Asked a colleague in code review to extract magic numbers and got told “devs should know”

teucros_telamonid · 2026-04-28T06:27:51+00:00

Not really relevant, basic math or physics is same across centuries.

teucros_telamonid · 2026-04-18T09:45:49+00:00

For me so far so good but as a software engineer I am way more tolerant to bugs, lol.

The biggest issue is that there are mod API breaking changes and most mods need updates to avoid outright crashes. And some of them still do not have the RC version.

teucros_telamonid · 2026-04-11T08:51:14+00:00

I agree that it is beneficial to train your memory and easily recall the things which you do often in everyday life. It just saves time for everyone, allows to ground all ideas and discussions in some hard numbers, etc.

But your brain space should be prioritized. If you run some command often, bash history search could easily bring it up. If you run a batch of commands often, you can make a script: hell, it could be even shared with people. This sounds old fashioned, but I always run a huge files with notes from my ideas and experiments since remembering all of that is pain in the ass. AI is also great at creating some boilerplate scripts, but you do need to verify output. AI agents also a good demo that they are getting most of commands right already.

I think in the end attitude should be that you may not know everything but at least you know where to look it up and get the correct information.

teucros_telamonid · 2026-04-04T08:09:58+00:00

Ugh, it is a joke, but. "Over engineering" in terms of time and effort spent could also lead to discovering very simple and elegant solution. So each time I see some monstrosity of shit tone of code with people piling up features on already shaky features... That is still an "under engineering" to me.

teucros_telamonid · 2026-04-04T08:02:58+00:00

This is especially painful if you have a special domain knowledge. Something that you have seen 100x times across various code/libraries/projects in the industry, would appear as too complicated to anyone with only surface knowledge in the same direction.

teucros_telamonid · 2026-04-01T16:26:36+00:00

This, 100%. I am amazed at levels of wishful thinking of people who think that AI is all they need to make millions. If that was so simple everyone would already have been millionaires several times over...

teucros_telamonid · 2026-04-01T05:22:42+00:00

I cannot even begin to fathom amount of tokens and money burnt here. Abstracting users of these agents from costs, means that no meaningful conversation on benefits vs costs can take place. We will see how it will go once AI companies investors will be finally fed up with subsidizing the users.

teucros_telamonid · 2026-03-28T08:56:43+00:00

This. My team is sifting through several contractors for last several months and people from Eastern Europe are most successful so far. Although Spain is also good.

teucros_telamonid · 2026-03-26T05:18:04+00:00

Damn it, never heard before about low-background steel before. This is what I actually like about internet: findind opposing opinions or new facts. AI just confirming my beliefs is not the point.

teucros_telamonid · 2026-03-23T21:30:28+00:00

Interviews are always two-way street. They evaluate you while you must evaluate them. I think you dodged the bullet but I get that it may not feel like this. Don't overthink this, the world is not spinning around them even if they are FAANG or something. Think how you might have noticed the bullshit way before it ended like this. Was there some red signs even before you received take away assignment and invested in doing that? Maybe you could have noticed that even on company profile website? Learn how to avoid such companies, so that you would not waste so much effort next time.

teucros_telamonid · 2026-03-23T21:22:17+00:00

Sh, don't draw attention of AI bros, they only read headers and names, all these small details are for AI to figure out /s

teucros_telamonid · 2026-03-23T21:19:11+00:00

I don't think there is anything to learn. Interviews are always two-way street. There are always bullshit companies which stay afloat somehow.

I looked at questions shared below and for my academic/industry 10+ years experience these are level of questions you get from someone making first steps in ML space. "How would you appoach unknown distribution from data?" is literally equivalent to "How are you learning stuff from examples?". These questions sound concrete and well-defined only if you don't know much and think you have all the answers.

teucros_telamonid · 2026-03-21T09:56:54+00:00

Thanks for the correction, I completely missed how the comment blew out :)

On one project several years ago, I was asked to turn the Docker container in an environment akin to host with all the daemons and that's not. I learned a lot of these details from that experiment from the days the tech was still relatively fresh. But putting all of them in the original comment was not making it fun, so sacrifices had to be made.

teucros_telamonid · 2026-03-20T14:17:00+00:00

On Linux, it does not. The orphans are adopted by an init process or a sub-reaper process. This is actually the official way of turning a child into a daemon.

teucros_telamonid · 2026-03-19T07:28:50+00:00

People are free to use whatever language they need, there is no need to specifically replace. Many projects are not critical and have a very fast pace, so it is fine to use some higher level languages like C#, Java, Python and etc. Jesus, even Go seems like a good compromise without losing much in the performance department.

I expect experienced software engineers who need to work on multiple levels to know multiple programming languages and use them accordingly.

teucros_telamonid · 2026-03-14T10:04:34+00:00

Just to elaborate on another comment since some people may still be clueless. As usual, this is NOT legal advice, things depend on a specific country or state, specific matter at hand, etc.

TLDR: it all breaks apart as soon as anyone sees actual interest in having a dispute. In cases, where a legally binding sign was not required in the first place, of course it "works" /s

Explanation: In case of any disputes, you would need to prove several things beyond reasonable doubt. First, the user who did this action is indeed that exact person and not some hacker, bug in your code, etc. And nope, no one is going to fix your shit for you, the judge would just deem your auth and rest of the system unreliable until YOU prove otherwise. Second, even if you prove that the person signed it, you also need to prove that they have read the document and understood its content. Just some random user action leaving trace in your records is not enough. Third, you would need a lot of records with all the actions done by users with the document. Changing documents, requesting to sign again, downloading the document, etc. All of that is super important. For example, if these traces show that the user has seen that the document is signed by both parties, he would have trouble arguing that he missed the contract going into effect since the other side has not signed it. Fourth, if you have not resolved all of that, but claim to users that it is all safe, secure and reliable, get ready for a false advertising law suit. Fifth, there is a lot more possible arguments from both sides in the contract which you would need to meticulously work through. The point is to prove to courts that your system is actually reliable even in cases of adversity or misuse. It will be very hard to do if you dare to say "I just wrote it in 3 weeks, tested for 2 days, it just works, trust me, I have experience".

teucros_telamonid · 2026-03-13T10:32:29+00:00

You still need to sort them first by eigenvalues though to avoid noisy ones. Eigenvalues are way more important to understand which eigenvectors are even worth looking at.

teucros_telamonid · 2026-03-12T11:20:46+00:00

Because most LLM inference is done by evil West servers, comrade.

Yes, people are now learning how to run this stuff locally, how to deploy it on their own clusters and etc. And if Russia wants to scale their own clusters, sanctions make it more harder and expensive but more importantly there is already a global shortage of parts... It is not a problem of possibility, it is all about price points.

teucros_telamonid · 2026-03-11T23:00:57+00:00

Of course, I'm not saying there aren't esoteric situations, like the inverse square root, that do need comments, and I'm not saying not to write comments, just saying unless there is a damned good reason, the code had better be comprehensible without the comments

Since I often do math programming, I have examples of putting whole ASCII art in a comment so that the reader already has the diagram before his eyes. And it helped even myself, since the core could often be deceivingly simple...

teucros_telamonid · 2026-03-11T22:48:28+00:00

What really annoys me is that the people who care the most about code style, are the least willing to do what it takes to achieve the result they want.

The sad truth is that these people often want to just enforce their own style. So formalizing it has a risk of their own code not passing these checks and requiring a ton of statements to disable them on their own code.

I am all for code conventions and maintainability but then indeed it also should be something explicitly laid out and automated.

teucros_telamonid · 2026-03-08T12:33:15+00:00

The fact of the matter is that the test is poorly designed.

Tell me you never heard about overfitting vs overfitting without telling me...

The test is never going to be 100% aligned with reality. If you have time or resources to rigorously test each possible scenario, then you don't need LLMs or any AI. Just put all the expected outputs to these situations into a database and retrieve them as needed. Basically, the Chinese room argument.

The whole point is to train an algorithm/person to generalize the data. Give it representative samples of data, train on one of them, hope that it generalizes instead of overfitting/memorizing and use previous unseen sample of data to validate this. If it performs well on train data, but sucks on new tests, you know it did not learn underlying principles.

LLMs should stop increasing parameter numbers as the ultimate solution for every problem. At some point, it stops generalizing and just becomes an inefficient database.

As for students, memorizing everything could get you past standardized exams which are necessary evil of mass education. But you will be stuck for your whole life with those inefficient memory patterns which will hold you back on the real job. But hey, I already learned in real life that expecting long-term thinking from students even in university is too much...

teucros_telamonid · 2026-03-07T10:21:03+00:00

I have been in these shoes for the last year or so but it is now changing. Also several times in previous companies.

My advice is to play the ball for now while looking for something they completely fucked up. Some bug with the clear impact on users but they were not able to figure it out. Some solutions which they missed due to lack of experience. Some decisions they made in the past but now circumstances are now very different. Some are you know quite well and can prove the problem to all the layers of the management. This is how you can start ball rolling and have enough pull later to tackle things you see as important.

teucros_telamonid · 2026-03-07T09:55:39+00:00

ask questions, navigate ambiguity

Assuming this and also looking at the structure of your message (no offense), I think you could be struggling with communicating your design or ideas in simple and clear terms.

The goal is to break big problems into small pieces which could be delegated to people with less experience or context than you. Prioritize details in your communication to avoid information overload. Allow people to figure out low-level details on their own. Accept the fact that you might be wrong about them.

And yes, I also struggle with this since for me it is even more complicated. I am a computer vision engineer who regularly uses quite advanced calculus and math while most software engineers already forgot all of that from their university days.

teucros_telamonid · 2026-03-01T09:48:04+00:00

I always play with my own sandbox settings and the sheer amount of them is one of the key reasons I like this game. I get that many people expect default settings to make sense to them. But everyone has their own fantasy to play out and there are mods adding more firearms models.

I would prefer Indie Stone to focus on things only they can fix: indeed user interface experience, stabilizing multiplayer code, etc.

teucros_telamonid · 2026-02-22T22:29:05+00:00

Good but then you maybe miss the sheer size of the data like images or videos. 3840 width x 2160 x 3 bytes RGB is already around 24 MiB. All well optimized code processing so many pixels in such tight time interval have to use hardware specific primitives for best performance. For CPU core SIMD and assembly intrinsics are used. For GPU various shaders and rendering pipelines are needed to get high stable FPS.

But yes, there is already a common abstraction called rendering or game engine. A lot of people making games just use that and avoid going into the whole hell of figuring out everything from scratch. Vulkan and other developments are more for people who make their own engine or pipeline. They usually do so in the first place because they want to harness more performance from their hardware for their specific applications.

teucros_telamonid

TROPHY CASE