The most extreme example could be the legislation on weapons. A less extreme example could be legislation on food additives or PFAS.

But once the prototype is done, I spend too much time refining the details, fixing everything going wrong (bas design details, wrong implementation, half done testing ...)

A full agentic setting would be too expensive for me (I wonder how much Garry tan spends...)

So I'd like to take a more balanced approach with: 1. usual LLM specs and prototyping to get the bases of the feature and boilerplate done 2. Write myself the code, with the help of an ai auto complete (this is Where I look for recommendations) 3. Use a setup as OP mentioned to review code

My goal is to draft the solution with ai, write it myself but faster with auto complete, then throw ai review.

> Old images get dropped > A screenshot attached four turns ago can be 50,000 tokens. It is not helping the agent decide what to do now. Once an image falls behind your last two user turns, Brilliant strips it and leaves a short [Image cleared] stub in its place. The recent ones stay, because those are the ones that matter for the next move. Zero user effort, zero config.

Ok the context gets smaller but doesn't it invalidate the LLM cache?

To the previous poster: do other intense sweeteners (stevia, saccharin, sucralose) taste sweet to you?

If the safeguard against mass surveillance is strictly tied to geolocation (US vs. non-US), it can't be an intrinsic property of the model. It has to be enforced at the API or contractual level. This means international users are left out of those core, embedded protections. Unless Anthropic is planning to deploy multiple, differently-aligned foundation models based on customer geography or industry, the safety harness isn't really in the model anymore.

Credit where it's due, going on record like this isn't easy, particularly when facing pressure from a major government client. Still, the two limits Anthropic is defending deserve a closer look.

On surveillance: the carve-out only protects people inside the US. Speaking as someone based in Europe, that's a detail that doesn't go unnoticed. On autonomous weapons: realistically, current AI systems aren't anywhere near capable enough to run one independently. So that particular line in the sand isn't really costing them much.

What I find more candid is actually the revised RSP. It draws a clearer picture of where Anthropic's oversight genuinely holds and where it starts to break down as they race to stay at the cutting edge. The core tension, trying to be simultaneously the most powerful and the most principled player in the room, doesn't have a neat resolution.

This statement doesn't offer one either. But engaging with the question openly, even without all the answers, beats silence and gives the rest of us something real to push back on.

Either "we" create models better than commercial state of the art (by using whatever means).

Or we use open models AND fund organisations building such models (could be by purchasing service from these orgs or donations - in which case would these orgs be different than hyperscalers?).

But i dont see how just hosting the models on some private servers would give us an edge?

You can give it a try: there are very easy cameras!

For matters concerning IT and privacy, the CNIL (French Data Protection Authority) could spearhead such cancellation proceedings.

And companies doing business in France should watch out—CNIL sanctions are no joke!

Are there specific events making you feel it has been neutered?

- Fentanyl is ~100 times more potent than morphine

- 2mg can kill

- Medical use is around 100ug/hour for patches