I've made the decision to purchase a new M5 Macbook Air because of the memorypocalypse. My current M1 model is already upgraded to the amount of memory and storage as the current base model and I'm wondering if it's worth spending the extra 2-4 hundred dollars on memory upgrades today.

My current computer is more than good enough for today but I figure I should probably future proof just in case. I was thinking the 16GB would be enough, but I also know that I'm kind of falling behind by not embracing AI coding agents. According to my research the maximum 32GB is recommended for most coding-relevant models - almost as a minimum.

I work in education so coding is not actually much of a need, and obviously there are cloud providers I could use if I end up needing them in the future. I also have less than a teacher's salary because I work part time, which is the greatest reason why I'm sticking with the 16GB base for the moment, but other than that I also don't do many memory-intensive programs. But I thought I would get some recommendations before they start shipping.

I'd also be interested on people's opinions on trading in my old one, since it'll only get me ~$275 back. I'm considering reneging on that part and keeping it around to act as a web server or give it to my husband who has a computer that still runs Windows 7 and barely uses it.

Eagleson's Law states

"Any code of your own that you haven't looked at for six or more months might as well have been written by someone else."

I keep reading how fewer and fewer of the brightest developers are writing code and letting their AI agent to do it all. How do they know what's really happening? Does it matter anymore?

Curious to hear this communities thoughts

I've grown increasingly unsure about if I'll stay with this profession long term thanks to the AI "revolution". Not because I think I'll be replaced, I have an extremely wide set of skills thanks to working over a decade in small startups so I think I'm safe for a long while to come.

No, I've grown weary because an increasingly larger share of the code that we produce is expected to be ai generated and with it shorter timelines and I just plain don't like it. I think we reached a tipping point around Claude opus 4.5 where it really is capable and that's only going to continue to get better. But damnit I like coding, I enjoy the problem solving and I feel that's getting stripped away from me basically overnight. Also, as these models become more and more capable I think the number of companies vibe coding to a product with fields of junior level engineers is going to grow which is going to push down senior job opportunities and wages.

So now I'm left wondering if it's time to start pointing towards a new career. I really love building stuff and solving problems so maybe I go back to school and switch to some other flavor of engineering? Idk. Curious where other's heads are at with this.

I've been thinking perhaps I'll need to get one of the desktop LLM UI. I've been out of touch with the state of the art of end user LLM as I've been exclusively using it via API, but tech-y people (who are not developers) mostly talk about the end-user products that I lack the knowledge of.

Ethical problems aside, the problem with non-API usage is, even if you pay, I can't find one that have better privacy policy than API. And the problem with API version is that it is not as good as the completed apps unless you want to reinvent the wheel. The apps also may include ads in the future, while API technically cannot as it would affect some downstream usecases.

As a dual use technology, the table doesn't include the extra retention period if they detect an abuse. Additionally, if you click on thumbs up/down it may also be recorded for the provider's employee to review.

I don't think OpenWebUI, self hosted models, etc. would suffice if they are not built to the same quality as the first party products. I know I'm probably asking for something that doesn't exists here, but at least I hope it will bring to people's attention that even if you're paying for the product you might not get the same privacy protection as API users.

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?

I asked Claude for references to some ideas the ai had output earlier about a 16th century cardinal (Sadoleto). It's response was, Let me analyze the letter, and then this:

async function searchForSadoletoLetter() {
  try {
    const files = ['sadoleto_letter.txt', 'sadoleto.txt', 'sadoleto_to_geneva.txt', 'letter_to_geneva.txt'];
    
    for (const filename of files) {
      try {
        const content = await window.fs.readFile(filename, { encoding: 'utf8' });
        console.log(`Found file: ${filename}`);
        console.log("First 500 characters:");
        console.log(content.substring(0, 500));
        return content;
      } catch (err) {
        // File not found, try the next one
      }
    }
    console.log("Could not find any files containing Sadoleto's letter");
    return null;
  } catch (err) {
    console.error("Error searching for files:", err);
    return null;
  }
}

const content = await searchForSadoletoLetter();

// Since we don't have the letter available as a file, let's search for published versions online
console.log("The letter isn't available as a file. We would need to rely on scholarly knowledge about Sadoleto's letter to Geneva (1539).");
console.log("Sadoleto's letter was published in 'A Reformation Debate: Sadoleto's Letter to the Genevans and Calvin's Reply' (ed. John C. Olin).");

This strikes me as odd? Did Claude write a script to generate its own response? Have coders put something like this in as a gaurdrail?

edit: details about earlier convo

I want something like typingmind but for free, and that doesn't require installation. mainly for gemini and mistral (or perhaps groq too) I just want to be able to paste my API key and just use it. I know about OpenWebUI and msty but OpenWebUI requires installation, and msty doesn't have an android version.

anyone know something like this ? (would also be nice if it supports LaTeX)

Apologies if this isn't an appropriate place to post this.

Inspired by a paper I found a while back (https://publications.lib.chalmers.se/records/fulltext/215545/local_215545.pdf), I tried my hand at implementing a program (in C#) to create ASCII art from an image. It works pretty well, but like they observed in the paper, it's pretty slow to compare every tile to 90-some glyphs. In the paper, they make a decision tree to replicate this process at a faster speed.

Recently, I revisited this. I thought I'd try making a neural net, since I found the idea interesting. I've watched some videos on neural nets, and refreshed myself on my linear algebra, and I think I've gotten pretty close. That said, I feel like there's something I'm missing (especially given the fact that the loss isn't really decreasing). I think my problem is specifically during backpropagation.

Here is a link to the TrainAsync method in GitHub: https://github.com/bendstein/ImageToASCII/blob/1c2e2260f5d4cfb45443fac8737566141f5eff6e/LibI2A/Converter/NNConverter.cs#L164C59-L164C69. The forward and backward propagation methods are below it.

If anyone can give me any feedback or advice on what I might be missing, I'd really appreciate it.