Gabriel Moral 🇮🇪 🥘

More haste less speed. Software writer at @dinghq. Video game player 🕹️

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

Learn as if you were to live forever.
- Mahatma Gandhi

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

Inside the Super Nintendo cartridges 💎 https://t.co/DRgsnl7jJm

[Daniel Blanco 💻🤖 @DanielBlancoSWE]

En cuanto a los despidos de Blocks: estamos hablando de una empresa que pasó de 3,500 empleados en 2019 a 13,000 en 2022. Más del triple en sólo 3 años.

Al mismo tiempo, los ingresos de la empresa llevan estancados desde finales de 2021. Todas esas contrataciones no han supuesto un crecimiento.

Eso hizo que las acciones bajaran un 75% desde finales de 2021. Al no haber growth, el mercado castiga la empresa.

Ahora despiden al 40% de la plantilla, apuntando al incremento de productividad con la IA. Si hubo tal aumento de productividad, como es que no se está reflejando en un aumento de los ingresos?

Es un overhire de libro, del mismo CEO que tenía más de 7 mil empleados en Twitter.

Podemos echarle la culpa a la IA, sí. Y seguramente tendrá parte de culpa en algunos despidos. Pero en este caso, la razón principal es otra: estancamiento a pesar de contratar como locos.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

Ladrón que roba a ladrón, tiene 100 años de perdón.

[Anthropic @AnthropicAI]

We’ve identified industrial-scale distillation attacks on our models by DeepSeek, Moonshot AI, and MiniMax.

These labs created over 24,000 fraudulent accounts and generated over 16 million exchanges with Claude, extracting its capabilities to train and improve their own models.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@deAprendices https://t.co/uhdAmqdqzx

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@deAprendices https://t.co/rBcOMQFWrz

[deAprendices @deAprendices]

Hemos terminado de leer "AI Engineering", muy recomendable.

Estamos buscando nuevo libro para leer, indicad en un comentario vuestras propuestas (máximo 3), dejamos de margen hasta el final del 17 de febrero.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@juanmacias How much revenue is going to generate in the next 6 months? Show me the money not the LOC

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

https://t.co/QadMXBo0zs

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

💯

[Andrej Karpathy @karpathy]

A few random notes from claude coding quite a bit last few weeks.

Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent.

IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits.

Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased.

Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion.

Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage.

Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building.

Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it.

Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements.

Questions. A few of the questions on my mind:
- What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*.
- Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro).
- What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music?
- How much of society is bottlenecked by digital knowledge work?

TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

🔝🔝🔝😂

[Peter Girnus 🦅 @gothburz]

Last quarter I rolled out Microsoft Copilot to 4,000 employees.

$30 per seat per month.

$1.4 million annually.

I called it "digital transformation."

The board loved that phrase.

They approved it in eleven minutes.

No one asked what it would actually do.

Including me.

I told everyone it would "10x productivity."

That's not a real number.

But it sounds like one.

HR asked how we'd measure the 10x.

I said we'd "leverage analytics dashboards."

They stopped asking.

Three months later I checked the usage reports.

47 people had opened it.

12 had used it more than once.

One of them was me.

I used it to summarize an email I could have read in 30 seconds.

It took 45 seconds.

Plus the time it took to fix the hallucinations.

But I called it a "pilot success."

Success means the pilot didn't visibly fail.

The CFO asked about ROI.

I showed him a graph.

The graph went up and to the right.

It measured "AI enablement."

I made that metric up.

He nodded approvingly.

We're "AI-enabled" now.

I don't know what that means.

But it's in our investor deck.

A senior developer asked why we didn't use Claude or ChatGPT.

I said we needed "enterprise-grade security."

He asked what that meant.

I said "compliance."

He asked which compliance.

I said "all of them."

He looked skeptical.

I scheduled him for a "career development conversation."

He stopped asking questions.

Microsoft sent a case study team.

They wanted to feature us as a success story.

I told them we "saved 40,000 hours."

I calculated that number by multiplying employees by a number I made up.

They didn't verify it.

They never do.

Now we're on Microsoft's website.

"Global enterprise achieves 40,000 hours of productivity gains with Copilot."

The CEO shared it on LinkedIn.

He got 3,000 likes.

He's never used Copilot.

None of the executives have.

We have an exemption.

"Strategic focus requires minimal digital distraction."

I wrote that policy.

The licenses renew next month.

I'm requesting an expansion.

5,000 more seats.

We haven't used the first 4,000.

But this time we'll "drive adoption."

Adoption means mandatory training.

Training means a 45-minute webinar no one watches.

But completion will be tracked.

Completion is a metric.

Metrics go in dashboards.

Dashboards go in board presentations.

Board presentations get me promoted.

I'll be SVP by Q3.

I still don't know what Copilot does.

But I know what it's for.

It's for showing we're "investing in AI."

Investment means spending.

Spending means commitment.

Commitment means we're serious about the future.

The future is whatever I say it is.

As long as the graph goes up and to the right.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@DanielBlancoSWE @Toscanorevenge Fair enough 👌

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@DanielBlancoSWE @Toscanorevenge La mayoría de personas trabaja por dinero, cuanto más mejor. No se me ocurre ningún incentivo que lo reemplace. ¿Tienes algún ejemplo?

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

Viendo las respuestas a este hilo se entiende la sociedad donde vivimos. Todo el mundo opina de todo sin saber un absoluto carajo.

[Diario de un picateclas @devruso]

poco se habla de que microsoft se acaba de sacar la chorra con .net 10 y su rendimiento

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@mikeilundain @ACDPeloton Me haría muchísima ilusión, vivo en Irlanda desde hace 9 años y le sigo desde hace mucho tiempo.

[deAprendices @deAprendices]

¡Curso nuevo, libro nuevo!

Hemos aparcado el libro "Deciphering data architectures", y estamos buscando nuevo libro para leer, indicad en un comentario vuestras propuestas (máximo 3), dejamos de margen hasta el final del 3 de septiembre.

Gracias.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

@VicenteSevilla En España no piden nada comparado con lo que piden en otros países

[Greg Young @gregyoung]

https://t.co/zZFfDMzVUK

Code I wrote no longer is even shown to have been written by me Check out my "history" in https://t.co/umqPJIopgr

I have written no @eventstore code since 2018?! If you actually believe this they likely have a bridge for sale #SCUMBAGS

[Team Visma | Lease a Bike @vismaleaseabike]

🇮🇹 #GirodItalia

He never left - Combativity award for WVA. 🌟

[deAprendices @deAprendices]

Hemos terminado de leer "Balancing Coupling in Software Design", bastante interesante, y ahora estamos buscando nuevo libro para leer, indicad en un comentario vuestras propuestas (máximo 3), dejamos de margen hasta el final del 30 de mayo.

[Gabriel Moral 🇮🇪 🥘 @Gabrielmoral]

A company’s goals extend beyond its stated objectives and metrics; they include “continuing to exist,” “having enough money to pay everyone,” and “having a good reputation.”
From the staff engineering book.