La situación actual de 🇨🇺 respecto a la no-electricidad y el no-internet en absoluto, me han obligado olvidarme de los asistentes IA para código y regresar a los manuales y libros. A la vieja usanza, codeando a mano. Me siento en la caverna. Estoy en la caverna.

losing sleep for your goals is better than dreaming about them

Can’t put the genie back in the GPU.

Algún proveedor LLM decente que se pueda pagar desde Cuba?

If you're not having fun asking questions, you're not doing science right.

Underrated joy.....opening stuff up

Fable 5

Ready @QvaPay 🫡 Esperando aprobación 🔥 » A ver si alguien por fin me complace con una API para subir chorro de productos de una (>5k) » Ponle 🔍 en las primeras versiones 🙏 💜

Lo extraordinario comienza el día que tu estándar interno se vuelve más exigente que cualquier competencia externa. La mayoría fracasa por tolerar demasiado tiempo lo que sabe que podría hacer mejor.

“Solve via iteration. Then get paid via repetition.”

Executive Brief of our latest episode with special guests @rauchg, @bscholl and @maxhodak_. The AI Industrial Revolution 1. The engineer’s job has changed from shipping output to building the factory that ships it. We used to argue whether 10x engineers exist; now it’s 100x and 1,000x and the world hasn’t caught up yet. 2. Waste tokens to save time. Don’t look at the tokens either as inputs or outputs—just look at your time and the final output. 3. Enterprise software dies when the customer can generate their exact workflow internally. Even spreadsheets are cooked—they were the closest thing to custom software before everybody could build their own. 4. When models speak natural language and source code, pure software gets harder to defend. The moat shifts toward factories, hardware, network effects, regulatory barriers, and other things AI can’t generate on demand. 5. Two engineers can now vibe code a jet engine. Instead of passing spreadsheets around like it’s the ’90s, software engineers build the architecture, hardware engineers vibe code the parts, and the aerodynamics update in real time. 6. China’s open-source AI push is industrial policy. If users can generate software on demand, China’s hardware advantage compounds and Silicon Valley loses one of its biggest edges. 7. Intelligence is an unalloyed good, so you always want the smartest model. The moment one is even a little smarter, you stop trusting the dumber one’s answers. 8. Humans are becoming verifiers. The job isn’t to read every line of a pull request—it’s to sign off on the consequences and be willing to stand behind it when something breaks. 9. When AI can finish 200 pages of compliance paperwork in hours, hardware teams can iterate on an airplane design without months of regulatory rework after every iteration, shortening cycle times. 10. Healthcare is a small communist society running inside a larger capitalist one: there is no price list because patients don’t pay directly—you get care, and the bill goes to an insurer. The fix isn’t single-payer; it’s making care cheap enough to put on a credit card, which China is already doing. 11. Your job is no longer to do the work—it’s to train the agent that does it. 12. In the end it’s not humans vs. AI, but humans with AI vs. humans without AI. What’s left to us is creativity, taste, and judgment—a bicycle for the mind, accelerated.

Buy the dip and meditate 🧘🏻‍♂️ bitcoin:native

Marketplaces dentro de QvaPay. Si eres vendedor, del país que sea, vas a acceder a un mercado de 7 millones de dólares. No lo dejes pasar.

How to Get Rich (without getting lucky):

La noticia del BCC sobre la suspension de VISA y Mastercard en el procesamiento de operaciones no me sorprende. Lo que si me da gracia es el lloriqueo. NINGUNA PYME REALMENTE PRIVADA de Cuba tiene el chance de aceptar pagos con VISA o MC, eso es un tinglado de unos pocos. TODAS LAS PYMES REALMENTE PRIVADAS son mas que bienvenidos a QvaPay. Tu saldo en DOLARES REALES, sin vigilancia, sin corralitos financieros, sin bloqueos, 100% tuyo. No digo más.

Me acosté a dormir sin quemar todos mis tokens de Claude. Que despilfarro 🥵

“Be on guard. The road widens, and many of the detours are seductive.”

.@QvaPay .@ErichGarciaCruz Sería una práctica permisible crear un sistema interno para mi negocio que use la API del P2P para comprar QUSD, donde un cliente va a comprar en mi tienda, genero una oferta de compra en el P2P, envío tarjeta del peer al cliente y “me paga”?

Thread. I thought I was immune from ever feeling hollowed out by AI as a programmer, because I've always gotten far more enjoyment from shipping, getting users, and solving problems than indulging in the art of coding. As the LLMs have eaten deeper and deeper into our field, I've empathized with my peers who've expressed a sense of loss and disillusionment as the art of programming has become more and more automated. But, I've always seen myself as someone who saw coding as a means to an end to solve problems. Not something whose craftsmanship, culture, methodologies, and fads were worth getting too hung up on, beyond what was needed to adeptly deliver value to others and not fall behind the (frankly, rare) genuine advancements over the years. This all changed for me over the last week. The frontier probably shifted a bit earlier than today, but I didn't see it until now. The change has come about for me because GPT-5.5 was able to build complex software I needed built autonomously for 2-3 days at a clip. Work that would have taken me months, or even years if you include learning the requisite languages, libraries, and tooling, being completed over a weekend. This isn't something I think anyone who has been programming as long as I have can really be prepared for, this kind of velocity jump is just mindboggling. This is truly superhuman performance - it's not perfect, and there certainly is a level of simplicity and clarity that would come in the hands of the world's best programmers, but that margin is so small so as to be unnoticable when contrasted with the sheer volume of working software that it can produce per unit time. So, why has this caused a shift in the way I feel about these technologies, after all this time not having felt it as each subsequent model advanced closer to what we see now? There are two reasons. First, it's clear that the age of humans understanding how software works is over. Yes, humans will need to understand things, at least for a few more years, but we are now at a kind of escape velocity where the % of lines of code that are created every year that are even read, nevermind understood, by humans, is now permanently declining. But the real shift, is I am no longer a programmer, I am a manager. Good managers do not take credit for the work of their team - they see themselves in service of their team. Up until now, claiming "I built this" still felt true when talking about things I had created with the help of LLMs. But now, when the LLMs are writing thousands of lines of code, and I am simply providing guidance, direction setting, and oversight to catching the bigger errors, I found myself in the bizarre situation (that many will be in soon, I presume) of no longer feeling entitled to take credit for the work being done. Not being able to say "I built this" when sharing something whose basic conception came from my own mind, but under the tireless effort of these insane machines to actually reason through and materialize into a working solution, is devastating. Not because of the fact it doesn't feel truthful now, but because I know it will never be truthful again for myself and soon for all of the rest of us.