Ronny López

Eventually opinionated. Opinions are my own, but I change them very often.

[antirez @antirez]

@zeeg The majority of people are not able to distinguish good from bad.

[DHH @dhh]

You can’t outwork the whole world. There’s always going to be someone somewhere willing to work as hard as you. Someone just as hungry. Or hungrier.

Assuming you can work harder and longer than someone else is giving yourself too much credit for your effort and not enough for theirs. Putting in 1,001 hours to someone else’s 1,000 isn’t going to tip the scale in your favor.

What’s worse is when management holds up certain people as having a great “work ethic” because they’re always around, always available, always working. That’s a terrible example of a work ethic and a great example of someone who’s overworked.

A great work ethic isn’t about working whenever you’re called upon. It’s about doing what you say you’re going to do, putting in a fair day’s work, respecting the work, respecting the customer, respecting coworkers, not wasting time, not creating unnecessary work for other people, and not being a bottleneck. Work ethic is about being a fundamentally good person that others can count on and enjoy working with.

So how do people get ahead if it’s not about outworking everyone else?

People make it because they’re talented, they’re lucky, they’re in the right place at the right time, they know how to work with other people, they know how to sell an idea, they know what moves people, they can tell a story, they know which details matter and which don’t, they can see the big and small pictures in every situation, and they know how to do something with an opportunity. And for so many other reasons.

So get the outwork myth out of your head. Stop equating work ethic with excessive work hours. Neither is going to get you ahead or help you find calm.

[The Outwork Myth — It Doesn't Have To Be Crazy At Work, 2018]

[Guillermo Rauch @rauchg]

Every time GitHub has an outage our team is paged. Incidents at Vercel get automatically filed by anomaly detection systems.

We just detected an outage 16 minutes before their status page changed. Deployments suddenly dipped and surged.

Despite all the chatter about coding AGI, the reality is that software infrastructure remains an extremely hard problem.

I have no doubt the GitHub team is highly competent, and there's no shortage of models and agents available to them. Don't forget this is the company that brought us Copilot, the first major breakthrough product in AI coding. Yet clearly the prompt "/goal scale GitHub, make everything extremely fast, make no mistakes" is not enough.

The hard parts of software remain very hard, especially under unprecedented demand, as more people join in on the fun of building new things.

[kate @whoiskatrin]

breaking news, there is life outside of agents

ciao

[Ronny López @ronnylt]

@fodor Pues yo tengo otro amigo que organizaba hackathons para que el equipo hiciera horas extras y trabajara los findes. A ver si va a ser el mismo Marek.

[Mitchell Hashimoto @mitchellh]

I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out.

I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really).

It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely.

The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture.

We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying.

I worry.

[Guillermo Rauch @rauchg]

If you become exceptional at managing agents, but are also exceptional in your understanding of the fundamentals, you will be unstoppable.

We all prefer to work with masters of their craft. What’s new: you can’t afford to miss out on the amplification agents have on your output

[Ronny López @ronnylt]

@antirez Same. I’ve spent way too many hours leading debates around JS frameworks, rewrites, tooling, and whatever the new hot thing was. So much energy for so little actual value most of the time.

[antirez @antirez]

I must admit that nothing about computers, since I'm in love with the field, was so uninteresting as the Javascript different fashions, waves, frameworks, rewrites, hypes. And I'm one that loves almost every shit programming related.

[Ronny López @ronnylt]

@davidalvarezdlt ¿Qué es para ti un coworking decente? ¿Qué no le puede faltar?

[Miguel Carranza @elwatto]

Many such cases. Monoliths acquired for billions, while startups with 1,000 users worry they won’t scale without the latest architecture preached by some random conference tech influencer. Just be pragmatic. Use the right tool for the problem and the stage.

[Ronny López @ronnylt]

@davidalvarezdlt @Deckard86 Puede ser, y de esto se ha hablado mucho y no es generalizable, hay de todo tipo de casos.

El otro día escucha al CEO de una empresa bootstrapped 100% remoto hablando de por qué es más importante que nunca el saber trabajar en remoto y desarrollar esos skills.

[Ronny López @ronnylt]

@davidalvarezdlt @Deckard86 Si te rascaste los huevos no fue culpa tuya, fue de tu manager/responsable/socio/whatever. Y es lo de siempre, la gente que se rasca los huevos se los rasca en remoto, presencial y en híbrido.

[Ronny López @ronnylt]

@flopezluis @davidalvarezdlt Félix, creo que la "ofensa" viene de que te has mofado sin dar el contexto completo.

Seguro que sabes lo difícil que es montar una empresa de cero, aguantar años y poder pagar nóminas...

No es "Voy corriendo porque todos sabemos que es más difícil tener la idea que ejecutarla"

[Ronny López @ronnylt]

@Jason I'm in

[Ryan Florence @ryanflorence]

I'm not sure anybody has AI coding figured out, but some sure think they do

I've experienced the entire spectrum from "my job is cooked" to "agents are chopped, doing this myself"

I see their tweets and think "ah yes, I remember being on that point in the cycle last month"

[Míriam González @miriamgonp]

Tengo 35 años y cancer de mama metastásico, un caso raro, menos del 1% de tumores de mama son como el mío y hay poca documentación sobre ello.

Por eso me gustaría encontrar personas que se dediquen a esto y que quieran investigar con mi caso. Twitter haz tu magia

[Ronny López @ronnylt]

100%

[Karri Saarinen @karrisaarinen]

One unproductive AI discourse pattern keeps to be how individual workflows preferences are talked as the universal hallmark of software engineering.

Group 1: A solo builder with agents, their preferred stack, and a pile of markdown files, working on their own apps, is the right way to build and everyone else ngmi

Group 2: A much larger group building with agents at scale inside companies, where coordination, reliability, shared systems, and organizational complexity create a very different set of problems which most people don't hear about.

tbh individual workflows can still be directionally useful to show new ideas, but they can also be not stable, and enterprises might have very different problems that individuals don't ever have.

It's like why small startups don't need to or shouldn't operate like Google, but Google kind of has to operate more or less like company of Google's scale.

All ideas are good but much of the AI narrative still very confidently comes from group 1 too little from group 2 (with few notable exceptions).

[Ronny López @ronnylt]

@david_bonilla @iagolast David, imposible, imposible no sé yo. Por muy indeterminista que sea la generación de código, tienes múltiples procesos deterministas para controlar el resultado.

(yo hablo de un entorno de desarrollo de software profesional, si me hablas de vibe coding y esas cosas ahí no sé)

[Ronny López @ronnylt]

@iagolast @david_bonilla PRDs en lenguaje natural no son el problema, el problema es no bajarlos a capas verificables.

Debugging nunca fue solo "leer código", sino aislar y validar.

No creo que estemos perdiendo control (yet), estamos moviendo dónde ejercerlo.

[Ronny López @ronnylt]

@iagolast @david_bonilla Se está confundiendo lenguaje con control.

El control no viene de "hablar más cerca de la máquina", sino de tener restricciones verificables (tipos, tests, invariantes, etc..).

La IA no rompe eso, solo amplifica el problema de siempre: specs incompletas y no verificables