Javier Cup

AI Engineer.
Teaching silicon to reason.

[Javier Cup @javi_cup]

@SergioGMN Te lo va a vender como servicio o incluso regalado pq el negocio va a ser que las empresas conecten su negocio via MCP o similar a su sistema de agentes personales. La Apple Store 2.0 o la Agent Store xD

[Javier Cup @javi_cup]

Evento top!! Muchas gracias a @rdelcampog e @inigodelasantas por la organización 👏

[Rubén del Campo @rdelcampog]

En @barracafh hablamos mucho de cercanía y frecuencia. De vernos a menudo, de volver a encontrarnos y de que las conversaciones no se queden en un apretón de manos.

El jueves pasado probamos a hacerlo construyendo juntos.

Aquí el resumen. 👇🏻 https://t.co/xM2XSkMj9X

[Javier Cup @javi_cup]

@JustMicrock Justo te iba a decir eso, que con el check azul deberías tener acceso. Espero que te funcione!!🤞

[Javier Cup @javi_cup]

@JustMicrock Es verdad que yo tengo uno, pero debería dejarte, si no menudos listos. Al final es cargar créditos en su sistema de API

[Javier Cup @javi_cup]

@JustMicrock De Café Cursor Valencia. El otro día los cargué al comprar créditos de la API, si quieres haz la prueba con 1$

[Javier Cup @javi_cup]

Esta red social es gratis

[NIK @ns123abc]

personal AI assistant wars, summarized

[Javier Cup @javi_cup]

@SergioGMN Tenéis una relación muy especial ❤️

[Javier Cup @javi_cup]

@OrcaRouter @SergioGMN poca broma

[Javier Cup @javi_cup]

@joakm5 @barracafh @soti_house El dream team!

[Javier Cup @javi_cup]

@SergioGMN @barracafh Ha sido un placer desvirtualizarse!

[Javier Cup @javi_cup]

@RogerKernel Difícil respuesta, las mejores cuentas tech en X tienen una imagen de un manga

[Javier Cup @javi_cup]

@pepeloperg Es que encima son 60k€, por hogar, ojo!! La vida padre!

[Javier Cup @javi_cup]

Mira @pepeloperg lo que hemos hablado antes en barraca sobre ser rico en España, 60k€

[RuralxData @RuralxData]

Madre mía, lo de Donosti es tremendo, la gente caga dinero

[Javier Cup @javi_cup]

Lectura interesante, por cierto el punto 7 y 8 es lo que comentaba hace un par de días

[GREG ISENBERG @gregisenberg]

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.

My observations:

1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively.

2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.

3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.

4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.

5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.

6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.

They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.

7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.

8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.

Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.

9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.

10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!

11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.

12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.

13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.

14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.

15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.

16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.

17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?

18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.

19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.

20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.

21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.

Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.

Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.

Happy to be home and locked in.

Until next time!

[Javier Cup @javi_cup]

Últimamente le estoy dando vueltas a lo que implica este trend, cualquier sw/programa es ahora copiable, se puede hacer ingeniería inversa y ya lo tienes para ti. Esto tiene implicaciones gigantes, por ejemplo, GTA6 sale en nada, ¿cuanto van a tardar en hacerle reverse engineering?¿semanas?¿días? Afectará a las ventas y manda un aviso a las compañías, "te ha costado cientos de millones tu producto y en cuestión de días tras el lanzamiento ya te han copiado". Esto es extrapolable a otros negocios basados en SW.

Va a tener efectos de segundo y tercer orden que me cuesta predecir, pero de entrada lo que veo más plausible es que las empresas no te dejen bajarte su producto y que este solo se pueda consumir online

[chasm @chasmmmmmmmmmmm]

NOT EVEN THE PLAYSTATION 5 IS SAFE 🚨

Someone jailbroke a PS5 and got Qwen 3.8 27B running on its GPU at 20 tok/s. That's a real 27B AI model running locally on a games console.

The same model on the PS5's CPU did about one token a minute.

Meanwhile, DDR4 prices are up 24% in 3 months, AMD just raised GPU memory prices, and 5090s are basically gone.

PS5 coming to a datacenter near you.

[Javier Cup @javi_cup]

Ahora invertir en tu cuenta de X te da acceso a Cursor 🚀

[Cursor @cursor_ai]

Cursor is now part of The X Subscription.

Current Cursor subscribers can keep their plan or switch to The X Subscription.

Paid plans share one usage pool across Cursor, Grok Build, and other Grok products, with twice the coding usage on Grok models as the equivalent Cursor plan. Premium, Super, and Ultra also include Grok Bot.

To make room for more Grok usage, third-party models in Cursor move to API pricing on the new plans. We'll keep working to make your usage go further, with more compute, better inference, and more token-efficient models.

The X Subscription is available at https://t.co/KIM9X7FZrq.

[Javier Cup @javi_cup]

Los puntos peligrosos y de posible corrupción no son auditables:
1) Indra: es quien recibe los datos de que se ha votado en cada colegio electoral y saca la suma final. Si ahí hay fraude no se puede auditar (q yo sepa)

2) Voto por correo: si hay manipulación de sacas, ídem, tampoco sabemos y se mezclan los votos con las personas que sí fueron a votar en persona.

Aquí una idea sería que los datos de cada colegio se publiquen por una de las personas independientes que contó votos. Si tenemos todas debe salir lo mismo que el punto 1), Indra. Pero vaya esto es imposible de conseguir

[Javier Cup @javi_cup]

@root_rat Este es el contenido de calidad por el que sigo a esta cuenta