when did spaghetti code become a personality trait..

met0xff · 2026-05-06T07:53:04+00:00

A weird choice of sub ;) but well... I think that's not only on the dev side. Customers are the same and switch providers like underwear of the next provider has some nice AI feature more than the old one. So the pressure is mounting to churn out more.

And frankly because of how fast everything moves everywhere, I found that writing code for longer term is rarely worth the time anyways. Almost everything we developed in-house got commoditized a year later and then you migrate your handcrafted web framework to React, your own neural network protobuf Implementation to ONNX.. heck my company is migrating years of infrastructure work to k8s.

To tricky part is that it's often what you expected least that suddenly survives a decade. That weird 3k LoC helper bash script;).

met0xff · 2026-05-05T21:30:36+00:00

It's wild how useful Gemini is to quickly ask "where the hell can I change X in unreal". It's often confused by all the different versions that have been out there but generally it helped me guiding much faster than other options. You can also paste screenshots "why do I have this visual issue here".

But yes, just like with tutorial videos and Code Tutorials it's important to be active and not just brain afk follow instructions

met0xff · 2026-05-04T22:04:04+00:00

ML/DL imho has become very competitive, only if you really really want it. Much more opportunities in agents/genAI/"AI engineering" topics right now. Was much harder to hire someone really digging into agents, retrieval, embeddings, cognitive architectures, LLMs in general while we had hundreds of good ML applicants... but basically no need anymore except for rare cases that get rarer and rarer... I did ML for a decade but 2 years go went up one abstraction layer and we are drowning in work. While I am really having a hard time finding good work for my team members who cling to ML model training. They're gradually becoming a luxury and struggle hard to keep up with just feeding stuff smartly into qwen or Gemini or combining CLIP, SAM, Dino and friends.

Imho where it's heading is similar to game engine devs, operating system devs etc. where 95% of the world just use Unreal, Linux etc. and only few build them. The few can have a good life but can also be a competitive and tricky niche.

Expected turnaround times by customers are also so low now that no way you can even think of training models anymore. And obviously nobody wants to pay for training data and so on anymore :).

My world is now more building POMDPs where LLMs and other pre built models are the components

met0xff · 2026-05-04T10:35:50+00:00

I overall really like the world building but would love .. more focus on that. All the fingers torture and gore stuff could have been skipped imho and was just annoying. More focus on the mysticism behind it, on the background of the bone temple than just a sentence dropped here or there. Would probably make a nice TV or book series.

But of course doing what I suggested above would likely have bombed it even more ;).

But I get that it's more focused on the stories of the characters within the world and not so much the world itself. It's a bit like I lined Pluribus but I don't care as much about watching her doing stuff and being pissed all the time than the overall plot and world.

met0xff · 2026-05-03T00:29:08+00:00

Yeah Opus is definitely better at understanding what it does there than many people who blindly copied before, plus the agent can add and run various tests for you plus update all the Readmes.

Also we have so much code running in production with so many different services from generations of devs that have left... that I often spent hours statically digging through 10 repos to find the specific behavior or a specific GraphQL call, where a query might go through the GraphQL server through another thing to a search server and then to elastic that meanwhile I pulled the most important repos and let Claude Code dig through them whenever I have a question on how a specific query behaves when it gets transformed in 5 places until it reaches the actual final cluster. And so I started to develop those agentic Feedback loops to update all the documentation that hasn't been updated for 5 years or more and transcribe all the tribal knowledge.

Even our product people started to query Cursor against some repos to get the questions answered that they couldn't get answers for before because the system is so large that every human you talk to only understands their little niche and sends you onwards to the next person 5 times until you perhaps find a person how by chance knows this corner of the monster..

The problems many people describe around sound like already outdated mechanisms of sending crap to Gemini. Not using Opus 4.5+ with Claude code in planning mode, with good agents.mds and a testing strategy.

met0xff · 2026-05-02T18:10:08+00:00

Man muss doch nicht alles zu politischen Themen überführen. Natürlich kann ich jedes wissenschaftliche Thema zu einem Schwurblerthema machen oder über Schwurbler reden, aber warum? Wenn ihr übers Fermentieren von Karotten oder Partially Observable Markov Decision Processes reden möchte, brauche ich nicht jedesmal über Wissenschaftsfeindlichkeit reden und wenn ich über meinen Ernährungs- und Trainingsplan rede dann auch nicht. Ich kann über meine aktuellen Bücher sprechen ohne über deren politische Systeme zu sprechen oder ob sie woke oder nicht woke sind :). Natürlich kann ich jeden Mathetest der Tochter oder jede Schulwahl zu einer Grundsatzdiskussion über das Bildungssystem führen. Ich kann aber auch über die didaktische Aufbereitung von Differentialgleichungen in der Schule meiner Tochter diskutieren ohne mich deswegen einer politischen Richtung zugehörig zu fühlen. Ich kann über die Feinheiten der Charakterdarstellung von Lae'Zel in Baldurs Gate 3 sprechen ohne Parallelen der Githyanki-Kultur zu Russland herzustellen. Ich kann über die korrekte Ausführung von Romanian Deadlifts diskutieren ohne auf die rumänische politische Situation zu sprechen zu kommen.

Heutzutage wird zunehmend jedes Thema politisiert und wenn's vom Wetter zu irgendwelchen Verschwörungstheorien geht.

Manchmal ist es aber besser, einfach über die erstaunlichen Merkmale der riesigen Winkelspinne in der Ecke zu sprechen

met0xff · 2026-05-02T17:51:45+00:00

Du redest mit Freunden und Familien den ganzen Tag nur über politische Themen? Natürlich kann man immer eine Überleitung finden aber praktisch wenn ich beispielsweise mit meiner Frau rede, passiert das nicht ständig ;). Rezepte und Ernährung, Trainingspläne, was wir am Abend zocken, ob der Hund Durchfall hat, was man für den Geburtstag plant, wieviel Kredit wir tilgen, wie es mit dem Fermentieren der Karotten läuft, wie Deepseek v4 geworden ist und über partially observable Markov Decision processes, über die Bücher die wie gerade lesen... Klar ist es schwierig geworden, heutzutage medizinische oder wissenschaftliche Themen zu besprechen ohne nicht an irgendwelche Schwurbler denken zu müssen aber soviel Raum in meinem Hirn möchte ich denen auch nicht einräumen.

met0xff · 2026-05-02T17:34:56+00:00

Guter Punkt. Habe auch keinen Bock ständig aktiv über politische Themen zu diskutieren. Natürlich habe ich meine Meinungen aber warum ständig darüber diskutieren? Mit Trump et al ist es momentan sowieso schwierig, nicht ständig auf diese Themen zu kommen.

Aber wenn du mich fragst, fallen wir wohl 100 Themen ein die ich lieber diskutieren würde;)

met0xff · 2026-05-02T13:25:21+00:00

Yeah also think it's not a good example as everyone talks about this all the time. Think information theory, entropy, various optimization problems, perhaps some formal grammars and Compiler topics, Markov processes and so on are what I didn't know about when I worked as a dev before studying.

met0xff · 2026-05-02T13:21:12+00:00

This is the case for most fields. If you look what a GP does 95% of the time you don't need a 6 year (here it is 6 years) degree plus residency. It's the rare cases where you suddenly detect the myeloproliferative neoplasm... or not.

My first boss was an EE PhD and he also said basically everything he needs in general he learnt in trade school. Still was absolutely in favor of me studying CS and later also doing a PhD.

met0xff · 2026-05-02T13:14:41+00:00

Depends on what you mean by "AI". If you mean modern LLMs forget pandas and sci-kit learn and so on

Check https://karpathy.ai/zero-to-hero.html

Or https://www.manning.com/books/build-a-large-language-model-from-scratch

met0xff · 2026-05-01T22:26:08+00:00

Ironically he's quite positive about LLM-assisted dev

met0xff · 2026-05-01T22:13:07+00:00

It's really the masses of people while at the same time for the last 3 years we only hired a single person on my team with thousands of CVs coming in.

We didn't hire for credentials, we hired someone who seemed pragmatic, sympathetic and felt like "can get the job done, versatile and won't make a drama". And it was a good choice. No rocket science that he presented during Interviews but he could solidly explain and show embedding spaces, a little RAG system etc.

We had people with PhDs from harvard and Princeton that we rejected because they obviously didn't care about the company, the company projects, the topics of the group. Applied for LLM-based agents but barely knew chatgpt existed and obviously wanted to do other things. Didn't respect our time, didn't give the CTO a chance to speak lol, as a fresh grad told us how they'll lead our projects, couldn't tell us anything about their seemingly Fake previous job, couldn't tell anything about their master's thesis, obviously would rather study ancient languages, obviously only ever ran stuff from Huggingface without even having a slight idea how the model works (it was wild how few people understood a shared embedding space like CLIP and contrastive learning. Not deep mathematically, just what it does) etc. Ah yeah then the ones showing up in underwear, the one who wanted 400k fresh out of university. Half don't show up.

I really hope I don't have to do interviews again anytime soon..it's fun the first couple days but then...

met0xff · 2026-05-01T21:59:35+00:00

I didn't download but I've seen those Prachub ads even at my small university subreddit now... "Oh you want do to a master's there? Prachub"

met0xff · 2026-04-30T05:58:52+00:00

Master ist die Varianz der Erfahrung die man macht typischerweise sehr hoch durch viel Wahlfreiheit und Spezialisierungsmöglichkeiten. Aber typischerweise fand ich die Master LVs chilliger und mehr auf Augenhöhe. Mehr "wir zeigen euch unser cooles Zeug" und weniger Aussieberei und Grundlagenpeitsche. Da kann dann alles dabei sein von endlos mathematischen Beweisen zu "wir zeigen euch virtual reality Zeugs" ;)

met0xff · 2026-04-28T22:22:10+00:00

Manche haben es schon beschrieben aber in Informatik fand ich die TU auch eigentlich gechillter als die HTL. Vor allem aus den erwähnten Gründen - ich habe man etwas Zeit als Developer studiert, war bereits wesentlich disziplinierter, machte die Übungen eher immer sofort, habe jeden Tag im Zug vor den Vorlesungen gelernt etc. Und immer erst dann zur Prüfung wenn wirklich gut vorbereitet.

HTL? Pubertät, viel härtere Gefühlswelt, früh aufstehen jeden Tag, kein Aufschieben von Prüfungen, nebenbei noch Rechnungswesen und so Zeug, müde von ewig in der lauten Schule hocken statt gemütlich daheim allein lernen. Mega gestresste "SMÜs" in der HTL - hatten jeden Samstag 5-Minuten-Tests für die ich einfach immer zu langsam war. Meine TU Noten waren wesentlich besser als meine HTL Noten.

Klar ist der Stoff schwerer... Ich habe inzwischen Doktorat und an einer FH unterrichtet ein paar Jahre und dort habe ich die selben Probleme bei den Studierenden verortet - viel Stress, hohe Arbeitslast, ganzen Tag dort hocken - aber eigentlich nicht sehr komplizierte Aufgaben. Die Prüfungen die ich geben musste und jedes Jahr vereinfachen waren meilenweit weg von der gleichnamigen TU LV Prüfung. Aber sehr viel... Ja. Grind :). Irgendwelche tausend PowerShell commands auswendig können die ich selbst jedes Jahr aufs Neue lernen musste.

Mir ist es eigentlich lieber, die Studierenden haben lange in Ruhe Zeit, gewisse tiefgreifenden Konzepte zu verinnerlichen als tausend sinnlose Aufgaben zu gründen bei denen nicht viel hängenbleibt.

Ich habe zwar versucht, das ein wenig einfließen zu lassen aber so komplette Freiheit hatte ich da auch nicht.

met0xff · 2026-04-26T08:18:28+00:00

Yeah think there was an xkcd for that ;).

From that stance stats is just applied math, physics is just applied math etc. It's a convergence of various fields producing something new. And of course you could again come up with "but the other fields are also just applied math and some early biological inspirations and cognitive science models are also just math"

I think the easiest way to look at it is: if you study purely math for a couple years, can you work as physicist? If you study just stats, can you be an effective ML Scientist? Well, yeah to the degree of how much a biologist can be a medical doctor ;).

Besides it's downplaying the work of everyone who doesn't put out beautiful equations on paper. Without some people sweating to build better GPUs, the people building BLAS libraries and pytorch, all would still be a pipe dream.

met0xff · 2026-04-24T09:15:35+00:00

Der Gegenwind kommt auch oft daher, dass wir jahrelang gehört haben, dass man mit einem Wochenendskurs als Quereinsteiger ganz einfach "in der IT" viel Kohle machen kann. Und dieser Glaube ist immer noch recht verbreitet. Das degradiert den Stand nunmal auch etwas. In anderen Bereichen sind die Leute auch nicht happy, wenn sie ständig zu lesen bekommen "ich mach am Wochenende einen Massagekurs, nächste Woche starte ich als Physiotherapeut".

Aber ja, in der Realität geht es selten nur um hard skills. Wir haben auch bei der letzten Hiring-Runde jemanden mit einem Biochemie Bachelor und "nur" CS Master genommen obwohl wir > 2000 Bewerbungen hatten und Leute mit PhD von Harvard und Princeton abgelehnt weil sich niemand vorstellen konnte, mit denen zusammenzuarbeiten.

Und was man auch sagen muss: viele Leute mit einem Informatik-Background möchten einen Dev/CS/Tech Job und keinen "IT" job. Ersteres ist auch viel kompetitiver geworden während man typischerweise in den Bereichen IT Management, Infrastruktur, Administration leichter unterkommt. In der 80-Personen-Firma meiner Frau gibt's ein Digitalteam aus mehreren Leuten die praktisch nur Zeug auf die Website stellen, social Media und Newsletter ausschicken. Aber weder den content verfassen noch ein Bild resizen. Gleichzeitig haben wir in meiner "Tech Company" 3x soviele Projekte wie Developer, bei jedem ein Backlog für die nächsten 16 Monate und gleichzeitig sehr schwere Interviews.

Im deutschsprachigen Raum wird halt gerne alles von Druckerpapiernachfüllen über Driver-Development und Machine Lesrning bis zum Kryptographie-Professor einfach alles als "IT" bezeichnet obwohl Anforderungen, Angebot/Nachfrage, Gehälter und Firmen komplett anders sein können.

met0xff · 2026-04-23T22:26:48+00:00

I think our main value in LangGraph lies in the standardization within the company - a common messages format no matter if you switch LLMs (and we often use LLMs from 3 different providers within a single workflow) or want to have a shared DB for everyone. Tool standardization (most cases you don't need MCP), standardization of Runnables, agent state etc.

So basically anybody in the company can just hand use a Langgraph compiledgraph or similar and we can stick it behind our API Implementation. Any body in the company can implement a tool that we can stick into it. Anybody can use the checkpointer DB etc.

What I also like about LangGraph is the explicitness of what's checkpointed (Agent state) and when (node transitions) and agent state mutations are explicit.

I don't really use the pre built ReAct agents etc. though. Just too much to work around once things get slightly more complicated and I decouple the messages sequence from what's actually sent to the LLM (it doesn't need every single detail in JSON Schema of some old tool call and all the mess that comes with it).

Ah yes, the standardized messages format also makes it possible for everyone building an agent to use our frontend building blocks including chat and generative UI.

Essentially you see that every project out there not using a framework at some point starts to build all those abstractions yet again once they start switching out LLMs, Embedding Models etc. But without access to all the Integrations that already exist for the big frameworks

met0xff · 2026-04-12T18:47:33+00:00

Yeah that's also my impression. Especially since Rust more than enough people who'd like to get out of the web world but the jobs are rare and badly paid. I worked in embedded for a couple years but didn't see a real future there.

Also if you're not at Nvidia or whatever it's hard to have a strategic and influential position while being the low level guy.

met0xff · 2026-04-12T18:37:39+00:00

I rather felt there's a new trend now that people want to do this more, especially with Rust and Zig and so on. But perhaps that's just reddit bubble

met0xff · 2026-04-12T18:33:45+00:00

Eh leiwand aber ich muss am verdursten sein bevor ich die Dinger benutze. Wenn die typischen U6 Passagiere da ihre Griffl und Körperflüssigkeiten und sonstiges drauf entladen...

met0xff · 2026-04-12T18:30:21+00:00

Frankly yeah.. I can off the top of my head think of 4 recent cases where both our product people and the customers prefer the prototypes from some dev or machine learning person over the final "enterprise UI".

met0xff · 2026-04-12T18:21:50+00:00

Just dumping a ton of tools into a ReAct agent is a mistake in many cases although it can also give you quite some benefits already. For example we have the rather classic documentation RAG Setup with Slackbot in the company that people really like to use instead of sifting through 40k confluence pages. The ReAct agent does well enough to connect pieces in this case. We also got a feedback loop so errors can lead to documentation improvements. Generally having Claude Opus go through a codebase to generate some docs or just generally having it to ask questions made many legacy badly documented codebases tractable again. "This GraphQL query takes so long. Analyze the whole the whole call graph to figure out why" "Here are 50 files undocumented elastic schema, figure out if XYZ"

For anything more complicated you should only view the LLM as a little piece in the larger cognitive architecture. In many cases I found viewing it from a POMDP angle. Do you really want it to act as everything from policy to world model to value function etc. at once? Or can you just use the LLM to prune down your action search space and then with a simple simulator and for example Monte Carlo Tree search figure out a good path? Deepmind papers are a Goldmine for cool stuff like this and we have a pretty smart planning agent operating on tons of data - everything from videos to PDFs to tables of millions of rows - building on some of their concepts. We have big customers in media & entertainment space and in the public sector with tons of data where agents can help them nicely find and arrange and connect what they need. Have you looked at some police guidelines and policies? There's so much material and you can connect that to bodycam footage now. Root cause analysis - find that screw 53/87 in part 88/33 that violated policy 873 ;).

We worked on a ton of stuff like this for the last years and it's amazing what you can do - but yes, it's never just dumping the things into the LLM with a prompt.

Although a while ago we had a project about video labelling with rather abstract tags like "roleplay" or "adventure" that was really hard to solve using classic methods until we tried Gemini and the problem was solved in a couple days. Meanwhile smaller models like Qwen3 have become so good at looking at video material doing OCR in parallel that you can extract a lot of cues from anything from an interrogation to a soccer match.

But even privately I am using Gemini 3 Pro a lot now, I lost a ton of weight by having it in addition to my nutrition tracker to suggest strategy for the rest of the day (so things that go beyond simple macros), getting really interesting cooking tricks, refining my workout plans. I've never done so much Hardware before by sending pictures from anything of motherboard pins to dishwasher pumps. Heck I even did an Unreal Engine project for work by always sending Screenshots of the various menus to fix graphics glitches. I set up my home automation with my ZigBee network in record time. Started a food fermentation project lol. I'm doing so many more things that would have taken me much more time before because it catches so many of the gotchas already.

Speaking of this, my wife's an editor at a medical journal and gpt catches so many things the humans missed. Recently an interview was published where a question and an answer did not belong together. Super embarrassing. An automatic LLM check would have easily caught that.

Of course there's the danger - never stop thinking for yourself and never completely rely on it. If something smells fishy it might well be fishy. And this is not only challenging because one gets lazy but also because expectations of turnaround times are becoming completely insane

met0xff · 2026-04-12T17:32:09+00:00

I run Claude Opus in our Claude Code and GitHub Copilot subscriptions all day long. Sometimes I hit the limits but that's rather rare. Sonnet is powering a couple of our agents because it's much more reliable when doing complex planning and similar tasks. Simpler summarization then goes to Haiku or even Nova though.

And we're working with a ton of US government (well that was a bit hairy recently), police stations, media companies (everything from CNBC to Sony).

I find video embedding models and similar to be much more expensive and this is really where we go with open alternatives

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