fa¢u

[fa¢u @FacundoRu]

@codemiadot desarrollo con agentes e ia orientado a programadores

[fa¢u @FacundoRu]

@mantisarti amigo, como escribiste el prompt para que te recomendara las pag del libro?

[fa¢u @FacundoRu]

@maxifirtman Que paper es el que decís maxi ?

[Fran Pradas | Ingeniero de IA @franpradasAI]

🚨 LEE ESTO: Satya Nadella (CEO de Microsoft) acaba de soltar el artículo más importante del año sobre IA y empresa.

Y nadie en España está hablando de ello.

Te lo resumo en español y para tontos 🧶👇

[fa¢u @FacundoRu]

@maxifirtman es que no tiene sentido maxi... A que nos referimos sin humanos? a que no se realiza ningun control o validacion humana sobre nada?
Se esta tratando que el agente de IA como algo que tiene vos y voto y solo es una herramienta

[fa¢u @FacundoRu]

@ladriguruok de codemia hice el de aprende IA que lo dicto Maxi super completo y fueron 4 clases de 2 horas explicando todo desde cero sin dejar nada por sentado.
el de google tambien lo hice y para mi pasa cosa por alto. El de codemia esta preparado para gente que posta no sabe nada de IA

[fa¢u @FacundoRu]

@Rafadelbarrio2 me interesa, donde me contacto?

[Maximiliano Firtman @maxifirtman]

🔴CURSOS Y EVENTOS DE IA

Sí, yo doy cursos de IA en @codemiadot (hoy empiezo uno) pero no quita que haya muchos otros cursos o eventos que le sirva a los que quieren empezar y necesitan un empujón inicial.

Si conocés un curso o evento, dejá link con algún detalle u opinión👇

[Mario Zechner @badlogicgames]

I'm usually not one to write thought pieces without much technical depth. But here we go.

Slow the fuck down.

https://t.co/dcOwPK357F

[fa¢u @FacundoRu]

@G_Programming y cuales son los fundamentals que uno deberia tener afianzados @G_Programming ?Concuerdo con lo que dices que lo importante es el porque y no el como lo hacemos.Mi situacion es no saber como aplicar esos fundamentals.Tienes pensando hacer algun video sobre eso? o hay alguno ya?

[fa¢u @FacundoRu]

@maxifirtman Meli no tiene QA contratados, el testing lo hacen los devs

[Shraddha Bharuka @BharukaShraddha]

Complete Full Stack Developer Roadmap 2026📚

✅Frontend
✅Backend
✅Database

1/n

[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.

[fa¢u @FacundoRu]

@arielmathov @cursor_ai Product

[fa¢u @FacundoRu]

Thank you @PlaybackPress for writing this helpful article.

An Animated Introduction to Web Development from Back to Front

https://t.co/alXWfx4UC9

[fa¢u @FacundoRu]

@maxifirtman perdon @maxifirtman pero para mi no es tan claro, que es lo que reflejarian ? cual seria el estado?

[GitHub @github]

👀 Most devs use Copilot like autocomplete. But senior devs use it like a delegated engineer. Here’s your 1-week workflow to stress test Copilot where it actually matters ⬇️

[agrim singh @ ai engineer world fair @agrimsingh]

https://t.co/I6mRRqeQWT

[Anton Martyniuk @AntonMartyniuk]

Junior developer needs to know 4 patterns

Middle dev needs to know 12 patterns

Senior developer needs to know 20 patterns

Design patterns help you solve common problems and improve code quality if used properly.

Ever wondered which design patterns you should focus on as you grow as a developer?

This could be the difference between writing good code... and building great software.

👉 𝗝𝘂𝗻𝗶𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿:

You don’t need to know everything at once.
Focus on the essentials — the patterns that show up everywhere.

1️⃣ Builder
2️⃣ Factory Method
3️⃣ Singleton
4️⃣ Decorator

These four patterns help you create, organize, and extend objects efficiently.

Master these, and you’ll write cleaner, more flexible code from day one.

👉 𝗠𝗶𝗱𝗱𝗹𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿:

Ready to step up?

Now it’s time to add more versatile tools to your toolbox.

1️⃣ Strategy
2️⃣ Adapter
3️⃣ Abstract Factory
4️⃣ Template Method
5️⃣ Facade
6️⃣ Bridge
7️⃣ Command
8️⃣ Mediator

These patterns teach you how to swap behaviors, simplify complex systems, and make your code more modular.

👉 𝗦𝗲𝗻𝗶𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿:

You've mastered the basics.

Now it's time to tackle patterns that solve the toughest architectural challenges.

1️⃣ Prototype
2️⃣ Composite
3️⃣ Chain of Responsibility
4️⃣ State
5️⃣ Flyweight
6️⃣ Proxy
7️⃣ Visitor
8️⃣ Interpreter

These patterns give you superpowers for working with complex structures, dynamic behaviors, and resource optimization.

You'll notice: as you start solving bigger problems, these patterns show up again and again.

📌 Important note:
Don't try to learn everything all at once!
Follow a progression — master the basics, then level up with more advanced patterns as you grow.

Which design pattern was the hardest for you to learn, and how did you finally "get it"?

——

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