━━━━━━━━━━━━━━━━━"You can just do things. You can be a little bit unreasonable in your ambitions." — Max Junestrand, CEO of Legora━━━━━━━━━━━━━━━━━━━━ABOUT TRUTH WORKSTruth Works is a podcast about building companies and the people behind them. Hosted by Jessica Neal, former Chief Talent Officer at Netflix, and co-host Peter Clark.Legora: legora.comLegora careers: legora.com/careersSponsored by Manifest Law, the AI-native immigration law firm.#Legora #MaxJunestrand #LegalAI #AIforLawyers #YCombinator #StartupGrowth #Hiring #TruthWorks #JessicaNeal

Most of the AI products getting hype right now are built for people like us, the tech industry. But your customers don't care how the AI works — they just want their problem solved in a way that's easy for them. Brian McMullin, SVP and Head of Product at Network Solutions, has spent 15 years building for small businesses at companies including HubSpot, ezCater, Wayfair, and SamCart. In that time, he's yet to meet a business owner who wakes up thinking, "I can't wait to use AI today." For many of them, a prompt box might as well be a terminal window. So his team doesn't ship the box. They ship the finished work artifact, and all the user has to do is claim it. In this episode, Brian shares: Why doing the work for small businesses first, instead of handing them an empty prompt box, is what gets them to try AI His warning about baking inference into the core of your product before token pricing settles — and the two models he's testing to find out what small businesses will actually tolerate And what SamCart taught him about churn: customers left because basic things were broken, not because features were missing. Links LinkedIn: https://www.linkedin.com/in/brianemcmullin/ Network Solutions: https://www.networksolutions.com/ Chapters 00:00 Introduction 00:48 Brian's product journey from developer to SMB product leader 02:42 How small businesses went from distrusting AI to have AI FOMO 06:10 SMBs don't wake up excited to use AI, they want to close the deal 08:42 Stop showing the agent, ship the finished work 11:48 Inference costs break the old SaaS margin math 15:00 Testing free credits and tiered usage with small businesses 16:47 What usage-based pricing does to ARR and predictability 22:28 Churn is a pile of micro-annoyances, not one event 25:06 What SamCart's churn data revealed about broken basics 28:55 Conclusion Follow LaunchPod on YouTube We have a new YouTube page! Watch full episodes of our interviews with PM leaders and subscribe! What does LogRocket do? LogRocket's Galileo AI watches user sessions for you and surfaces the technical and usability issues holding back your web and mobile apps. Understand where your users are struggling by trying it for free at LogRocket.com.Special Guest: Brian McMullin.

Les soucis et les ruminations peuvent s'exprimer à travers des tensions corporelles. Cette méditation guidée utilise les sensations de chaleur, de lourdeur et de soutien pour favoriser un relâchement profond et apaiser le mental en fin de journée Cette séance constitue la troisième étape du parcours Arrêter de trop penser, une série de cinq méditations pour retrouver une relation plus paisible avec les pensées et préparer un retour au calme. Parcours complet Arrêter de trop penser Prenez le temps de vous installer confortablement et choisissez un environnement calme pour vivre cette pratique. Voir la vidéo Vous portez vos soucis dans votre corps depuis trop longtemps | Méditation Podcast Arrêter de trop penser – Méditation du soir #MeditationGuidee #DetenteDuCorps #Ruminationse

Juhász László Amerikáért sem volt hajlandó elárulni Magyarországot. A citerás mérnök Nagydorogról indult, Németországon keresztül jutott el az Egyesült Államokba, ahol később az elektronika, az orvostechnológia és a modern technológia világában épített karriert.   László azt mondja, azért lett mérnök, mert citerázott. A zene megtanította hallani azt is, amit mások még nem hallanak, a kíváncsisága pedig már gyerekként a műhelyek, a mágnesek, a rádiók és a televíziók világa felé vitte. Mesél Vas Feri bácsiról, aki meglátta benne a megszállottságot, és mentorává vált.   A beszélgetésben szóba kerül a nyolcvanas évek Magyarországa, Csernobil, a személyes veszteségek, a kilátástalanság érzése és az a döntés, hogy feleségével elindulnak nyugat felé. Egy tízdolláros szótár, az Orient Expressz, németországi panziók, televíziójavítás és olyan emberek segítsége is része ennek a történetnek, akik akkor hittek bennük, amikor még semmi sem volt biztos.   László őszintén beszél arról is, miért nem volt hajlandó a családja ellen vallani azért, hogy könnyebben juthasson Amerikába. Ez a döntés később sokak szemében többet ért bármilyen kitöltött papírnál: amikor végül megérkezett az Egyesült Államokba, egy mondat fogadta: „Welcome to the US, my friend."   Az adásban nemcsak az amerikai újrakezdésről hallunk. László mérnökként dolgozott elektronikai, orvostechnológiai, energiaipari, akkumulátor- és dróntechnológiai projekteken is. Beszél a fiatal mérnökök képzéséről, a gyakorlati tudásról, a problémamegoldásról, a haditengerészetnél szerzett élményeiről, és arról is, miért kapott nemrég munkalehetőséget a Teslától.   Szerinte az igazi szakembert nem kizárólag az iskola formálja. Kell hozzá kíváncsiság, kitartás, józan gondolkodás, alázat és az a fajta belső kényszer, amely miatt valaki addig nem nyugszik, amíg meg nem találja a választ.   László története közben arról is szól, milyen magyarnak lenni Amerikában. Arról, hogyan lehet hálásnak maradni a kapott segítségért, miért fontos visszaadni abból, amit az ember kapott, és miért nem érdemes folyton azt nézni, ami hiányzik.   LINKEK: www.Nagydorog.hu Kutasi József Antal - Magyar Katolikus Misszió https://bit.ly/3VAALcW   Ha tetszett a beszélgetés, iratkozz fel a MÓKA Podcast YouTube-csatornájára, nyomj egy like-ot, és oszd meg ezt az epizódot valakivel, akit inspirálhat egy magyar mérnök rendkívüli amerikai története.   FEJEZETEK:   00:00 – Hidegnyitó: Csernobil, Amerika és a Tesla ajánlata 01:55 – Juhász László: a citerás mérnök 06:07 – Vas Feri bácsi és a gyerekkori megszállottság 08:01 – Televíziójavítás Németországban 12:20 – Intuíció, hit és egy megoldhatatlannak tűnő műszaki probléma 20:07 – Mitől lesz valaki igazán jó mérnök? 26:02 – Csernobil, veszteség és a távozás gondolata 30:21 – Döntés: el kell hagyni Magyarországot 32:20 – Az Orient Expressz és az út Münchenbe 33:34 – Megérkezés Németországba 39:01 – Menekülttáborok, segítség és az IRC 43:02 – Magyarnak lenni két világ között 45:19 – Kármán Tódor és a magyar tudósok öröksége 50:31 – Amerikai papírok és a nagy lehetőség 54:01 – A döntés, hogy nem árulja el a családját 58:00 – Menekültek, kiutasítás és Amerika kapuja 01:05:03 – Elmenne-e ma Magyarországról? 01:09:03 – Drónok, akkumulátorok és a Tesla megkeresése 01:17:36 – Haditengerészet, Enterprise és magyar kapcsolatok 01:22:44 – Amerikai állampolgárság, hála és visszaadás 01:26:50 – A legfontosabb üzenet: becsüld meg azt, amid van 01:28:16 – Személyes veszteségek és zárógondolatok   Írd meg kommentben: számodra mi volt Juhász László történetének legerősebb gondolata?  

L'any 1405, dècades abans que Cristòfor Colom creués l'Atlàntic o que Vasco de Gama arribés a l'Índia, l'Imperi Ming va llançar als oceans la flota d'exploració més colossal que el món havia vist mai. Aquesta setmana, A les Portes de Troia, viatgem a la Xina del segle XV per descobrir la història silenciada de les grans expedicions del tresor. Resseguim la increïble vida de Zheng He, un eunuc musulmà capturat de nen que va arribar a comandar impressionants armades de més de tres-cents vaixells gegants i vint-i-set mil homes, establint rutes diplomàtiques des del sud-est asiàtic i el Golf Pèrsic fins a les costes orientals d'Àfrica. Al llarg d'aquest episodi analitzem les ambicions de l'emperador Yonglè per legitimar el seu poder i projectar la superioritat tecnològica xinesa arreu del món mitjançant un complex sistema tributari, intercanviant porcellana d'altíssima qualitat per exòtics lleons, zebres i girafes. Aprofundirem en el dur conflicte polític intern entre els eunucs exploradors i els funcionaris confucians, una guerra de poder que va acabar provocant la destrucció sistemàtica dels arxius imperials. Finalment, ens plantejarem el gran misteri geopolític de l'època: per què la Xina, tenint la millor tecnologia naval del món i el domini absolut de les rutes marítimes, va decidir girar cua de cop, destruir els seus vaixells i cedir el control dels oceans a l'imperialisme europeu? Ja disponible un nou viatge històric! Si t'agrada el programa, recorda compartir-lo i fer-te mecenes per ajudar-nos a continuar divulgant la història. Enllaços del programa: https://linktr.ee/portesdetroia Moltes gràcies als nostres mecenes: Carles Siscar, Marc Sancho, Arístides Gutiérrez, Dani Vallés, Josep Raya, Patrick Urbano, Noè Merles, Pol Garcia, Raul Martínez, Esclàput, Alex Garcia Manzanera, Roser O. M., Pere, Víctor Martínez, Josep Sanchis, Ferran Marro, David Piedrafita Farràs, Gontzal Zubizarreta, Alvaro Buitrago Hondarza, Roser Mora, Magí, Salvador, Jordi Martorell, Núria Arràras, sapcat7, Gloria M. Pujol Carmona, Info Quagga, caquiroga, Carles Bonas, Pol Moix, Sergi Jubany Planas, Xavier Aldeguer, Jessica Romero Plasencia, Joan Blasco Fortuny, Jordi Guillaumet, Marc Llurba Pont, Geòrgia Costa Villaró, Jaume Perello, Núria Arràras, Carles Pérez, Marc Rodriguez-Estivill.,

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) The WSJ says the Hugging Face might not be all that it was cracked up to be 2) The bots were told to hack? 3) Was this all a false flag for an effective altrust takeover? 4) Was this a smoke screen to conceal bad financial numbers from the AI labs? 5) Alex: Actually, maybe we should take these issues seriously? 6) Ranjan: They why aren't the labs being more transparent 7) Astra-6's crazy instructions to alter its personality in training 8) Anthropic hits $100 million in ARR 9) The IPOs will go on 10) The frontier AI business shows signs of slowing --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

Matt van Hilst carefully plans a solo motorcycle ride and repeatedly chooses caution when conditions change. Yet the day still ends in DEEP TROUBLE, raising a difficult question: can every crash be traced back to a mistake—or a series of them?

CJ sits down with multi-time CFO Rick Smith, founder of Bonfire Advisory and author of Six Months to the Sale, to break down what actually happens when you sell a company. They cover why buyers value some businesses on ARR and others on EBITDA (and why being slightly profitable can hurt you), how to negotiate banker fees, what buyers find when they dig into your balance sheet, and why every cap table Rick inherits is wrong.—SPONSORS:RightRev is a revenue recognition platform built for the AI economy, helping finance support usage-based pricing, credits, hybrid contracts, seats plus consumption, and whatever commercial model comes next. It gives product teams the freedom to keep innovating without outdated revenue systems slowing them down. Learn how RightRev can help at https://rightrev.com/cjRillet 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 posts 98% of transactions directly to its ERP, with the remaining 2% routed to a human for review. You pay for outcomes, not seats. See it at https://www.maximor.ai/Brex is an intelligent finance platform with AI-powered workflows that enforce expense policies at the point of sale, match receipts automatically, and reduce month-end close from weeks to hours. Thousands of companies, including Anthropic, Coinbase, and DoorDash, already run on Brex. Stop asking A-level finance talent to do B-level admin work. 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/rtnEY works with high-growth tech companies to navigate the messy realities of scaling—from regulatory requirements to IPO readiness. By helping teams get it right early and often, EY lets founders stay focused on building while reducing risk as they grow. Learn more at https://www.ey.com/techstartups—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNGuest: linkedin.com/in/rick-smith-906939Company: https://www.linkedin.com/company/bonfire-advisoryCJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—TIMESTAMPS:1:21 Meet Rick Smith and "Six Months to the Sale"2:44 Why Teach M&A Through Fiction4:26 CEO/CFO Tension7:08 Botching the Announcement8:15 How Staff Really React9:18 When Personal Life Collides With a Deal13:50 ARR vs. EBITDA17:58 What to Optimize Before a Sale18:50 Churn and Contract Renewal20:43 Strategics vs. PE27:46 Investment Banker Fee Structures29:09 What's Negotiable29:56 The Realtor Problem34:53 Big 4 vs. Regional Firms for Audit and QoE35:47 Negotiating Accounting Fees37:47 Deferred Revenue41:23 Warrants, Options, and Carta Cleanup44:02 QSBS: What CFOs Need to Know45:28 Quality of Earnings: Who Pays and Why47:44 What a QoE Actually Digs Into51:22 Why Deal Momentum Is So Hard to Stop53:47 The Waterfall58:19 Who Keeps Their Job61:31 Why Selling CFOs Feel Intimidated62:56 Prospect Theory65:28 Where to Find the Book#RunTheNumbersPodcast #MandA #CFOLife #SellingACompany #QualityOfEarnings

Voir la vidéo Arrêter de trop penser – Méditation Cette méditation guidée vous aide à prendre de la distance avec les pensées répétitives. En observant leur mouvement puis en revenant au corps et à la respiration, vous laissez le mental retrouver progressivement plus d'espace et de calme. Cette séance est la deuxième étape du parcours Arrêter de trop penser. La série réunit cinq pratiques pour apaiser les ruminations mentales, relâcher leur empreinte corporelle et revenir au présent. Parcours complet Arrêter de trop penser Prenez le temps de vous installer confortablement et choisissez un environnement calme pour vivre cette pratique. Podcast Arrêter de trop penser – Méditation du soir #RuminationsMentales #pleineconscience

L'info du matin- Les dix titres de rock les plus streamés dans le monde en 2026.Le winner du jour- Elle paye 1 612 francs suisses pour un croissant.- Arrêté à l'aéroport avec 8,8 kilos de charcuterie, il écope de 430 euros d'amende.Tu te souviens ?- Tu te souviens des premiers posters que tu as accrochés dans ta chambre ?Les savoirs inutiles- Pourquoi les surfeurs font-ils toujours ce signe avec la main, le pouce et le petit doigt tendus ? Ce geste s'appelle le "shaka" et derrière ce symbole emblématique d'Hawaï se cache une histoire assez étonnante.La chanson du jour- Kim Wilde "Kids in America"Tendances- Les nouvelles façons de marcher.Le jeu surprise (petit quiz)- Nicolas de Saran vers Orléans gagne un séjour pour 4 personnes au Parc Astérix.La Banque RTL2- Jessica de Melun repart avec un bon d'achat de 100€ valable sur le site Le Vent à la Française.- Oxana de Carpentras vers Avignon gagne un séjour à l'hôtel Thalassothérapie & Spa Thalazur de Royan : un séjour Thalazur de 6 jours et 5 nuits avec petits-déjeuners comprenant 24 soins pour 2 personnes.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

En este episodio del podcast de Itnig hablamos con Antonio Berga y Carlos Serrano, co-CEOs y cofundadores de Embat, la plataforma de tesorería con IA que ya trabaja con cerca de 600 empresas y que acaba de levantar 30 millones de euros liderados por Cathay Innovation. Durante la conversación entramos en un problema que casi nadie ve: empresas que pierden entre 5 y 7 millones de euros al año por no optimizar su caja, filiales que piden crédito mientras otra filial del mismo grupo tiene medio millón parado, o equipos financieros que dicen "sí a todo" en divisas y descubren que lo que habían vendido vale un 20% menos. Antonio y Carlos explican cómo funciona Embat por dentro: bancos conectados en más de 75 países, forecast de tesorería, conciliación bancaria automática del 95% y una IA determinista con modelos propios, porque en finanzas lo que el cliente valora es la trazabilidad. Pero la historia de Embat también es personal. Antonio y Carlos cuentan cómo el Covid les quitó el miedo a dejar JP Morgan, cómo montaron una tecnológica sin CTO, cómo quemaron los 200.000€ que pusieron de su bolsillo y cómo han levantado más de 50 millones sin hacer nunca un proceso competitivo. Una conversación sobre fintech, tesorería, inteligencia artificial, fundraising, venture capital, SaaS B2B y emprendimiento. Suscríbete a Itnig para más conversaciones sobre negocios reales, startups y marcas

Building AI startups can make past success a liability when it convinces you that the way you built before is the way you should build next.Sam Kroonenburg knows what it feels like to build at scale. He co-founded A Cloud Guru, helped grow it into a business serving millions of learners, and eventually sold the company to Pluralsight. Now, as CEO and co-founder of Cuttable, he's back at the beginning: finding customers, testing assumptions, shipping imperfect products, and learning how different company-building looks in the AI era.In our conversation, we explore what Sam had to unlearn when he moved from running a 600-person company back into an early-stage startup. We get into why Cuttable walked away from nearly $1 million in annual recurring revenue, how enterprise customers can pull a young company away from the product it actually needs to build, and why AI is shifting product and engineering teams from owning parts of a system to owning measurable outcomes.Key TakeawaysPast success can distort your judgment: Starting Cuttable reminded Sam that reputation means little if the product does not solve a problem customers will pay for.Experience does not transfer automatically: Sam could trust his instincts when building for engineers, but entering advertising required him to test assumptions and learn from customers.Revenue can hide the wrong product: Cuttable reached nearly $1 million in ARR while engineers were still manually doing work the product was supposed to automate.Taking the long view can require a reset: Sam and his co-founders released every customer, returned to zero revenue, and rebuilt around end-to-end automation.AI shifts the focus from tasks to outcomes: Instead of teaching AI to copy a human process, teams should define the desired result and let AI determine how to achieve it.Additional InsightsSpeed can be an advantage over scale: A Cloud Guru prepared courses before AWS certifications launched, then updated them using real exam feedback.Playfulness can strengthen a product: Short, entertaining lessons made cloud training easier to engage with and helped A Cloud Guru stand out.Paying customers provide stronger signals: Payment shows whether a problem matters enough to solve and makes the customer's feedback more meaningful.AI is changing team ownership: Cuttable is moving from teams that own system components to teams accountable for measurable customer outcomes.Founder optimism needs a counterweight: Glitch Capital uses analysts and experienced operators to challenge assumptions and add rigor to investment decisions.Episode HighlightsEpisode Highlights00:00 – Episode RecapSam reflects on starting again after a major exit and learning that customers care more about solving their problem than a founder's reputation.02:13 – Guest Introduction: Sam KroonenburgMeet Sam Kroonenburg, CEO and co-founder of Cuttable, co-founder of A Cloud Guru, and founder investor at Glitch Capital.03:29 – The Moment Technology ClickedSam traces his entrepreneurial journey back to receiving his first computer and learning to code through an online pen pal.09:11 – Winning Through Speed and PlaySam explains how A Cloud Guru used informed bets, rapid updates, and playful learning experiences to move faster than larger organizations.12:26 – Starting Again and Unlearning Founder InstinctMoving from a 600-person company to an early-stage startup forced Sam to test his assumptions and relearn how to earn customer trust.17:51 – Running a Startup Like a Large CompanySam initially brought too much structure, reporting, and sales pressure into Cuttable before refocusing on product-market fit.20:56 – Why Cuttable Went Back to ZeroAfter reaching nearly $1 million in ARR, Cuttable released every customer and rebuilt around end-to-end automation.27:48 – Why Paying Customers Change the SignalSam explains why payment reveals whether a problem matters enough to solve and makes customer feedback more meaningful.29:43 – Stop Teaching AI to Work Like a HumanCuttable learned to give AI the available data and desired outcome instead of forcing it to follow a prescribed human process.34:45 – Organizing Teams Around OutcomesSam explores why engineers focused on customer impact often embrace AI and how Cuttable is organizing teams around measurable outcomes.38:41 – Why Founder Optimism Needs a FilterSam explains how Glitch Capital balances founder optimism with analysts and experienced operators who challenge assumptions.42:03 – Smaller Teams and Bigger ImpactSam shares his optimism that AI will help smaller teams create impact at a scale that once required much larger organizations.FAQsQ1. What did Sam Kroonenburg have to unlearn after building A Cloud Guru?Sam had to unlearn the confidence and operating habits that came with previous success. At Cuttable, he found that reputation could not replace customer value, evidence, or the search for product-market fit.Q2. Why did Cuttable give up nearly $1 million in annual recurring revenue?Enterprise demands were pulling Cuttable toward custom work and manual intervention. When engineers began generating and fixing campaigns themselves, the team released those customers and rebuilt around end-to-end automation.Q3. How does Sam Kroonenburg think AI changes product development?Sam believes teams should spend less time telling AI how to perform a task and more time defining the desired outcome. AI can then use the available data to determine the best method.Q4. Why does Sam prefer feedback from paying customers?Payment shows that a problem matters enough to solve. Free users can offer feedback without genuinely valuing the product, while paying customers provide a stronger signal.Q5. How is AI changing the way Cuttable organizes engineering teams?Cuttable is organizing teams around measurable customer outcomes instead of software components. Teams can use AI and evaluation systems to improve those outcomes continuously.Useful ResourcesCuttable — Sam Kroonenburg's AI-powered creative production system for advertising.A Cloud Guru — The cloud computing education company co-founded by Sam and later acquired by Pluralsight.Glitch Capital — The Australia and New Zealand founders fund Sam started with fellow founders and operators.AWS re:Invent — Discussed in Sam's story about how A Cloud Guru prepared training for new AWS certifications at launch speed.Square Peg — Cuttable's investor, whose response to the company's decision to reset revenue reinforced Sam's understanding of seed-stage investing.Artificial Organizations — https://geni.us/artificialorgsRead Artificial Organizations? Leave a review on Amazon - https://www.amazon.com/review/create-review/ref=cm_cr_othr_d_wr_but_top?ie=UTF8&channel=glance-detail&asin=1067626328Follow Barry O'Reilly:LinkedIn: https://www.linkedin.com/in/barryoreillyWebsite: https://barryoreilly.comFacebook: https://www.facebook.com/barryoreillyauthor/X:

B2B doesn't get a lot of mascot love. Sett went all in on one anyway — and grew ARR by 20X without spending a dollar on ads.Before their rebrand, Sett was still finding its voice: a placeholder logo, one landing page, and little to differentiate them in a market where every brand looks the same. A meerkat changed that.In this episode of The Debrief, Focus Lab CEO Bill Kenney sits down with Jonathan Fishman, Head of Marketing at Sett, and Daniela Szwarc, Brand & Content Lead at Sett, to unpack how a bold rebrand became their biggest growth lever.Tune in to hear:✅ Why Jonathan ran an internal brand sprint to get alignment before ever contacting an agency✅ How a Duolingo-inspired mascot became Sett's most effective (and most maintainable) differentiator✅ Why founders should stop polling opinions ✅ How Sett measured brand ROI in real numbers — not vibesIf you're a B2B marketing leader trying to prove brand's ROI — or wondering whether a little personality could be your best differentiator — this one's for you.Episode Resources:

Voir la vidéo La méditation que toute personne anxieuse devrait faire Cette méditation guidée vous accompagne lorsque l'anxiété mobilise votre attention et que le mental produit de nombreuses pensées. Vous apprendrez à observer l'agitation intérieure avec douceur, à revenir aux sensations du corps et à laisser le calme retrouver sa place. Cette séance ouvre le parcours Arrêter de trop penser, une série de cinq méditations guidées consacrées aux ruminations mentales, à l'anxiété du soir et au retour au présent. Parcours complet Arrêter de trop penser : youtube.com/playlist?list=PLcBxDqwtc_n8 Prenez le temps de vous installer confortablement et choisissez un environnement calme pour vivre cette pratique. Podcast La méditation que toute personne anxieuse devrait faire #MeditationGuidee #Anxiete #CalmerLeMental

Dans de nombreux pays du monde, les étudiants commencent à reprendre le chemin de l'université. Une rentrée qui s'effectue sous le signe des difficultés économiques. En cause principalement les frais d'inscription, s'élevant à plus de 100 000 euros par an dans de grandes universités américaines. En France, les étudiants hors Union européenne sont confrontés à une flambée de ces coûts. Pour ne citer que ces pays. Les étudiants sont-ils devenus la variable d'ajustement des dépenses publiques ? Pourquoi ? Quelles conséquences sur les sociétés et les économies de demain ? Pour en débattre : - Marie Mesmeur, députée LFI Commission des Affaires culturelles et de l'éducation  - Hugo Harari Kermadec, professeur à l'université d'Orléans, sociologue de l'Enseignement supérieur, co-auteur du livre Arrêtons les frais, éditions Raisons d'agir - Ilan Amiard, vice-président étudiant du Crous de Bordeaux-Aquitaine, élu national de La Fédération des associations générales étudiantes (FAGE).

A viral AI extinction claim, a federal advisory naming six Chinese AI labs for industrial-scale distillation, and a $60 billion Qualcomm-AWS silicon pact define a week when enterprise AI risk and opportunity collided head-on. Patrick Moorhead and Daniel Newman weigh in on what's signal and what's noise across AI safety, chip supply deals, and a market rally still betting big on compute. The handpicked topics for this week are: Anthropic Researcher's Doomsday Claim Sparks Congressional Response: Anthropic researcher Jacob Coxon left the company after six weeks and posted a claim that AI carries a greater than 10% chance of ending humanity by 2030, a post that pulled more than 150 million views and landed him on every major network. Patrick Moorhead questioned whether the moment was organic, pointing to Coxon's ties to activist groups. Daniel Newman called the underlying technical claims thin, noting Coxon could not explain a concrete mechanism for how AI would end civilization. Jensen Huang and Dario Amodei both pushed back publicly, and Amodei argued safety claims only carry weight when the underlying work happens in the open. (The Decode) Qualcomm's AWS Deal Validates Its Data Center Silicon Bet: Qualcomm signed a multi-generation collaboration with AWS worth up to $60 billion over a decade, with an initial issuance already covering roughly $9 billion in committed orders. AWS also picked up warrants for 25 million Qualcomm shares tied to the spending commitment. Daniel Newman framed the deal as proof that TSMC capacity plus a credible product lineup is enough to win hyperscaler business, even against entrenched incumbents like Broadcom and Marvell. Patrick Moorhead called AWS the hardest hyperscaler to crack given its in-house CPU and accelerator competency, making the partnership a bigger validation signal than the market's muted stock reaction suggested. (The Decode) Apple's Ternus Era Opens With a Pricier iPhone and a First Real AI Monetization Signal: Apple's first major product event under new CEO John Ternus introduced a $1,999 foldable iPhone Duo alongside a $100 price increase on the iPhone 18 Pro and Pro Max, tied to a 4x jump in memory costs. Patrick Moorhead noted the company already guided gross margin down to 48% and softened the price hike with lease and Apple One bundling options. Apple also detailed its first concrete AI monetization plan, introducing token limits for cloud-based Siri processing beyond what its on-device AI can handle. Moorhead remained skeptical of the actual Siri experience, expecting the rebuilt assistant to stay in beta status for up to a year after launch. (The Decode) Federal Agencies Name Six Chinese AI Labs in a Distillation Advisory: The NSA, CISA, and FBI issued a joint advisory naming DeepSeek, Moonshot AI, Alibaba, Minimax, StepFun, and Z.AI for running industrial-scale knowledge distillation campaigns against US frontier models. Daniel Newman linked the advisory to a separate Anthropic security report describing API exchanges in which Chinese labs extracted answers directly from Claude. Patrick Moorhead pointed to his own August analysis of Kimi K2, which he said was distilled from frontier models months before the government confirmed the pattern. Newman estimated the distillation activity generated roughly $40 billion in revenue attributed to Chinese labs, separate from the $5 billion Anthropic removed from its own reported ARR after tracing distillation activity back to Meta's Muse model. (The Decode) IonQ's Investor Day Shows the SkyWater Bet Paying Off Early: IonQ used its September 9, 2026 investor day to show tape-out cycles falling from nine months to two months since acquiring SkyWater, alongside a raised combined revenue guide of $450 to $460 million, up from a standalone range of $280 to $290 million. The company confirmed Qolab as its first merchant foundry customer, with roughly a third of SkyWater's wafer capacity currently booked. Patrick Moorhead flagged that IonQ still has not disclosed gate fidelity and error rate figures for its Superion 256 roadmap, data he believes is more important than the qubit count headline. Daniel Newman placed IonQ alongside IBM as the only two companies pursuing a fully vertically integrated quantum stack, running at what he estimated is a $100 million quarterly pace. (The Decode) The Flip: Does the Distillation Advisory End Enterprise Use of Chinese Open Weight Models?: Daniel Newman argued the joint federal advisory makes Chinese open weight models like Qwen unsponsorable inside major enterprises, regardless of legality, because no general counsel wants a breach traced back to a model the FBI specifically named. Newman pointed to open weight alternatives like MBZUAI's K2 Horizon as a viable substitute already gaining ground. Patrick Moorhead argued the advisory specifically targets malicious extraction techniques and leaves legitimate distillation untouched as a valid technical method. Moorhead cited Meta's reported $5 billion in distillation spending against Anthropic's Claude as evidence the same technique operates as standard practice among US labs too. (The Flip) Citi's Bullish Call Ignites a Broad Chip Rally: A bullish Citi note on the semiconductor sector combined with CPU pricing chatter and renewed custom silicon momentum to send Intel, Qualcomm, AMD, and Broadcom all higher on September 8, even with oil prices falling. Patrick Moorhead credited the move to growing confidence across the entire AI buildout chain, from NVIDIA's line of sight toward $1 trillion in bookings to the financing and power capacity required to support it. Dell shares climbed almost 12% and HP gained roughly 11% on the same data center capex read-through. (Bulls and Bears) Oracle's Backlog Keeps Growing as Free Cash Flow Turns Negative: Oracle posted $19.3 billion in quarterly revenue, up 30%, with cloud infrastructure revenue up 121% and remaining performance obligations climbing $209 billion year over year to $664 billion. The company delivered more than 300,000 GPUs and signed over $30 billion in new AI cloud contracts during the quarter. Patrick Moorhead flagged that Oracle generated $23 billion in operating cash flow, funded largely through customer prepayments and equity, in the same quarter its free cash flow turned negative. Daniel Newman added that Oracle's cloud gross margins trail the larger hyperscalers, a tradeoff he said the company is betting will resolve through pricing power once customers are locked in. (Bulls and Bears) Adobe Beats Estimates Again, AI Revenue Still a Sliver of the Business: Adobe posted record revenue and non-GAAP EPS that beat estimates, with AI-first ARR up 150% to more than $650 million. Patrick Moorhead pointed out that figure still represents only 2.5 percent of Adobe's total revenue base, following a June pricing reset that redirected roughly $500 million toward a freemium push for Firefly. Adobe shares lagged the broader software rally that lifted Salesforce, ServiceNow, and Snowflake sharply higher on separate AI announcements during the week. (Bulls and Bears) Watch the full video at sixfivemedia.com, and subscribe to our YouTube channel so you never miss an episode. The Decode Anthropic Researcher's Doomsday Claim: https://fortune.com/2026/09/09/anthropic-researcher-resigns-warn-ai-companies-gambling-with-lives/ Qualcomm's AWS Deal: https://www.qualcomm.com/news/releases/2026/09/qualcomm-announces-multi-generational-product-collaboration-with Apple's Ternus Era: https://www.reuters.com/technology/foldable-iphone-pricier-18-pro-unveiled-apples-first-event-under-ternus-2026-09-09/ https://moorinsightsstrategy.com/research-notes/patrick-moorhead-discusses-apples-iphone-launch-on-cnbc-september-9-2026-broadcast-analysis/ Federal Distillation Advisory: https://www.cisa.gov/news-events/cybersecurity-advisories/aa26-251a IonQ Investor Day: https://x.com/MoorInsStrat/status/2097431533170913505 ; https://x.com/PatrickMoorhead/status/2078119899059179668 The Flip Does the Distillation Advisory End Enterprise Use of Chinese Open Weight Models? FOR: https://www.cisa.gov/news-events/cybersecurity-advisories/aa26-251a AGAINST: https://www.reuters.com/legal/litigation/us-urges-hands-off-approach-ai-regulation-g20-tech-meeting-2026-09-01/ Bulls and Bears Chip Rally: https://www.investing.com/news/stock-market-news/citi-boosts-chip-sector-outlook-as-semiconductor-stocks-rally-93CH-4892192 Oracle: https://investor.oracle.com/investor-news/news-details/2026/Oracle-Announces-Q1-Results-Driven-by-Triple-Digit-Growth-in-Cloud-Infrastructure-Revenues/default.aspx Adobe: https://finance.yahoo.com/technology/articles/adobe-reports-record-q3-results-200500281.html  

Dans de nombreux pays du monde, les étudiants commencent à reprendre le chemin de l'université. Une rentrée qui s'effectue sous le signe des difficultés économiques. En cause principalement les frais d'inscription, s'élevant à plus de 100 000 euros par an dans de grandes universités américaines. En France, les étudiants hors Union européenne sont confrontés à une flambée de ces coûts. Pour ne citer que ces pays. Les étudiants sont-ils devenus la variable d'ajustement des dépenses publiques ? Pourquoi ? Quelles conséquences sur les sociétés et les économies de demain ? Pour en débattre : - Marie Mesmeur, députée LFI Commission des Affaires culturelles et de l'éducation  - Hugo Harari Kermadec, professeur à l'université d'Orléans, sociologue de l'Enseignement supérieur, co-auteur du livre Arrêtons les frais, éditions Raisons d'agir - Ilan Amiard, vice-président étudiant du Crous de Bordeaux-Aquitaine, élu national de La Fédération des associations générales étudiantes (FAGE).

Some opportunities don't wait around forever. Heather Lea's life has been shaped by the ones she chose not to let pass—from adventure and solo travel to motorcycles and a journey that would take her much farther than she ever expected.

Joel, Chad , and Emi break down the intersection of AI recruitment technology, global labor markets, and industry regulation, alongside pop culture banter and sports highlights. Key Topics Covered:Pop Culture & Fantasy Football: Reactions to Steve Ballmer's retro Microsoft commercials and NBA ban, US Open tennis highlights, and fantasy football draft grades. HR Tech & Startups: Spotlights on Sonic Jobs' LLM integrations, Hackajob's Archer agent rebranding following a 3x ARR increase, and previews of global HR events. The H-1B & Union Debate: A look at how H-1B visa restrictions drive different hiring behaviors. Jobs Report Reality Check: An analysis of August's 162,000 job additions, against structural economic shifts, immigration, and tariff impacts. AI Compliance & Job Board Evolution: The European crackdown on fully automated management illustrated by Uber's €825 million Dutch fine, and what the closure of Guardian Jobs signals for traditional recruitment advertising.

The U.S. and China's AI strategies are diverging, according to Sam Vadas, who points to DeepSeek's new model as the newest example behind the thesis. This, as Moonshot AI targets a ramp up in ARR. Sam offers her top takeaways to close out the trading week. ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

AppleIphone DuoAvailable October Starting at $2000MetaUnveils personal AI agent: MuseNvidiaNvidia to buy Hugging Space for $13B.  Per WSJ. Jensen Blog post. More than 18 million developers, researchers and creators use Hugging Face to share more than 3 million models, 500,000 datasets and 1 million applications. More than 200,000 companies use the platform to discover, evaluate, customize and deploy AI.Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want and the computing platforms they want. NVIDIA compute will not be required to build on or deploy through Hugging Face.NikeNike removed from S&P 100Lot's saying “go woke, go broke”.  Revenue down from 2024: $51B vs 46b. Net Income down $5B vs 3.1bI highly recommend Shoe Dog! AI Whistleblower from Anthropic on X breaking every record possible. The Jacob Coxon Post? Planned? Phyop? Theory is Anthropic wants regulatory capture so they can govern.TeslaCyberCab launch is looking legit. Appears to be 100's of cars in Austin. 420 registered at Texas DMV. hahah 420 Rooting for Waymo, Zoox and others to be successful. PLAY Elon just stole my idea. Uber/Lyft drivers buy Cybercabs. EngineeringUnboxed assembly. The car is built as parallel modules (front casting, rear, pack/seats, outer skins) and joined late. Tesla says the line footprint is about half a conventional line. Deleting hydraulics and paint is what makes that join possible.UnoColor-in-mold RIM body skins. Outer panels (doors, hood skin, roof, quarters, bumpers) are polyurethane made by reaction injection molding with the gold mixed into the part. No paint shop. Cycle time minutes instead of hours. That is a factory change, not a styling choice.Dry brake-by-wire. First Tesla with zero brake fluid, zero brake lines, no master cylinder. Each caliper has its own electric actuator. Pads can pull fully off the rotor (less drag). No fluid to flush on a 24/7 taxi. One of the first production cars in the world to do this dry; Chery in China got there a few months earlier.Steer-by-wire with no column. Cybertruck already had steer-by-wire and a wheel. Cybercab deletes the wheel. The rack sits behind the front drive unit and only takes electronic commands from the autonomy stack.Supermanifold V3 thermal system. Tesla's claim matches what you read: they cut extra refrigerant valves and lines, merged high- and low-voltage controllers into one box, say production is ~80% automated and the system is ~38% more efficient than other automotive thermal setups. That is the heat-pump / battery / cabin plumbing, not a marketing slogan about “climate control.”Smaller, lighter, rare-earth-free drive unit. Single front motor, 163 kW / 219 hp. Tesla: 18% smaller, 25% lighter than top competing EV units, designed for sub-10-second automated assembly. Ferrite / Halbach instead of neodymium. First Tesla that is front-wheel-drive only.No human controls as a packaging rule. No wheel, pedals, mirrors, or rear window. That is not just UX. It lets them drop hydraulic plumbing, a steering column, mirror drag, and a lot of crash structure around a driver. Cd claimed under 0.2.48-volt low-voltage architecture. Same idea as Cybertruck: thinner wiring, fewer fuses, easier automation. Most of the industry is still on 12V.Small 4680 pack, high miles per kWh. ~48 kWh, ~3,100 lb car, EPA-adjusted range near 300 miles. The engineering bet is efficiency and utilization (two seats, ~80% of trips) instead of a giant battery.Fleet-life design, not owner-car design. 500,000-mile target, camera washers, inductive charging as the intended depot method (NACS still there for now), automatic butterfly doors, cabin camera for leftover bags. That is ops engineering: fewer service visits, no paint matching, no brake-fluid intervals.In addition to: No steering wheel, pedals, mirrors…. READ Electronic actuators instead of hydraulic liquid brakes…this seems so obvious!! The Tesla Cybercab doesn't have ANY brake fluid. It is the first production vehicle to have a brake-by-wire system. Electronic actuators are responsible for the clamping pressure, rather than hydraulic fluid that you see in traditional vehicles.This system improves efficiency since the brake pads can fully disengage. They can go entirely off or on. It also enables Tesla to fine-tune the braking to be as smooth as possible.PLUS, when the car is built with the unboxed process, Tesla doesn't need to run any brake lines, everything is seamless.READ Painting: All panels are RIM Reaction Injection Molding. NO PAINT! Elons says TRUE! EntrepreneurshipDemand will be off the charts.Space XGrok is way better! SpaceX price targets. Today from Brett CFOSpaceX CFO Bret Johnsen has announced that the company has signed another AI compute deal that will generate $1.11 billion of revenue per month ($13.3 billion per year), starting on Dec 1, 2026."Earlier this month, we closed another hosting deal. By the end of this year, with annualizing our December number, we're on track to hit $100 billion of ARR."Launching first AI Compute satellites in 2027. Previously, have reported that Starlink V3 satellites are much more complex.Elon x-post and article. AI and Robots will solve the debt problem.You better all hope Elon gets us out of this mess. Play Gavin Baker talking about Phd's saying cooling in space is impossible.  Gavin Baker again on a great post of DataCenter Reality. Read: Engines compared. Webcast here. SpaceX CFO Bret Johnsen has announced that the company has signed another AI compute deal that will generate $1.11 billion of revenue per month ($13.3 billion per year), starting on Dec 1, 2026.DataCenter Hosting: Earlier this month, we closed another hosting deal. By the end of this year, with annualizing our December number, we're on track to hit $100 billion of ARR.Orbital Compute: Clean, unlimited energy, no “community” issues. First Orbital compute satellites launching in 2027Play  Tobi Lutke on the Picasso of our time: the SpaceX Raptor Engine. Moving forward by subtraction. Elon security detail has been “marshalled”.Boring CompanyBoring in Nashville. Per Total Recall, we'll need tunnels on Mars. So maybe an acquisition? CaliforniaThe state of California. By Chamath. Schools have a constitutional funding guarantee, bondholders sit ahead of most other claims, and Medi-Cal and pension contributions come with legal and financial constraints. Together, those four categories account for roughly $150 billion of the $226.7 billion the General Fund expects to collect.Recommendations Travis Kalanick on David SenraBill Ackman called all 400 people on Forbes 400 list. 96% rejection.

George Wright III interviews Blake Erickson, co-author of The Science of Scaling and partner at Scaling.com, about his path from door-to-door team building, and a $10M revenue business, followed by a plateau that pushed him to pursue a bigger mission. Erickson explains how he partnered with Dr. Benjamin Hardy to co-author a book and launching Scaling.com. He distinguishes growth (e.g., 10–24% annually) from scaling (doubling or 10X in three years), arguing scaling requires doing different—often less—through focus, leverage, and “who brings the how.” He stresses that exponential, time-bound goals simplify strategy, cites a popcorn company jumping from 200 to 26,000 stores via one partnership, and emphasizes founder psychology, humility, pruning, and weekly alignment reviews. He shares Scaling.com's lessons from a $12M plateau, previews the book Power Law Strategy (Jan 26), and offers a free audiobook at https://scaling.com/audiobook-ce00:00 Exponential Scaling Mindset02:29 Mission to Sales Path05:44 Building Teams and Leaders07:12 Goals Shape the Present10:03 Comfort Plateau Wake Up12:59 Partnering With Ben Hardy16:59 Million Dollar Commitment18:34 All In on Future Self20:46 Growth vs Scale Defined23:02 Building for Scale Leverage25:00 Big Goals Simplify Strategy26:08 Exponential Goals Matter27:18 Popcorn Company 10X Path32:02 Rebuilding Model And Team38:31 Scalingcom Plateau Lessons43:10 Data Driven Scaling Science46:01 Where To Start Scaling48:51 Power Law Strategy VisionThanks for listening, and Please Share this Episode with someone. It would really help us to grow our show and share these valuable tips and strategies with others. Have a great day.George Wright III“It's Never Too Late to Start Living the Life You Were Meant to Live”FREE Daily Mastermind Resources:CONNECT with George & Access Tons of ResourcesGet access to Proven Strategies and Time-Test Principles for Success. Plus, download and access tons of FREE resources and online events by joining our Exclusive Community of Entrepreneurs, Business Owners, and High Achievers like YOU.Join FREE at DailyMastermind.comFollow me on social media Facebook | Instagram | Linkedin | TikTok | YoutubeGrow Your Authority and Personal Brand with a FREE Interview in a Top Global Magazine HERE.About BlakeBlake has built and operated several businesses and spent four years helping scale a door-to-door sales organization into an eight-figure company. He has recruited, trained, and led more than 1,200 people, with much of his experience centered on leadership, recruiting, and building high-performance teams. After reaching a point where his businesses required little day-to-day involvement, Blake found himself becoming comfortable and complacent while spreading his attention across real estate, media, podcasting, and several other ventures. He ultimately realized that maintaining what he had already built was no longer fulfilling, and he felt called to play a bigger game. That led him to sell his companies and real estate portfolio, step away from his podcast, and go all-in on Scaling.com, growing the company to $10 million in ARR in its first eight months. Today, he and his team advise more than 500 companies ranging from $500,000 businesses to $10 billion enterprises. Blake is a TEDx alumnus, and a professional speaker who has presented to organizations including Vistage, Entrepreneurs' Organization, YPO, Keller Williams, and Direct Selling University. He's also been a guest on podcasts such as Everything The Don't Tell You, Building the Good Life, The CO1 Show, Let's Get Real with Stephen Jones, and many more.LinksWebsite: http://Scaling.comGet the Audiobook at https://scaling.com/audiobook-ceInstagram: https://www.instagram.com/theblakeerickson/LinkedIn: https://www.linkedin.com/in/blake-erickson-756b54168/

Today's blockchain and crypto news Bitcoin is down slightly at $78,408 Ethereum is down slightly at $2,473 BNB is down slightly at $750 Strategy repurchases 1.8M STRC preferred shares. Visa's stablecoin settlement volume has surpassed a $20 billion ARR. Cronos said about 9 million dollars remains unrecovered Learn more about your ad choices. Visit megaphone.fm/adchoices

After a motorcycle racing crash left his father with a traumatic brain injury, Ari Henning's family life with motorcycles came to a stop. Years later, a journey shaped by his father's past began leading Ari toward Motorcyclist, RevZilla and a career neither of them could have planned.