lysdexic
@lysdexic@programming.dev
- Comment on How is funding? 1 year ago:
$1500/year sounds an awful lot for a site that barely receives any updates even from the public.
What efforts are being developed to lower operational costs?
- Comment on Programming.dev instance: Sponsors needed 1 year ago:
The whole idea to check the donations came from stumbling upon this post which discussed costs per user.
Things should be put into perspective. The cost per user is actually the fixed monthly cost of operating an instance divided by the average number of active users.
In the discussion you linked to, there’s a post on how Lemmy.ml costs $80/month + domain name to serve ~2.4k users. If we went through opex/users metric, needlessly expensive setups with low participation would be a justification to ask for more donations.
Regardless, this is a good reminder that anyone can self-host their own Lemmy instance. Some Lemmy self-host posts go as far as to claim a Lemmy instance can be run on a $5/month virtual private server from the likes of scaleway.
- Comment on Programming.dev instance: Sponsors needed 1 year ago:
Is there something else I’m not seeing?
Possibly payment processing fees. Some banks/payment institutions charge you for a payment.
- Comment on Is GitHub Copilot worth it to you? 1 year ago:
I often felt that current ML speeds up newbie devs by effectively teaching them the language and libraries — but slows down experts that already know the stack well from memory.
It depends. You don’t need LLMs to write stuff for you that you already know. You use them to take.care of the drudge work or explore things you are not familiar with. Things like Copilot’s /explain can speed up onboarding even for seasoned developers, and Copilot can also help you speed up iterations on proofs of concept. For example, I’ve been using Copilot to experiment with some changes to the software architecture of some projects I own, and it’s fantastic at generating code following specific design patterns. It’s also fantastic to get it to iterate designs in near-real.time by prompting it with directives such as “repeat the last example but implementing X with design pattern Y and moving the implementation to Z”. You are presented with examples that you can browse through and get a taste of what you’d get, but with a fraction of the time. To top things off, you can prompt Copilot to present pros and cons and even propose optimizations.
Like any tool, it has its purposes. You just need to learn how to use it.
- Comment on Is GitHub Copilot worth it to you? 1 year ago:
I don’t use chat, it’s usually useless.
I think Chat is the most useful feature of Copilot. Prompts like /docs work impeccably, but /explain and /optimize is also pretty good. /tests is hit-and-miss if you have zero tests and require too much context if you already have them. More often than not /fix is a waste of time.
Where I found Copilot to be quite useful is something unexpected: naming things. You can prompt it to give suggestions, you can ask it to refactor things for you. Quite nice.
I think that Claude is far better at generating code, and explore new stuff, but Claude is also down and broken extremely often,not to mention it’s annoying limit of 10 questions per half a day.
- Comment on Is GitHub Copilot worth it to you? 1 year ago:
I use chat the most. It’s pretty good once you understand the importance of building context, set up personas, and feed it workable prompts. The biggest mistake I see people do is presume that you can expect it to output gold when inputting garbage.
Once you build up an understanding of what personas work for your personal tastes and what context you need to have, it can output impressive results. The most success I’ve been having is with somewhat complex refactorizations. Stuff like “refactor X so that Y and Y” can save you a lot of time.
The most disappointing experience has been with writing unit tests. copilot has this infuriating tendency to remove old tests when you’re prompting it to add new ones. You need to explicitly request it to append tests to file X without overwriting existing tests for it not to mess up, and even then results are sketchy. For unit tests it’s also important to setup good contexts otherwise whatever time you save by prompting copilot to write them will be wasted refactoring code to use specific frameworks and follow specific styles.
- Comment on Is GitHub Copilot worth it to you? 1 year ago:
Like most have already said, the auto complete is top tier (…)
My experience is the exact opposite. Even though it has its moments, more often than not it just hallucinates and proposes a lot of stuff that neither matches definitions nor could possibly compile. I guess that this might reflect the impact of having classes with similar names in multiple namespaces but it’s bad to the point I prefer to rely exclusively on plain old autocorrelation.
- Comment on Self taught = no imposter syndrome? 2 years ago:
I imaging trying to be a professional electrical engineer (despite having a degree)
That’s the definition of specious reasoning, and fails to address the point I made.
- Comment on Self taught = no imposter syndrome? 2 years ago:
This might be relevant to the discussion: