I use Claude and Thaura for search in my daily life.

I use Claude as a rubber duck for coding. I also let it review my code for errors or make recommendations. On occasion, I'll let CoPilot or Claude add a few lines of code directly. I don't "vibe code".

I enjoy both uses. I don't feel guilty about either.

This entry was edited (Wednesday, March 25, 2026, 5:57β€―PM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I'd like to setup my own openwebui and ollama server at home sometime, but I haven't gotten around to it. I think it'd be nice to use open weight models instead of cloud services. But I'm doing ok otherwise.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I don't agree with many of the arguments against LLMs I see on the Fediverse.

LLM usage is not a GHG-intensive activity, especially compared to other everyday activities.

It disturbs me when people imply that LLMs are primarily responsible for climate change. This is not remotely true, and it ignores our real responsibility for working on the climate emergency.

It hurts my heart that smart people I know and respect don't know the main sources of GHGs.

cosocial.ca/@evan/115580076628…

This entry was edited (Friday, March 13, 2026, 3:36β€―PM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I don't use the term "stealing" for ideas, and I don't think it applies for LLM output.

I think that training LLMs on content to produce a model, then using that model to generate new content, is more akin to human learning than to verbatim copying.

I don't think that LLM output is a "derivative work" of the training data.

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I generally don't like LLM-generated images or video. I mostly don't like LLM-generated text -- it's usually flat, wordy, and full of business jargon. I don't often use LLMs for either of these things.
This entry was edited (Sunday, April 5, 2026, 4:17β€―PM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I think that using LLMs to create text, images, video or code is an empowering technology for a lot of people. I think especially with code, it gives people who don't code and who've never had control over their computing experience more agency in their life and work. I think that's a net positive result.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

As a software engineer and engineering manager, I am mildly concerned for my employability in the future. However, I've had a good career, with much more luck than I deserve. People in my profession have been notably pampered and paid extremely well. As automation turns its Sauron-like eye to my own industry, it's hard to say with a straight face that we have been unfairly treated. I also think that there are, and will be for the foreseeable future, a lot of options for people who like to code.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I see a lot of strong anti-LLM takes on the Fediverse. I like some of them, and I don't like others. I sometimes respond if I think I can contribute to the conversation, but not always.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

working on a piece on this but broadly in agreement - i think the AI exceptionalism is fever pitch here rn as if everything up to here was somehow fine and dandy and now we've passed an invisible threshold into fascism. like cmon...
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I have a lot of good friends who are passionately anti-LLM. I also have some friends who are deeply into LLM usage, especially for creating software. I like both sets of friends and I want to stay friends with all of them.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I don't like the effect of AI/LLM scrapers on the open web. I think it's a serious problem. I think AI producers should commit to supporting robots.txt and other rate-limiting schemes, and to only using third-party data that has been acquired with similar support.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

In my career, I have experienced several waves of technology advances that have made building software easier and opened the process up to more people: high-level programming languages, IDEs, HTML and the Web, low-code/no-code platforms. I don't think software development with LLMs is a discontinuous break with these other advances.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

Hmm, I understand many of your arguments and experiences, but I see a break with low-code/no-code platforms. That's because I don't know of any professional solution where these platforms really serve their purpose. I have worked as a freelancer and employee in various companies (Germany, EU) and have also been involved in several LC/NC projects. All of them failed due to the complexity of the business processes and failure to implement the requirements of decision-makers. The hoped-for simplification of implementation through UI-driven tools, which was supposed to save on devs, ultimately led to developers operating the UI tools and the business finding it too complex. However, the lc/nc SaaS solutions represented a discontinuity in the development

1/2

in reply to Aljoscha Rittner (beandev)

pipeline and were also considerably more expensive than traditional implementations, for which the developers had been trained.

So if lc/nc doesn't really work, I don't know how LLM with agent-based AI will help us. Plus, it's not even deterministic. The lc/nc platforms even have the advantage of working with code in the background that was created by developers who hopefully still understand it. Unfortunately, the same cannot be said for many prompt hunters who generate code.

I am very skeptical about what the future will bring with AI. But this is my personal opinion and experience (and I'm not alone in my area). However, as a professional I use AI to do boring stuff faster. Like a wrench or hammer. But not as a machine to produce complete solutions.

2/2

@evan

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

More broadly now that scraped data is a large-scale internationally traded commodity like oil or coffee, we need a system of certification to allow for traceability of point of origin, environmental impact, ethical production etc., and regulatory scrutiny & enforcement layered on top of that.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I didn't acknowledge in this discussion that the special role that software developers and other technologists have doesn't just mean extra privileges and higher wages. For some people, it's a lifeline.

Some neuro-atypical, LGBTQ+, politically dissident, disabled, culturally non-conforming and simply weird and eccentric people have found a place in society where they are tolerated and even celebrated because of their ability to make and maintain software systems.

This entry was edited (Saturday, July 18, 2026, 7:04β€―PM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I don't think it's ever been a safe harbour, but it's been a handhold.

I think it's more than reasonable for people to question what the growth of AI-assisted and AI-generated software development and maintenance means for that handhold.

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

By far, one of the best takes I’ve seen on here.

I fear that the tech world has become too cliquey.

I appreciate the β€œfound family” aspect of what the space has become, but it turns to tribalism & fandom real quick because a lot of people have internalized the β€œus vs them” mentality as a means of safety that has turned quite toxic.

The humanity of others has been lost on the internet for so long and a lot of the hurt is starting to come from people who have been hurt the most.

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I don't have a knee-jerk reaction to AI. I find quite often that people will jump on a bandwagon and attack something based upon headlines that state others are attacking it. I usually have opinions on how something is being used such as LLM's and AI using data without permission. I generally research before making a judgment which, sadly, not many people do- in my experience.
This entry was edited (Saturday, July 18, 2026, 7:35β€―PM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

common GenAI images aren't great, since they're generated by image uneducated users.

But I've seen really interesting work by photographers already (it's not a surprise, since their own art got the same criticisms a century ago "it's not your work, it's the machine's", "it's not art, it's engineering"). But that also implies that a lot of curation and post-production takes place in the process, just like photography.

And of course, using the medium to say something through it.

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

There are so many applications for which LLMs are used/useful. I think you make good points about learning based on experience for code production and other uses. OTOH, if I had worked intensively to produce copyrighted content β€” I am thinking about books, whether fiction, textbooks, etc. β€” that was then scooped up and regurgitated after a query (e.g., medical advice), I might think otherwise (not to mention the risk that LLMs probably shouldn't be used unsupervised for med advice rn).
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

Data doesn't support your belief.

β€œglobal electricity consumption for data centres is projected to double ... by 2030 ... representing just under 3% of total global electricity consumption”
β€œmainly driven by AI adoption”
iea.org/reports/energy-and-ai/…

I'm sure you can find more online. Or even ask you agent of preference πŸ™„ Your example simply ignores the big picture, and narrows down the problem to someone's personal choice.

This entry was edited (Wednesday, March 11, 2026, 12:23β€―AM)
in reply to Sieva πŸš΄πŸš‡πŸ™οΈπŸŒΉ

my previous job was building greenhouse gas inventories at the national, state and city levels.

Electricity generation is about 1/3 of global emissions; 3% of that would be less than 1% of global emissions for all data centres.

Even given the numbers you're sharing, and even if AI were responsible for all data centre energy use, AI is not a major source of GHG emissions compared to transportation (15%), cattle (7%), cement production (8%), deforestation (15%) or rice cultivation (3%).

This entry was edited (Wednesday, March 11, 2026, 1:11β€―AM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

@Anibyl I appreciate that hearing that electricity use in data centres is going to double by 2030 sounds troubling. But doubling a small percentage of total greenhouse gas emissions gives a larger but still small percentage. Electricity production is also one of the GHG sources that's easiest to decarbonize.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

This is whataboutism, Evan. Of course AI is not the biggest source of our emissions, but its contribution is significant. Like, it's close to a whole %? In the context of it 1) not being essential and 2) bringing other substantial negative side effects I don't understand how it's possible to say β€œnah it's ok”.
in reply to Sieva πŸš΄πŸš‡πŸ™οΈπŸŒΉ

@Anibyl it's absolutely whataboutism.

I started the conversation talking about relative contributions to global GHG emissions. That requires comparing different activities.

If you want to help stop climate change, skipping one hamburger does 2000 times more good than avoiding AI.

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I agree that they aren’t the only drivers of climate change, but please take a look at this article which explains why AI is polluting more than regular energy users.
β€œThe rush to build supply has bid up the cost of conventional gas-fired plants (and deliveries are back-ordered for 5+ years). To work around that, big tech companies are bringing small truck-mounted turbines designed for short-term or peak use by the dozens. This is the opposite of economies of scale. These generators have roughly 50% higher fuel costs than a utility-grade combined cycle gas-burning plant, and the maintenance of a field of engines is multiples more expensive. That also means 50% more emissions pushed onto the local community, and tempting opportunities for developers to play fast and loose with air permitting rules.”
blog.ucs.org/mike-jacobs/as-se…
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I think the question is not so much about current pollution but what will happen as things scale. β€œGiven the direction AI is headedβ€”more personalized, able to reason and solve complex problems on our behalf, and everywhere we lookβ€”it’s likely that our AI footprint today is the smallest it will ever be. According to new projections published by Lawrence Berkeley National Laboratory in December, by 2028 more than half of the electricity going to data centers will be used for AI. At that point, AI alone could consume as much electricity annually as 22% of all US households.”

technologyreview.com/2025/05/2…

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

Since I already have my own servers at home I have been ramping up my research and playing with locally hosted LLM’s, one project (that is currently waiting for me to have more time to work on its next phase is: github.com/scanner/booklore
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

A bit late to reply on this but I dropped my chatGPT sub at the start of the year in favor of using openwebui with openrouter. I would highly recommend it. You get to use any model you want. Have a lot more control over how it generates responses and at least for me I've only spent half of what the chatGPT sub would have cost me in 2 months.
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

It's kind of nuts how polarized people are on this. I've been following this technology since 2015 (I, as an artist, taught myself Linux so I could run my own style transfer neural networks locally) and it feels a little disorienting the kerfuffle that stirs.
in reply to Aslan French

@jcklpe.bsky.social I think there are a lot of reasons for this.

One big reason is gatekeeping. For those of us who've made our living from building software, it's threatening to see people without our skills making software for themselves. Especially if we are emotionally and intellectually invested in the craft of software making.

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

my employer will pay for pretty much any tools one can think of and yeah. for a quick "hey should this fail and panic!() and crash everything according to the docs" llms are (mostly) great
not so great when the thing i'm trying to do is niche and/or specific to the [in-house] libraries we use, but considering the main offender is mostly a thin api wrapper around an opensource c thing it manages more or less fine

would i want the whole "ai" industry to go up in flames without any hope for recovery? yeah
am i gonna take everything my BigTechCorpInc. employer will give me? also yeah

tho now that i think about it, maybe i could ask them for a 128gb ram mac mini or smth as a one-time purchase as an ollama server instead of the subscriptions :neofox_evil_3c:

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

@Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ This is where I'm going to have to respectfully disagree.

If I'm going to ship code, I need to be able to be able to answer for what that code does. The necessary level of understanding can be achieved with LLM-generated code, but it involves studying its output to be sure that every lineβ€”every statementβ€”is understood. To me, it seems that the amount of work necessary to achieve that level of understanding negates any boost in prodictivity I may get from using the LLM in the first place, and it certainly doesn't justify the ethical cost.

I've been working on a fork of a large FOSS project lately. For me, the bottleneck hasn't been the actual writing of the code. More than half of my time has been spent studying the existing code to understand how it works so I can figure out the best way to make my edits. An LLM can't just magically give me that understanding.

Also, when it comes the actual writing of code, it's easier for me to express what I want in the unambiguous syntax of a programming language rather than the crude tool that is natural language. The latter I only use for communicating with other humans, and only because I lack a better tool for doing so. I'll freely admit that that last point is not universally true for everyone.

Also, I'll concede that the use of third-party libraries muddies the waters in terms of understanding how the code works. This is why I choose not to crucify those who do use LLMs to write code. I just choose not to participate.

in reply to Jonathan Lamothe

@me Hey, Jonathan. You are not disagreeing with me.

You should go back and re-read what I said about how I use LLMs. I don't "vibe code", and I don't let LLMs generate a lot of code for me. I use LLMs for reference, rubber-ducking, and occasionally to do mechanical transformations (like changing the order of arguments to a method).

in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

@me Also, I really recommend that you try using Claude, Codex, or another agent to learn about an existing codebase. I think you'll be pleasantly surprised how well they can answer questions like "What are the high-level groups of modules in this software?" or "Why does this codebase still depend on Python 2? What would the upgrade path be?" or "Where is the configuration option for debug logging set?"
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

I will say that just for doing research and for doing code review, LLMs save me a lot of time and hassle. I do not enjoy breaking my flow to go read docs on the available arguments for a library's functions. I also catch a lot of typos and other minor errors using LLM code review. I think I make better software faster this way. And I'm a lot happier!
This entry was edited (today, 12:12β€―PM)
in reply to Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ

@Evan Prodromou πŸ‡¨πŸ‡¦πŸ‡ΊπŸ‡ΈπŸ‡¬πŸ‡·πŸ‡΅πŸ‡Έ I guess my problem here is that I can't trust the LLM not to "hallucinate" the answer. I would feel the need to double check them, negating any benefit I might get because I'd have to do the same amount of work anyway. I can perhaps see some limited utility in using the LLM as a sort of search though, e.g.: "where in this codebase can I find the logic that handles $thing?"

The one point where I really get hung up is this: if machines can in fact thinkβ€”which I doubt for reasons that are outside the scope of this postβ€”would that not make it morally wrong for us to try to bend them to our will? What makes that different from slavery? I bring this up because it seems to be the argument supporting your position that LLM output doesn't constitute a derived work of its training data.

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