David Lobe

Dad of two. Cloud Developer. Sociologist-in-progress in my spare time. #golang #docker #kubernetes #linux

[David Lobe @lopezator]

@Sercar_Gon @demas6Basket Tal cual. A engañar a otros 😅.

[Dev Side Story 💣 @devsidestory]

Passkeys & Buenri

[Guillermo Rauch @rauchg]

Almost every SaaS app inside Vercel has now been replaced with a generated app or agent interface, deployed on Vercel.

Support, sales, marketing, PM, HR, dataviz, even design and video workflows. It’s shocking.

The SaaSpocalypse is both understated and overstated. Over because the key systems of record and storage are still there (Salesforce, Snowflake, etc.)

Understated because the software we are generating is more beautiful, personalized, and crucially, fits our business problems better.

We struggled for years to represent the health of a Vercel customer properly inside Salesforce. Too much data (trillions of consumption data points), the ontology of Vercel was a mismatch to the built-in assumptions, and the resulting UI was bizarre. We generated what we needed instead. When you don’t need a UI, you just ask an agent with natural language.

We’ve also been moving off legacy systems with poor, slow, outdated, and inconsistent APIs, as well as just dropping abstraction down to more traditional databases. UI is a function 𝑓 of data (always has been), and that 𝑓 is increasingly becoming the LLM.

[Akash Muni @akashmuni27]

That story is real and it's the one that made the industry realize how far this had gone.

It was Target. 2012.

A teenage girl's father walked into a store furious because Target had sent his daughter baby coupons.

He thought Target was encouraging his daughter to get pregnant.

Target apologized.

A few weeks later the father called back.

His daughter was pregnant.

Target knew before her own family did.

What gave it away was a specific combination of purchases.

Unscented lotion. Certain vitamins. A large handbag instead of a small purse.

No single item was suspicious.

But the pattern matched thousands of women who later bought baby products.

Target's data scientist called it the "pregnancy prediction score."

They got so accurate they had to deliberately add random unrelated coupons next to the baby ads.

So it wouldn't feel like they knew.

They knew. They just didn't want you to know they knew.

14 years ago.

Imagine what the model looks like now.

[Akash Muni @akashmuni27]

It's not reading your thoughts.

It already knows what you're going to think.

Here's how.

You are not unique.

There are 10,000 people with your exact age, location, income bracket, browsing history, purchase pattern and social graph.

When those 10,000 people started searching for running shoes, you hadn't yet.

But you will.

The algorithm already watched it happen with people identical to you.

So it shows you the ad before you search.

You think it read your mind.

It just knew the next chapter of your story because it already read it on someone else.

This is called predictive behavioral modeling.

And it is accurate enough that Facebook's own researchers once described it as being able to predict a life event before the person experiencing it is aware of it themselves.

It's not surveillance of your thoughts.

It's a pattern match so precise it feels like one.

[Will Bredderman @WillBredderman]

Worst of all, gym classes are making them run miles an Uber could cover in less than a minute.

[Naruto @NarutoNolimits]

Jensen Huang on the smartest person he's ever met;

[Madison Kanna @Madisonkanna]

as a software engineer, i feel a real loss of identity right now.

for a long time i defined myself in part by the act of writing code. the pride in a hard-earned solution was part of who i was. now i watch AI accomplish in seconds what took me hours. i find myself caught between relief and mourning, awe and anxiety. the craft that shaped me is suddenly eclipsed by a machine. who am i now?

[Marc @MarcJSchmidt]

All my new code will be closed-source from now on. I've contributed millions of lines of carefully written OSS code over the past decade, spent thousands of hours helping other people. If you want to use my libraries (1M+ downloads/month) in the future, you have to pay.

I made good money funneling people through my OSS and being recognized as expert in several fields. This was entirely based on HUMANS knowing and seeing me by USING and INTERACTING with my code. No humans will ever read my docs again when coding agents do it in seconds. Nobody will even know it's me who built it.

Look at Tailwind: 75 million downloads/month, more popular than ever, revenue down 80%, docs traffic down 40%, 75% of engineering team laid off. Someone submitted a PR to add LLM-optimized docs and Wathan had to decline - optimizing for agents accelerates his business's death. He's being asked to build the infrastructure for his own obsolescence.

Two of the most common OSS business models:
- Open Core: Give away the library, sell premium once you reach critical mass (Tailwind UI, Prisma Accelerate, Supabase Cloud...)
- Expertise Moat: Be THE expert in your library - consulting gigs, speaking, higher salary

Tailwind just proved the first one is dying. Agents bypass the documentation funnel. They don't see your premium tier. Every project relying on docs-to-premium conversion will face the same pressure: Prisma, Drizzle, MikroORM, Strapi, and many more.

The core insight: OSS monetization was always about attention. Human eyeballs on your docs, brand, expertise. That attention has literally moved into attention layers. Your docs trained the models that now make visiting you unnecessary. Human attention paid. Artificial attention doesn't.

Some OSS will keep going - wealthy devs doing it for fun or education. That's not a system, that's charity. Most popular OSS runs on economic incentives. Destroy them, they stop playing.

Why go closed-source? When the monetization funnel is broken, you move payment to the only point that still exists: access. OSS gave away access hoping to monetize attention downstream. Agents broke downstream. Closed-source gates access directly.
The final irony: OSS trained the models now killing it. We built our own replacement.

My prediction: a new marketplace emerges, built for agents. Want your agent to use Tailwind? Prisma? Pay per access. Libraries become APIs with meters. The old model: free code -> human attention -> monetization. The new model: pay at the gate or your agent doesn't get in.

[David Lobe @lopezator]

@apa8263 @ADaimiel @NBA2K No os dais cuenta de que probablemente le haya puesto sus características físicas al jugador? Yo también hago siempre lo mismo 🙈

[@levelsio @levelsio]

When I realized most low effort modern art was just money laundering

Everything started to make sense

[David Lobe @lopezator]

Ídolo 🥲

[The Night Warrior @WarriorNight007]

@PicturesFoIder Listen from him itself

[David Lobe @lopezator]

Qué opinas de este parecido razonable @guillegimenez_ ? 🫠

[TheBasedLord @TheBasedOne_]

Tyrese Haliburton & Julian Strawther Might Be Brothers 😂😂

[David Lobe @lopezator]

@penniath Lo peor no son los otros chavalitos que los siguen, que tambien. Pero lo de los cuarentones que se creen esas mierdas ya...🤦‍♂️🟥

[Paco Álvarez Romano @romanos_somos]

Supongo que ya sabéis todos que el clan más grande de maoríes de Nueva Zelanda, estos del All Blacks y las Hakas, se llaman a sí mismos "paniora" que en su idioma quiere decir... españoles. ¿Cómo es esto posible? Os lo explico en un minihilo sigue +

[David Lobe @lopezator]

@raffiovalentina A mí me ha empezado a salir sola @linguriosa y la verdad que me encanta! Para que la apuntes en tu lista 😝.

[Hanky 🍷 @Hanky_solo]

El cabronazo de las gafas me representa. Joder, qué hartón de reír.

[David Lobe @lopezator]

Ahora toca estrenar mis @TimpersBrand ♥️

Si además de comprar das tu apoyo al pequeño comercio y a empresas que emplean personas con discapacidad, pues mola x2.

[David Lobe @lopezator]

No me puedo creer que haya empresas que monitoricen el "rendimiento" de sus trabajadores por como mueven el ratón. Hecha la ley, hecha la trampa 🫣🫠 https://t.co/S6BOseWkR9