Conversely, a no-AI ethos is one that will very likely need to be walked back at some point in the future for tech products. AI isn't going anywhere, so finding ways to use it constructively with your product is going to be a far better long term strategy. For now while it's new and scary and there's a lack of regulation and governance and ethical considerations - I can see why an anti-AI stance is popular, but it's not durable long term.

I'm a big supporter of LibreOffice, Codeberg, SourceHut, etc. on what they do, tell and defend, and I'm with them.

On the other hand, I'm not anti-AI, but I don't want it to be shoved down my throat in any and every app I have. I don't want that sparkly "Enhance this slide" button, "WhatsApp AI" in the corner, automatically generated "AI summary" in Google/YouTube, etc.

However, I'm fine with an unobtrusive "Summary" button in my search results (Kagi), or a tab which I can use with some models (Notion), "use ML" checkbox while resizing or "enhancing" images (Pixelmator Pro), or many small touches Apple enables with on-device models which doesn't have AI written all over it.

In short, I want consent, control and dignity in my workflows. Yes, I'm very against how these LLMs are trained, built and how the datacenters they run on harm the environment we live in. However, I'm not against the tech. I want responsible development of it, for the customer instead of their owners which wants to milk their users like content and cash cows.

The internet has been around for quite a while now, and is absolutely critical for a lot of applications. Most people would never give up the internet.

Yet there are still many applications without explicit mandatory internet tie-ins like cloud sync. In fact, "stores data locally" and "won't disappear with zero notice" are valuable features to many people!

Just because AI is a no-brainer must-have for some apps doesn't mean it is a required feature for all apps - let alone one shoved in your face every few minutes.

> finding ways to use it constructively with your product is going to be a far better long term strategy

It's worth pointing out that the original Document Foundation blog post (https://blog.documentfoundation.org/blog/2026/09/03/yes-no-a...) seems to be doing exactly this:

> The criteria we have listed do not amount to a definitive rejection. The AI sector is evolving rapidly; on-premises inference is becoming manageable on standard hardware; and open models are improving much faster than most of us had anticipated. Should an approach emerge that meets all the conditions, we will evaluate it very carefully.

I don't think there's enough information accurately assess this. Anti-AI movements might grow much larger than today, given AIs potential to replace jobs faster than we have the ability to create them. The movement could even result in AI going somewhere.

> is one that will very likely need to be walked back at some point in the future for tech products

No doubt, but that future is when companies have figured out proper fit for AI in their product context and preferably with local AI models.

It should not be with the current slap AI anywhere and everywhere approach that uploads and trains on all available user data, which is what everyone is opposed to.

I hate products that want me to find a use-case for their feature that they wanted to develop. It's great that some people love AI features, but for me, they are rarely solving an actual problem I have. But now I have to relearn the software because the company wants to go all-in on AI? Why should I? One example of that is Notion. I've loved it for years, and I'm still using it, but it's starting to lean heavier and heavier into an AI-first workflow and I don't like it to the point where I consider switching to something else regularly.

Nobody should be "finding ways to use" any technology. We should be solving problems first and foremost.