22 | scaling brands with AI • founder @aiscwork | marco@aiscwork.com

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Andrew Ng acaba de sacar el mejor curso que he visto sobre ingeniería de grafos. dos horas, desde un solo agente hasta la automatización completa 9:14 - tu primer agente 33:11 - agentes en bucle 1:02:46 - ingeniería de grafos 1:30:15 - agentes que se reescriben a sí mismos 1:49:05 - el sistema de grafos completo prompts → agentes → bucles → grafos con estas dos horas te sobran casi todos los tutoriales de agentes que has guardado este año la mayoría se queda en el primer agente y ya lo llama automatización. la última parte del curso va de montar el grafo que hace el trabajo sin que tú estés delante usas el mismo modelo y gastas los mismos tokens, pero tu semana cambia por completo
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se viene partidazo clásico
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Disney would've loved this in 1995. Today we're launching @mixie3D. (And yes, we made this entire film in it.) Making 3D has always meant one person doing a dozen jobs. Now a team of AI agents does them at once. Tell Mixar what you want. Agents model, texture and light the scene at the same time, and you can step in and change anything.
Made with AI
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El CEO de Google dándose cuenta de que Google Workspace está siendo usado por Claude y no por humanos
ANTHROPIC LANZÓ EL EMPLEADO MÁS BARATO DEL MUNDO Y CASI NADIE SE ENTERÓ Se llama "Claude for Small Business". Lo que puede hacer: → Gestionar facturas y finanzas → Crear campañas y contenido → Organizar ventas y clientes → Gestionar emails y calendarios → Ejecutar tareas entre apps Cómo funciona: → Conectas tus herramientas → Entiende todo tu negocio → Ejecuta flujos automáticamente Funciona con Microsoft 365, Google Workspace, Canva, QuickBooks y más. La idea es simple: en vez de abrir 10 herramientas, hablas con Claude y él hace el trabajo. Dedícale unas horas, lo agradecerás.
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generating voice is solved. knowing if the take is right is not. that's why you regenerate a line six times until it says the brand name right. in a language you don't speak, you can't even do that. Onepin checks every line, fixes the pronunciation, hands you what passes.
Your AI voice sounds human. So why can't it say your product's name? A great AI voice reads "Porsche Taycan" as TAY-can. Porsche says TIE-kahn. It guessed from the spelling, and nobody caught it, because nobody listens to line 1,200. Today we're launching Onepin: the production step after text-to-speech. It checks every line of voiceover before it ships using the voices you already work with. Onepin can: ➤ Check people's and product names against a 4-million-word pronunciation dictionary ➤ Spell out prices and dates before the voice speaks ➤ Score every line of audio for naturalness, clarity and word accuracy ➤ Fix the one wrong word in the same voice, without re-rendering the take Works with your voice subscription on @ElevenLabs, @OpenAI, @Google and 30+ more. No phonetic spellings to type. No re-rolls. No switching providers. Free to start, no credit card required. Hear the before and after in the thread ⬇️
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Got early access to Griffin from @tavus. I told it: "I'm practicing a speech. Interrupt me if I ramble." Thirty seconds in, it cut me off mid-sentence and told me exactly what I'd left out. Every AI I've used waits for its turn. This one doesn't.
Introducing Griffin, the first model to pass the video Turing test. 48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video. It’s the first Human Interaction Model (HIM).
Community note
The 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard. cellcog.ai/blog/tavus-gri… research.nvidia.com/labs/amri/proj… tech-ish.com/2026/10/02/tav…
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brands don't have an idea problem they have a testing and distribution problem until now you had one tool to generate content, another to schedule it and another to measure it. and in between, you guessing which message would land. Relay Self-Serve puts all 3 in one place: 1) you enter your website url. it researches the brand, builds the brand book and creates a full library of brand-aligned content in under 30 seconds. 2) you edit, comment on, approve or decline each post. 3) approved posts go out through a 50,000 human creator network or through your own connected TikTok account. and Relay tracks every result. the difference: a content generator → leaves you with the posts and the problem of getting them seen. Relay → creates, distributes and shows you which formats, hooks, personas and angles deserve more investment. TikTok is the only live distribution platform at launch, other platforms are coming soon. starts at $99 per month for 20 posts, and you own the content to use on any channel.
Today we’re introducing Relay We raised $20M from Google, Point72 & the founder of Reddit to build it. 1) Drop your website 2) Relay will create your content 3) Automatically distributes to our network of 50,000 U.S. creators 4) Drive millions of views and insights for your brand Comment your website URL below and we’ll build your brand’s content library for free 👇
Community note
The post claims Relay raised $20M from Google, Point72 & Reddit's founder with a 50k US creator network, but the site describes a small-scale TikTok content tool with no such details or scale and no independent sources confirm the claims. relaystudio.ai
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this is the use case for AI agents that makes the most sense to me. boring, repetitive, high volume, and directly tied to revenue.
In the last few years the effort to build a business has reduced dramatically You can build one in a weekend now if you really lock in But the effort to get customers has become equally hard, if not more You need to find leads, send emails, make calls, follow up, and figure out who is worth the time Today we are solving that with Runable Cold Outreach - It assigns itself a phone number and business email - Finds leads that fit your business - It handles calls, emails, and follow-ups, qualifies who’s interested, and converts them All of it, without you ever having to check or give any instructions It works around the clock, all year We’ve spent a lot of time helping people get their businesses off the ground. I’m excited about this next part - helping them find their customers
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ya no podremos reírnos del bicho
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esto es un salto más grande de lo que parece en el vídeo. hasta ahora un personaje de IA era una cara hablando. tú escribías, él respondía, y como mucho movía la boca. aquí el personaje tiene cuerpo y escenario: 1) actúa de cuerpo entero. baila, gesticula, hace el tonto. 2) se mueve por la escena. camina mientras habla en vez de quedarse clavado en un plano. 3) coge objetos. puede levantar un producto, enseñarlo y venderlo. 4) juega contigo a juegos web, repartiendo cartas y llevando la cuenta. y todo en directo, mientras le hablas. esa es la parte difícil. generar un vídeo así con tiempo por delante ya se sabe hacer. hacerlo en tiempo real, manteniendo al mismo personaje coherente mientras reacciona a lo que le dices, es otro problema. lo describes o subes una foto, y el agente lo monta. el caso de uso comercial está clarísimo: un presentador que coge tu producto y lo enseña, sin rodaje, sin actor y sin plató.
Create your own character. Call the shots. Live. Introducing A1 Playground + Agent: build a live AI character that talks, moves, and plays with you. Create yours: platform.vivix.ai/vivix-a1-m… Their look. Their personality. Their voice. Your choice. Describe who you have in mind, upload a picture, and let our Agent bring them to life. And they do a lot more than talk. 💃 Full-body performance. From air guitar to victory dances. 🚶 Move around the scene. Walk and talk. Pace while making a point. 🛍️ Interact with objects. Pick up products, show them off, and pitch them. 🎮 Play web games together. Deal cards, keep score, and play along. Solve a mystery with Sherlock Holmes, then interrupt him for a dance break. Take a walk with Socrates. Hand him a protein shake and debate the meaning of gains. Give Snape a bottle of shampoo. Ask for the most enthusiastic sales pitch of his life. Who will you bring to life?
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Marco retweeted
I'm incredibly excited to officially launch HQ. HQ is the shared AI context layer for your Humans, Agents, Dots, Bots and everything in between. Almost 1000 business run on HQ, including our own. The feedback has been phenomenal. Sign up now: hqforwork.com
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SIGAN A ESTA CUENTA, NO OS ARREPENTIRÉIS...
BREAKING: Today, we witnessed the future of marketing. Introducing Citation Outreach A profitable company can add +$3M/month by ranking in ChatGPT and Claude. 12 months ago nobody believed AI search could drive this much revenue. This is absolutely insane.
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Introducing OpenAI’s Dots x Higgsfield. Your always-on Higgsfield creative crew keeps working while you’re away. Check in by text, call or email, and pause the work whenever you need. Powered by GPT-6.1 Sol.
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okay this changed how i think about home robots
After 9 years. 16K+ family homes. 500M sqft inside real homes covered, we know home robots are being built in wrong order. So we built Matic the way nature grows a child. Finally, sharing our vision: 1.⁠ ⁠Why robots get stuck at the demo 2.⁠ ⁠Why labs can't ship robots 3.⁠ ⁠Why we started with eyes, not hands 4.⁠ ⁠The 99.999% rule in robotics 5.⁠ ⁠Where Matic is going next 1. Why most robots get stuck at demos Robot demos look brilliant in a room arranged around its limitations: familiar lighting, predictable furniture, nothing troublesome on the floor. A family’s home makes no such accommodations. There are cables, toys, shifting rugs and, occasionally, dog poop. Yes, humanoids will need to avoid that too. Repeating a task under familiar conditions of uncluttered floors is not the same as handling an unfamiliar home with all its chaos. 2. Why labs can't ship robots SLAM (Simultaneous Localization and Mapping) is how a robot maps its surroundings and locates itself within them. Ask most academics and they'll tell you it's a solved problem. But real homes are the most chaotic spaces that exist. There are glass doors that look like open doorways, mirrors, stairs, rugs, charging cables, and Legos placed all around. So ask yourself: if indoor mapping and navigation is "solved," where are the robots? Why aren't airports, hotels and grocery stores full of them? Calling it “solved” misses the question families actually care about: can I leave this thing alone and trust it? 3. Why we started with eyes, not hands Nature doesn't give birth to a fully working human. We took our cue from how nature develops humans: capabilities built on one another. Children learn to see before they learn to grab, and to grab before they learn to plan and handle the unexpected. Perception comes first. Manipulation follows. More complex responsibilities come after that. At every stage, the robot must earn the next job by doing its current one well enough. Before asking a robot to pick up a sock, we wanted it to understand where it was, where the sock was, and how to reach it. Most of the industry started at the top, with humanoids. We started at the bottom, with a robot whose job is to see and move through a home precisely with 1cm accuracy in any lighting condition. Floor cleaning gave that foundation an immediately useful job. It forced us to confront navigation, clutter, privacy and everyday reliability before reaching for more complex chores. The floor cleaner isn’t a detour from our larger ambition. It is how we’re building toward it. 4. The 99.999% rule in robotics At 90%, one in ten decisions is wrong, and a robot makes thousands in a single clean. That's the robot that bumps, gets lost, and falls down the stairs. Every extra nine is a new mountain. The failures get rarer, harder to find, and exponentially harder to fix. They barely even happen until they happen in your home. Matic's visual SLAM runs at 99.999% in 16K+ homes. We’re the ONLY unsupervised home robot at scale with pure vision-only full autonomy. If you ask us, the gap between 80% and 99.999% is where our 9 years of engineering went. We close that gap inside real homes. When Matic handles something imperfectly, it saves a short clip and keeps it on the device. It only leaves if the family chooses to share it. If they do, it gets labeled, fed back into the model, and every Matic gets smarter, including theirs. Families control what leaves their homes. We do the work of making the product better. Better robots earn trust > trust brings more homes > and more homes teach the robot more. 5. Where Matic is going next Phase one was perception and it's nearly done. Matic has covered 500 million square feet, 400K miles in thousands of real lived-in homes. Now phase two is going to be about manipulation. And our idea is to build a robot that doesn't just move through your home, but acts in it to eliminate even more chores. Each step must be useful today, not justified by something we promise tomorrow. The evolution of Matic is the revolution. The goal isn’t to put the most impressive humanoid in your living room. It’s giving your family time and energy back through robots that earn your trust, protect your privacy, and help without becoming another responsibility. More time for each other. Less work getting in the way. That’s Matic. Get yours today at maticrobots.com
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🚨 ¿CUÁNTO DE TU TIEMPO SE VA EN DESPLEGAR EN VEZ DE EN CONSTRUIR? el código lo escribes más rápido que nunca. el despliegue sigue tardando lo mismo que en 2018. InstaCloud ha levantado 8 M$ para arreglar esa parte: → serverless que autoescala, sin tocar infraestructura → cada agente trabaja en una réplica completa del entorno → producción no se toca → todo accesible por MCP y CLI la parte lenta de shipear ya no es escribir. es todo lo que viene después.
We just raised an $8M seed round to kill AWS, GCP, and Azure. Introducing instacloud.com, the agent-native serverless cloud. Your team is shipping code like never before. But you're getting caught up in manual, tedious DevOps work trying to deploy it. InstaCloud provides the serverless compute that lets your services autoscale, with all the infrastructure managed for you. Agents branch into complete replica environments when working, keeping prod safe and iteration speed high. And of course, it all works seamlessly with agents through MCP/CLI. Get off the traditional, legacy cloud. Start deploying your services on InstaCloud today.
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la parte que más me gusta de esta historia no son los 165.000 millones de visitas. es cómo empezó. la primera campaña la vendió sin tener nada: le dijo al equipo de Tyga que tenía clippers y a los clippers que tenía a Tyga. ninguna de las dos cosas era verdad todavía. y luego se puso a cortar los streams él mismo, elegir los mejores momentos y revisar clip por clip antes de que saliera. 500 millones de visitas en dos meses, a mano. solo después eso se convirtió en producto, y ahí está lo interesante: 1) seguimiento de visitas con oauth, o sea el dato real de la plataforma y no una captura que te manda el creador. 2) detección de fraude en cada cuenta que da like o comenta. 3) pagos automáticos por rendimiento. porque el problema de pagar por visita nunca fue pagar. fue demostrar que esa visita existe y que es de una persona. 2.850 campañas después, esto ya no es un bot de discord. es infraestructura de distribución. trabajo con creadores todos los días y esto es exactamente lo que separa una campaña que funciona de una que solo parece que funciona.
started clipster as a discord bot with 0 clippers 18 months later: 165,000,000,000 views a times square billboard would need 1,300 years to get that
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Sam Altman, CEO de OpenAI, dice que con GPT-6 Astra puedes crear 10 asistentes en una tarde. Cada uno puede encargarse de una tarea que haces todos los días. En 27 minutos explica cómo una sola persona puede hacer el trabajo que antes hacía un equipo entero durante semanas. Y mientras tanto, muchos seguimos haciendo esas tareas a mano. Su consejo es simple: darle tareas cada vez más difíciles. Software, ciencia, análisis, simulaciones… La IA cada vez puede hacer más y no lo estamos aprovechando
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sigan a este tipo si quieren aprender cosas realmente útiles relacionadas con la IA y sobretodo lo relacionado con claude no falla una
How to Build 10K$ Websites in Minutes with Claude Opus 5.5 Save this before you lose it 🔖
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cinco horas suena a mucho hasta que piensas en lo que llevas gastado esta semana haciendo a mano cosas que ya se automatizan solas. el salto de verdad no es aprender a escribir mejores prompts. es dejar de tratarlo como un chat. un chat te responde. un agente coge tu carpeta, abre los archivos, ejecuta cosas, se equivoca, lo vuelve a intentar y te deja el trabajo hecho. lo que yo miraría con atención en un curso así: 1) cómo darle contexto de tu proyecto una vez, para no repetírselo en cada mensaje. 2) cómo dejarle instrucciones fijas de cómo trabajar, en vez de corregirle siempre lo mismo. 3) qué permisos le das y cuáles no, que es lo que separa que te ahorre horas de que te rompa algo. 4) cómo partir una tarea grande para que no se pierda a la quinta iteración. lo demás lo aprendes usándolo. merece la pena y mucho
🚨 INSTEAD OF WATCHING NETFLIX TONIGHT. Spend 5 hours with this. Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything. The people who watch this tonight will wake up tomorrow with a new skill. Watch it and Bookmark it now.
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Este tipo en 22 minutos te muestra cómo aprender a crear videos automáticamente con Claude Code
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