Alexandru Nedelcu

Alexandru Nedelcu

@alexn.org

Software developer, FP, Scala, Kotlin, Java / JVM, Haskell, Rust; contributor to https://alexn.org, https://monix.io, https://typelevel.org. 🌍 Bucharest, Romania https://alexn.org/about/

1.2K followers187 following884 posts

Nice, features the "numa numa" song. BTW, that popular song is in Romanian and its lyrics say "you want to leave, you won’t take me with you."

Firefox@firefox.com

Since 2004, this community has helped make Firefox and the open internet possible. Our “Come Back to Firefox” campaign reunites a few early internet icons to remind people what made the internet special, and why it’s worth protecting.

Alexandru Nedelcu reposted

Since 2004, this community has helped make Firefox and the open internet possible. Our “Come Back to Firefox” campaign reunites a few early internet icons to remind people what made the internet special, and why it’s worth protecting.

#DeepSeek v4.1 Flash is an excellent worker, but it's benchmaxxed, and in agentic work it's inferior to GLM-5.3 or GPT-6.1 Sol. It has the glaring problem that it's not following its prompt, making it a terrible orchestrator. For me this casts doubt on all benchmarks I've seen.

IME this ability to follow instructions and understand nuance is best for GPT models. Even Opus 5.5 has had some issues in my tests, consistently ignoring a rule like “don't micromanage your sub-agents; when delegating, state the job, not the commands to execute.”

#AI is so bad at ... writing plain text (READMEs, ADRs, code/configuration comments, etc.) that I'm having issues trusting them with anything else. Like really bad, I don't understand how people put up with it.

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You have carefully structured Markdown files with rules? Telling the #AI to add another rule will make it take a dumb at the beginning of the file, treating that rule as the most important in the world; or it will place it in the wrong section, guaranteeing confusion.

Also, #AI writes sentences like when Joey from Friends discovered the Thesaurus. Sounds smart but it's confusing gibberish. Telling it that you don't understand what in the world it's talking about often does the trick, but this assumes we can still read.

#AI is so bad at ... writing plain text (READMEs, ADRs, code/configuration comments, etc.) that I'm having issues trusting them with anything else. Like really bad, I don't understand how people put up with it.

#AI will crap slop all over your carefully crafted README, either thinking that its current task is the most important in the world, hence it needs a mention on your project's homepage, or it will think the README is there for keeping a captain's log.

This follows other significant changes, such as delayed AOSP releases, included for security fixes, closing down of Pixel devices (preventing GrapheneOS releases), and moving of Android development behind closed doors. Well, if I'm forced to use a proprietary brick, I may choose an iOS device next.

All those security vulnerabilities, now discovered by #AI, have been exploited by state actors and organized crime syndicates for years. "Sunlight is the best disinfectant", don't blame AI for shedding light on existing vulnerabilities in both software and maintenance practices.

Complaints about solving simple algorithms in interviews for software engineering jobs are evergreen. Algorithms test your logic and communication skills. Software engineers are expected to solve problems that are easy enough for high schoolers to solve 😉

As we age, we lose some of those brain muscles. Forgetfulness can be a feature only as long as it happens by accumulating more important knowledge & skills. We do need to fight against brain rot; beware complacency. So, yes, “coding” in interviews will remain relevant.

What if "you being the bottleneck" is actually the recipe for creating good software that's actually used? You all had a full year of agent-driven development, so what do you have to show for it, other than personal utilities that nobody else will touch?

Most of you are still polishing your harness instead of building apps, but to be fair, I do that too. Turns out having ideas, ambitions or the knowledge to build something actually usable and maintainable is still hard.

Keep in mind that most “thought leaders” on social media that are touting the virtues of ignorance in AI-driven software engineering are engaging in wishful thinking.

Microsoft's #Copilot coding agent sucks, as it has a silly system prompt that's required and you can't override it. Screenshot shows 3 injected rules preventing efficient delegation. Note agent has no idea how many tool calls it will use, or it would make a script / 1 tool call.

I wouldn't care for Copilot, but this being Microsoft, it's getting forced on people in many orgs, and I have no mercy for closed-source software built by US monopolies.

Alexandru Nedelcu reposted

This is huge. With AOT, AHS, and the runtime changes coming in 28, it’s going to be a stellar release. Most people don’t realize how amazing the JVM is, and it just keeps getting better - github.com/openjdk/jdk/... #java #jvm

github.com8380289: Implement JEP 545: Faster Startup and Warmup with ZGC & JEP 546: Adaptive Heap Sizing for ZGC by fisk · Pull Request #33243 · openjdk/jdkThis PR is the implementation of two JEPs relating to ZGC adaptive heap sizing (AHS). The first one is JEP 546 (cf. https://openjdk.org/jeps/546): Enhance the Z Garbage Collector to adaptively adju...
Erik Österlund@eosterlund.bsky.social

Happy to announce that JEP 546: “Adaptive Heap Sizing for ZGC” and JEP 545: “Faster Startup and Warmup with ZGC” have both been targeted for JDK 28.

Agent harnesses (e.g. #OpenCode) show us how many apps will look like in the future: plugin-based, you ask for features you want, and it auto-refreshes w/ new feature. JS/JVM runtimes are great for this, compilers producing "native binaries", less so 😉 github.com/alexandru/...

github.comGitHub - alexandru/opencode-session-todo: Reimplements the agent's todo tooling for OpenCode v2Reimplements the agent's todo tooling for OpenCode v2 - alexandru/opencode-session-todo

I don't believe that AI will be worse for human cognition than social media. For one, you end up creating instead of mindlessly consuming short-form pre-digested content. Making builders out of people sure sounds more fun & productive. Also, my own learning has accelerated.

There will be negative consequences, of course, like with all software we've ever built. For example, people relying on their GPS app no longer learn to read maps or to navigate their city without GPS apps. OTOH, travelling being a skill, it prevented many from exploration.

In other words, while learning to go from A to B on a map was a valuable skill, with nice side-effects like getting lost in nice neighbourhoods ... it prevented many people from actually getting to B and learning what's there. Truth is, we have no idea where all this is heading.

I couldn't care less about how good #Anthropic's models are for the next 5 minutes. I care about: ✔️ Openness/portability (same thing); ✔️ Not supporting a US Big Tech wannabe that's actually a religious sect, with its priesthood hell-bent on imposing the cult of AI, literally.

When you hear about a 10x difference in throughput b/w a #Rust port versus a battle-hardened GC-managed runtime (#JVM, #dotNET, #Go), it can only be an apples vs oranges comparisson. Whether it's avoiding work via caching or algorithmic complexity...

It really pays off to know some computer science, to look at what the clanker is doing, and to approach the vast complexity of software with some humility. At the very least, it avoids embarassment, and it opens the door to improvements in software and wetware.

A shared idea these days is that SOTA models improve faster than you can improve your custom harness setup, so there's no point in having a custom harness. This misses the point. (1) Correcting an agent's behavior remains relevant for cheaper models, which make better loops.

(2) Making an agent follow YOUR engineering practices, making it align its behavior to YOUR way of doing things, will never get old, and it is the path to YOUR happiness and success, no matter how good the SOTA models get. (3) Models can't keep getting smarter forever. #AI #LLM

Unix philosophy: - Write programs that do one thing and do it well. - Write programs to work together. - Write programs to handle text streams, because that is a universal interface. Half a century old and more relevant than ever; your AI agents can work b/c of it.

“You don’t need mathematics to be an excellent software engineer” Yes, you do. This is like the hypothetical “Blub programmer” not knowing what they're missing. The good news is we can learn, on the job even, but not if we don't recognize our blind spots.

“The hate on Go is stupid” No it isn't. It's fine to hate tools. We build on our intuition, intuition is experience, intuition is good. Ofc, expertise requires opinions that are context dependent. E.g., I understand why some people like Go for their projects. But hating it is fine, healthy even.

Maybe the next programming languages being invented won't ignore the last 30 years of research, just saying 🤷‍♂️ Also, normalize feelings, it's what makes us human 😉

My son is in high-school. I keep telling him that to be a good software engineer, he needs 2 abilities: - Reasoning (math, obviously) - To read and write prose; to express his ideas and thoughts with words, efficiently. This has always been true, and will remain so.

Mathematics is somewhat obvious, but he's always shocked when I insist that he needs to read lots of books, and he needs to write, fiction even, in order to be good at building software 😀 Thankfully, he's quite good at writing already 🥰

When working on personal projects, it's a good idea to be frugal, to have a sustainable setup. Best "offers" right now are these: ‣ OpenCode Go ($10-$20) for $60-$120 worth of access to DeepSeek v4.1 Flash ‣ Mistral Pro ($15) for €255 worth of access to GLM-5.3

It's important to be able to live w/ chosen LLMs at API prices. I also have a ChatGPT Plus ($20) subscription, but I'm close to unsubscribing, as it's designed to upsell you on Pro ($100 or $200), and GPT-6 Astra or even GPT-6.1 Sol are not sustainable at API prices.

It's also important to optimize your workflow and to configure your harness to be token-efficient. When the bubble will burst, you'll be glad that you sought ways to be more token-efficient, which will include honing your programming skills & doing some automation w/o AI.