Hello Tildes!

There's an open-source app I would like to work on and contribute code to, but it uses a toolchain that I'm not terribly familiar with (Deno), and I'm not a huge fan of letting tools like this have full access to my system and files.

Do any of you use a system to containerize different development environments for software development? I could definitely use a standard Docker/Podman container to run the app, but I'm not aware of a good system where you can edit a program's source in an IDE, make changes, build the app, open a local port, and save your new code, all within a sandboxed environment.

If anyone uses a system like this or something related, I would love to hear about it and share ideas.

First, I am emphatically not talking about LLMs.

Just a shower thought kinda question. For most people, the primary issue is anthropomorphizing too much. But I think programmers see it differently.

Let's say someone comes up with something that seems to walk and talk like a self-aware, sentient, AGI duck. It has a "memories" db, it learns and adapts, it seems to understand cause and effect, actions and consequences, truth v falsehood, it passes Turing tests like they're tic-tac-toe, it recognizes itself in the mirror, yada.

But as a developer, you can "look behind the curtain" and see exactly how it works. (For argument's sake, let's say it's a FOSS duck, so you can actually look at the source code.)

Does it ever "feel" like a real, sentient being? Does it ever pass your litmus test?

For me, I think the answer is, "yes, eventually" ... but only looong after other people are having relationships with them, getting married, voting for them, etc.

Sometimes I feel like there's something wrong with how I use technology, or I'm just incredibly biased and predisposed to cynicism or something, so I wanted to get a pulse on how everyone else feels about AI, specifically LLMs, and how you use them in your professional and personal lives.

I've been messing with LLMs since GPT-3, being initially very impressed by the technology, to that view sort of evolving to a more nuanced one. I think they're very good at a specific thing and not great at anything else.

I feel like, increasingly, I'm becoming a rarity among tech people, especially executives. I run cybersecurity for a medium sized agency, and my boss is the CIO. Any time I, or any of her direct reports write a proposal, a policy, a report, or basically anything meant to distribute to a wide audience, they insist on us "running it through copilot", which to them, just means pasting the whole document into copilot chat, then taking the output.

It inevitably takes a document I worked hard on to balance tone, information, brevity, professional voice, and technical details and turns it into a bland, wordy mess. It's unusable crap that I then have to spend more time with to have it sound normal. My boss almost always comes up with "suggestions" or "ideas" that are very obviously just copy pasted answers from copilot chat too.

I see people online that talk about how LLMs have made them so much faster at development, but every time I've ever used it that field, it can toss together a quick prototype for something I likely could have googled, but there will frequently be little hidden bugs in the code. If I try to use the LLM to fix those bugs, it inevitably just makes it worse. Every time I've tried to use AI in a coding workflow, I spend less time thinking about the control flow of the software, and more time chasing down weird esoteric bugs. Overall it's never saved me any time at all.

I've used them as a quick web search, and while they do save me from having to trawl through a lot of the hellhole that is the modern internet, with blogspam, ads, and nonsense people write online, a lot of times, it will just hallucinate answers. I've noticed it's decent at providing me results when results exist, but if results don't exist, or I'm asking something that doesn't make sense, it falls flat on its face because it will just make things up in order to sound convincing and helpful.

I do see some niches where the stuff has been useful. Summarizing large swathes of documents, where the accuracy of that summary doesn't matter much is a little useful. Like if I were tasked to look through 300 documents and decide which ones were most relevant to a project, and I only had an hour to do it, I think that would be a task it would do well with. I can't review or even skim 300 documents in an hour, and even though an LLM would very likely be wrong about a lot of it, at least that's something.

The thing is, I don't frequently run into tasks where accuracy doesn't matter. I doubt most people do. Usually when someone asks for an answer to something, or you want to actually do something useful, the hidden assumption is that the output will be correct, and LLMs are just really bad at being correct.

The thing is, the internet is full of AI evangelists that talk about their AI stack made up of SaaS products I've never even heard of chained together. They talk about how insanely productive it's made them and how it's like being superhuman and without it they'd be left behind.

I'm 99% sure that most of this is influencer clickbait capitalizing on FOMO to keep the shared delusion of LLM's usefulness going, usually because they have stake in the game. They either run an AI startup, are involved in a company that profits off of AI being popular, they're an influencer that makes AI content, or they just have Nvidia in their stock portfolio like so much of us do.

Is there anyone out there that feels this technology is actually super useful that doesn't fall into one of those categories?

If so, let me know. Also, let me know what I'm doing wrong. Am I just a Luddite? A crotchety old man? Out of touch? I'm fine if I am, I just want to know once and for all.

Part of my role at work is in security policy & implementation. I can't figure this out so maybe someone will have some advice.

With the advent of AI coding, people who don't know how to code now start to use the AI to automate their work. This isn't new - previously they might use already other low code tools like Excel, UIPath, n8n, etc. but it still require learning the tools to use it. Now, anyone can "vibe coding" and get an output, which is fine for engineers who understand how the output should work and can design how it should be tested (edge cases, etc.)

I had a team come up with me that they managed to automate their work, which is good, but they did it with ChatGPT and the code works as they expected, but they doesn't fully understand how the code works and of course they're deploying this "to production" which means they're setting up an environment that supposed to be for internal tools, but use real customer data fed in from the production systems.

If you're an engineer, usually this violates a lot of policies - you should get the code peer reviewed by people who know what it does (incl. business context), the QA should test the code and think about edge cases and the best ways to test it and sign it off, the code should be developed & tested in non-production environment with fake data.

I can't think of a way non-engineers can do this - they cannot read code (and it get worse if you need two people in the same team to review each other) and if you're outsourcing it to AI, the AI company doesn't accept liability, nor you can retrain the AI from postmortems. The only way is to include lessons learned into the prompt, and I guess at some point it will become one long holy bible everyone has to paste into the limited context window. They are not trained to work on non-production data (if you ever try, usually they'll claim that the data doesn't match production - which I think because they aren't trained to design and test for edge cases). The only way to solve this directly is asking engineers to review them, but engineers aren't cheap and they're best doing something more important.

So far I think the best way to approach this problem is to think of it like Excel - the formulas are always safe to use - they don't send data to the internet, they don't create malware, etc. The worst think they can do is probably destroy that file or hangs your PC. And people don't know how to write VBA so they never do it. Now you have people copy pasting VBA code that they don't understand. The new AI workspace has to be done by building technical guardrails that the AI are limited to. I think it has to be done in some low-code tools that people using AI has to use (like say n8n). For example, blocks that do computation can be used, blocks that send data to the intranet/internet or run arbitrary code requires approval before use. And engineers can build safe blocks that can be used, such as sending messages to Slack that can only be used to send to corporate workspace only.

Does your work has adjusted policies for this AI epidemic? or other ideas that you wanted to share?

So, got a new job. That's great. Pay bump, more / new responsibilities and all that jazz. It took until my first day on the job for it to like, REALLY sink in that it's my first job managing people. I want to be good at this, or at the very least, competent. I'm responsible for my team and I don't want to let them down. I'm already looking things up online, talking to my parents, friends in similar positions for more information, and figured it would be good to ask around on here.

I guess the other half of this is that I've gone from looking at code in the IDE to now being more responsible for higher level architectural decisions. Possibly company steering decisions. Not used to that yet either, or at least the feeling. I feel under-prepared, and am possibly verging on overwhelmed. Lots of new things happening at once here, also writing this to unpack it as I type it out.

What advice do you have for me? Anything that you've learned while in a managerial role that you haven't gotten to share? Tips and Tricks? Prayers? 🤣

This is my cry for help.

I'm a newer programmer who just got hired for my first actual programming job a few months ago. Before now the only things I really made were simple python scripts that handled database operations at my last job. I live in an area with no opportunities, and so this new job I got is my saving grace at this point. For the first time in my life I can have actual savings and can actually work on moving to an area with opportunities. However...

Everything is falling apart. I have no idea how this place has survived this long. There is no senior dev for me to go to. There are no code reviews. There is no QA. There is a spiderweb of pipelines with zero error handling or data-checking. Bugs are frequent and go undetected. The database has no keys or constraints, and was designed by a madman (so it's definitely not normalized whatsoever). I already have made a bunch of little scripts handling data-parsing tasks that are used in prod, and I've had to learn proper logging and notifications on errors along the way, and have still yet to learn how to do real tests (I ordered a book on pytest that I plan on going through). I am so paranoid that at any moment something I made does something unexpected and destroys things (which... kinda actually happened already).

We're in the long and arduous process of moving away from this terrible system to a newer, better-designed one but I'm already just so lost and... lonely? There's a few separate dev "teams" but one is outsourced and the other is infamously unapproachable and works on a completely different domain. There's no one there to catch me if/when I make mistakes except myself. The paranoia I have over my programs is really getting to me and already affecting my health.

I guess I just want advice on what I should do in this situation. Is this a normal first experience? I care deeply about making sure the things I make are good and functional but I also don't have the experience to forsee potential issues that may come up due to how I'm designing things. And how can I cope with the paranoia I'm feeling?

EDIT: It takes me a while to write responses, but I want everyone to know that I really appreciate all your advice and kind words. It does mean a lot to me! I'm doing my best to take in what everyone has said and am working on making the best of an atypical situation. I'm chronically hard on myself, but I'm gonna try to give myself a bit more grace here. Again, thanks so much for all the thoughtful replies from everyone. :)

Hello all, was inspired to fish for responses after seeing another user request resume feedback. Apologies if the background is on the longer side.

TLDR: Dropped out 10 years ago; have only a high school degree and university transfer credits. Conflicted between finishing my degree online while working full time, vs. specializing in a niche tech stack (Salesforce) via current employment. Looking for any input because I'm prone to decision paralysis.

Hey there! Back when the pandemic was in full swing, I stumbled upon a comment that shared a link to a website with a title quite like this post. I can't quite recall if I saw the comment on Reddit, the orange site, or even here. The site was quite basic, and claimed to have a list of jobs from companies that understood that its workers would like to have a life outside of work

The job market has changed a lot since the pandemic, but if any of you awesome folks happen to know where I can find a good part-time software development job, I'd be seriously grateful.

The vast majority of free and open source software available is well known for being clunky, having very unintuitive UI/UX and being very inaccessible to non-nerds.

We can see this in Linux distros, tools, programs and even fediverse sites.

I understand that a lot of it is because "it's free", but I also feel like a lot of people who make and use FOSS don't actually value user-friendliness at all. I feel like some of it is in order to gatekeep the less tech savvy out, and some of it is "it's good enough for me".

What are the best theories for why this is the case?

EDIT: A lot of replies I've been getting are focusing on the developers. I'm asking more why the users seem okay with it, rather than why the developers make it that way.

A common theme in web development, and the crux of the so-called "Web 2.0" is scrolling through dynamic lists of content. Tildes is such an example: you can scroll through about 50 topics on the front page before you reach a "next" button if you want to keep looking.

There's a certain beauty in the simplicity of the next/previous page. When done right it's fast, it's easy, and fits neatly into a server-side rendered model. However, it does cause that small bit of friction where you need to hit the next button to go forward -- taking you out of the "flow", so-to-speak. It's slick, but it could be slicker. Perhaps more importantly, it's an interesting problem to solve.

A step up from the next/previous button is to load the next page of content when you reach the end of the list, inserting it below. If the load is pretty fast, this will hardly interrupt your flow at all! The ever-so-popular reddit enhancement suite does precisely that for reddit: instead of a next button, when you reach the bottom, the next page of items simply plops into place. If the loading isn't fast enough, perhaps instead of loading when they reach the last item, you might choose to load when they hit the fifth from last item, etc.

To try to keep this post more concrete, and more helpful, here's how this type of pagination would work in practice, in typescript and using the Intersection Observer API but otherwise framework agnostic:

/**
 * Allows the user to scroll forever through the given list by calling the given loadMore()
 * function whenever the bottom element (by default) becomes visible. This assumes that
 * loadMore is the only thing that modifies the list, and that the list is done being modified
 * once the promise returned from loadMore resolves
 *
 * @param list The element which contains the individual items
 * @param loadMore A function which can be called to insert more items into the list. Can return
 *   a rejected promise to indicate that there are no more items to load
 * @param triggerLoadAt The index of the child in the list which triggers the load. Negative numbers
 *   are interpreted as offsets from the end of the list. 
 */
function handlePagination(list: Element, loadMore: () => Promise<void>, triggerLoadAt: number = -1) {
    manageIntersection();
    return;

    function handleIntersection(ele: Element, handler: () => void): () => void {
        let active = true;
        const observer = new IntersectionObserver((entries) => {
            if (active && entries[0].isIntersecting) {
                handler()
            }
        }, { root: null, threshold: 0.5 });
        observer.observe(ele);
        return () => {
            if (active) {
                active = false;
                observer.disconnect();
            }
        }
    }

    function manageIntersection() {
        const index = triggerLoadAt < 0 ? list.children.length + triggerLoadAt : triggerLoadAt;
        if (index < 0 || index >= list.children.length) {
            throw new Error(`index=${index} is not valid for a list of ${list.children.length} items`);
        }

        const child = list.children[index];
        const removeIntersectionHandler = handleIntersection(child, () => {
            removeIntersectionHandler();
            loadMore().then(() => {
                manageIntersection();
            }).catch((e) => {});
        });
    }
}

If you're sane, this probably suffices for you. However, there is still one problem: as you scroll,
the number of elements on the DOM get longer and longer. This means they necessarily take up
some amount of memory, and browsers probably have to do some amount of work to keep
track of them. Thus, in theory, if you were to scroll long enough, the page would get slower and
slower! How long "long enough" is would depend mostly on how complicated each item is: if each one
is a unique 20k element svg, it'll get slow pretty quickly.

The trick to avoid this, and to get a constant overhead, is that when adding new items below, remove the same number of items above! Of course, if the user scrolls back up they'll be expecting those items to be there, but no worries, the handlePagination from before works just as well for loading items before the first item.

However, this simple change is where a key problem arises: inserting elements below doesn't cause any layout shift, but inserting an item above ought to--right?

The answer is: it depends on the browser! Back in 2017 chrome realized that it's often convenient to be able to insert items into the dom above the viewport, and implemented scroll anchoring, which basically ensures that if you insert an item 50px tall above the viewport, then scroll 50px down so that there's no visual layout shift. Firefox followed suite in 2019, and edge got support in 2020. But alas, safari both on mac and ios does not support scroll anchoring (though they expressed interest in it since 2017)

Now, there's two responses to this:

• Surely Safari support is coming soon, they've posted on that bug as recently as April! Just use simpler pagination for now
• Pshhhh, just implement scroll anchoring ourself!

Of course, I've gone and done #2, and it almost perfectly works. Here's the idea:

• Right before loadMore, find the first item in the list which is inside the viewport. This is the item whose position we don't want to move. Use getBoundingClientRect to find it's top position.
• Perform the DOM manipulation as desired
• Use getBoundingClientRect again to find the new top of that item.
• Insert (or remove) the appropriate amount of blank space at the top of the list to offset the change in client rect (note that if there's scroll anchoring support in the browser this should always be zero, which means this effectively works as progressive enhancement)

Now, the function to do this is a tad too long for this post. I implemented it in React, however, and combined it with some stronger preloading object (we don't need all the items we've fetched from the API on the DOM, so we can use before, onTheDom, after lists to avoid getting a bunch of api requests just from scrolling down and up within the same small number of items).

What's interesting is that it still works perfectly on chrome even with scroll-anchoring disabled (via overflow-anchor: none), but on Safari there is still, sometimes, 1 frame where it renders the wrong scroll position before immediately adjusting. Because I implemented it in react, however, my current hypothesis is I have a mistake somewhere which causes the javascript to yield to the renderer before all the manipulations are done, and it only shows up on Safari because of the generally higher framerates there

If it's interesting to people, I could extract the infinite list component outside of this project: I certainly like it, and in my case I do expect people to want to quickly scroll through hundreds to thousands of items, so the lighter DOM feels worth it (though perhaps it wouldn't if I had known, when starting, how painful getting it to work on Safari would be!).

What do you think of this type of "true" infinite scrolling for web? Good thing, neutral thing, bad thing? Would you use it, if the component were available? Would you remove it, if you saw someone doing this? Are there other questions about how this was accomplished? Is this an appropriate post for Tildes?

Are you an “old timer” in the computer industry? I’m writing a story about the things programmers (and QA people) had to do to test their software. It’s meant to be a nostalgic piece that’ll remind people about old methods — for good or ill.

For example, there was a point where the only way to insert a breakpoint in the code was to insert “printfs” that said “I got to this place in the code!” And all testing was manual testing. Nothing was automated. If you wanted a bug tracking system, you built your own.

So tell me your stories. Tell me what you had to do to test software, way back when, and compare it to today. What tools did you use -- or build? Is there anything you miss? Anything that makes you especially glad that the past is past?

C’mon, you know you wanted a “remember when”!