"Advertencia":
Porque en EE.UU. pusieron un cartel explicándole a los estadounidenses por qué Messi estaba jugando por Argentina y no para un equipo de EE.UU.
I'm traveling the world for a bit, starting with China but then hopping around the globe, anywhere. Open to any adventure. No plans, only a backpack. Hoping to meet & get to know humans from all walks of life. The pic is from a long hike on the Great Wall. For me, as a fan of history, this was an epic experience.
In China, first I'm visiting a few big cities & talking to engineers at the heart of China's AI revolution. After that, if feeling crazy enough, I'm hitchhiking (first time) across rural China for a few weeks. Hitchhiking because I think it's the best way to meet rural folks who I would otherwise never get the chance to meet. I hope to do the same in US and other places.
I have a request, if you have a travel recommendation, fill out the form(s) below if you feel like it. Or share with folks who might have advice about such travel.
Form 1 - travel recommendation:
If you can, recommend to me an interesting place I should visit anywhere in the world. For this, fill out form 1. Not touristy stuff, but something off the beaten path, that tourists may not know about, but is legendary. It could be as remote as meeting a herder in the mountains who is a local legend. Asia, Middle East, Europe, India, South/North America, Africa, Australia, anywhere. In China, I'm hoping to visit maybe Heibei, Shanxi, Shaanxi, Gansu, Sichuan, Yunnan, etc, so recommendations for spots to visit are helpful.
Form 2 - coffee:
If you want to grab a coffee with me anywhere in the world, fill out form 2 (please don't use form 1 for that).
Anyway, I hectically tossed stuff in backpack. Realizing I don't have a clear plan of any kind, which is probably the only way to do it. LFG.
Love you all ❤️
Coding agents are accelerating different types of software work to different degrees. When we architect teams, understanding these distinctions helps us to have realistic expectations. Listing functions from most accelerated to least, my order is: frontend development, backend, infrastructure, and research.
Frontend development — say, building a web page to serve descriptions of products for an ecommerce site — is dramatically sped up because coding agents are fluent in popular frontend languages like TypeScript and JavaScript and frameworks like React and Angular. Additionally, by examining what they have built by operating a web browser, coding agents are now very good at closing the loop and iterating on their own implementations. Granted, LLMs today are still weak at visual design, but given a design (or if a polished design isn’t important), the implementation is fast!
Backend development — say, building APIs to respond to queries requesting product data — is harder. It takes more work by human developers to steer modern models to think through corner cases that might lead to subtle bugs or security flaws. Further, a backend bug can lead to non-intuitive downstream effects like a corrupted database that occasionally returns incorrect results, which can be harder to debug than a typical frontend bug. Finally, although database migrations can be easier with coding agents, they’re still hard and need to be handled carefully to prevent data loss. While backend development is much faster with coding agents, they accelerate it less, and skilled developers still design and implement far better backends than inexperienced ones who use coding agents.
Infrastructure. Agents are even less effective in tasks like scaling an ecommerce site to 10K active uses while maintaining 99.99% reliability. LLMs' knowledge is still relatively limited with respect to infrastructure and the complex tradeoffs good engineers must make, so I rarely trust them for critical infra decisions. Building good infrastructure often requires a period of testing and experimentation, and coding agents can help with that, but ultimately that’s a significant bottleneck where fast AI coding does not help much. Lastly, finding infrastructure bugs — say, a subtle network misconfiguration — can be incredibly difficult and requires deep engineering expertise. Thus, I’ve found that coding agents accelerate critical infrastructure even less than backend development.
Research. Coding agents accelerate research work even less. Research involves thinking through new ideas, formulating hypotheses, running experiments, interpreting them to potentially modify the hypotheses, and iterating until we reach conclusions. Coding agents can speed up the pace at which we can write research code. (I also use coding agents to help me orchestrate and keep track of experiments, which makes it easier for a single researcher to manage more experiments.) But there is a lot of work in research other than coding, and today’s agents help with research only marginally.
Categorizing software work into frontend, backend, infra, and research is an extreme simplification, but having a simple mental model for how much different tasks have sped up has been useful for how I organize software teams. For example, I now ask front-end teams to implement products dramatically faster than a year ago, but my expectations for research teams have not shifted nearly as much.
I am fascinated by how to organize software teams to use coding agents to achieve speed, and will keep sharing my findings in future posts.
[Original text: https://t.co/rnnVWqebVe ]
Look at this astronaut's face during reentry, knowing the capsule exterior is at 5,000°F.
The physics of why he's alive are wild.
The air in front of the capsule compresses so violently at Mach 25 that it turns into plasma. 5,000°F on the surface. Half the temperature of the sun. The heat shield absorbs that energy by literally burning itself away, layer by layer, carrying the heat with it as gas.
One inch of material is the entire margin. On the outside of that inch: 5,000°F. On the inside: 75°F. Room temperature. The thermal gradient across that single inch is the steepest temperature drop humans have ever engineered.
The orange glow in the window is ionized nitrogen and oxygen. That plasma is why comms go black for six minutes during reentry. Ground control can't reach the crew. The astronauts are alone inside a fireball, falling at 25,000 mph, watching the laws of thermodynamics keep them alive through a 1-inch wall.
Artemis II did exactly this last night. Four astronauts hit Earth's atmosphere at 24,664 mph, rode a 4,900°F plasma sheath for six minutes of radio silence, and splashed down a mile from target.
The heat shield is now being inspected for cracks. They found over 100 on the last unmanned test.
Esto es de película. Espías de Corea del Norte intentan infiltrarse en empresas tech de Estados Unidos.
¿Cómo los detectan? Les piden que digan que Kim Jong-un es un dictador y no son capaces.
Lock in, we’re Moonbound.
Artemis II astronauts are more than halfway to their destination, and preparations for lunar flyby are underway. During their trip around the far side of the Moon, they will capture imagery to share with scientists (and you, too!).
imaginate, de repente, tener una foto con el planeta tierra de fondo; tenés que estar muy preparado para sostener esa experiencia, pero sobre todo para sobrevivirle, volver a la vida común, a la continuidad de lo cotidiano sin caer en la insignificancia total. durísimo.
That's us! 🌍
The Artemis II crew captured beautiful, high-resolution images of our home planet during their journey to the Moon. As @Astro_Christina put it: "You guys look great."
Forbes estima que Guillermo Rauch, argentino, CEO de Vercel sería ya multi millonario, con una fortuna superior a 2 mil millones de dólares.
Desconozco si es así pero sí se que no se parece a ningún otro multi millonario que conozcamos por acá.
Probablemente sea igual el único multimillonario con el que hablé varias veces y hasta que conoce qué hago pero, más allá de eso, es una persona super accesible, algo muy difícil para el resto.
Compartí cena en Guadalajara hace unos meses y vino como un orador más y, si bien muchos lo tratan como estrella y un poco no le queda otra que tomar el guante, lo vi como alguien que quiere vivir haciendo lo que le siempre le gustó y no lo que (supuestamente) debería hacer por su éxito. Creo que prefiere estar charlando de un bug en JavaScript en una WebView de iOS (de eso charlamos porque recordaba que yo estaba con ese tema) que jugando al golf con algún magnate tomando champagne de 3000 dolares. Al menos lo que se ve de él en público.
No siempre coincido con él y tuvimos algunos debates menores que ni debe recordar, pero siempre tuve la imagen de alguien que pensaba distinto a la media. Me quedó grabado eso de una charla que tuvimos en el auto cuando lo alcancé a su casa en San Francisco (hace muchos años, mucho antes de Vercel) después de un evento donde coincidimos. Además siempre me pareció una persona excesivamente optimista.
Evidentemente es un distinto, te guste o no él o lo que hace. 😎
En Argentina fue el organizador de las únicas JSConf que hubo, fui orador y allí lo conocí, y siempre muestra ganas de hacer cosas acá para la gente de acá. Siente siempre que Argentina está para ser más Silicon Valley de lo que es.
vibecoder asks claude code to build a chat app, gets a working prototype in 20 minutes, immediately tweets "just killed slack and discord"…
brother you don't even know what a distributed system is. you don't know what database replication means. you have no idea how websocket connections behave at scale or what happens when 50k people are online at once and someone's message needs to show up in 200ms across 3 continents
slack has engineers making $300k+ who have spent a decade solving problems you don't even know exist yet. race conditions, eventual consistency, message ordering, presence systems, file storage at scale, search indexing across billions of messages
your app works on localhost with 2 connections. that's not the same thing as "killing slack" that's a college homework assignment
the prototype is maybe 0.5% of what makes these products actually work in production. the remaining 99.5% is infrastructure, reliability, edge cases, and years of iteration on problems that only surface when real humans use your thing at scale
and the worst part is the confidence. "yeah its not perfect but ai one-shotted it, just need to adjust a few things and deploy" - the few things you need to adjust IS the entire product. thats like pouring a foundation and saying you basically built a skyscraper, just need to adjust a few things
ai is genuinely incredible for building tools and prototypes. i use it every day. but there's this weird thing happening where people who have never shipped anything to real users at scale now think the hard part of software is writing the first 200 lines of code
it never was bro
Earlier today, a user attempted to buy AAVE using $50M USDT through the Aave interface.
Given the unusually large size of the single order, the Aave interface, like most trading interfaces, warned the user about extraordinary slippage and required confirmation via a checkbox. The user confirmed the warning on their mobile device and proceeded with the swap, accepting the high slippage, which ultimately resulted in receiving only 324 AAVE in return.
The transaction could not be moved forward without the user explicitly accepting the risk through the confirmation checkbox.
The CoW Swap routers functioned as intended, and the integration followed standard industry practices. However, while the user was able to proceed with the swap, the final outcome was clearly far from optimal.
Events like this do occur in DeFi, but the scale of this transaction was significantly larger than what is typically seen in the space.
We sympathize with the user and will try to make a contact with the user and we will return $600K in fees collected from the transaction.
The key takeaway is that while DeFi should remain open and permissionless, allowing users to perform transactions freely, there are additional guardrails the industry can build to better protect users. Our team will be investigating ways to improve these safeguards going forward.
En mi opinión:
• Especialmente útil para solo founders, startups pequeñas o entornos donde, si algo se rompe, no sea crítico. Ahí es donde realmente aumenta la velocidad de desarrollo.
• En empresas grandes o con código crítico, el bottleneck nunca fue escribir código. Hay demasiados procesos cross-equipos y validaciones antes de pushear a prod.
• Los modelos son no determinísticos. Predicen el siguiente token. No puedo confiar 100% sin leer el output. Por eso creo que leer y entender código va a ser cada vez más importante.
• Me cuesta imaginar, al menos en los próximos 2 años, empresas sin ningún ingeniero. Alguien va a tener que monitorear y traducir lo técnico a las personas no técnicas. Por eso creo que los skills de comunicación se van a volver más relevantes que antes en ingenieros.
@_trish_xD You still had to learn it in college even though you pretty much NEVER used it in your job…. same applies now. It’s a way to train your thinking.