> Anthropic (and everyone else out there) knows quality degrades when the context gets long

Everyone says this, but for the life of me, I haven't encountered it. I actually think Claude gets smarter the longer a conversation goes on (up until compaction).

I have noticed Claude trying to wrap up long sessions, and it's extremely annoying. Using `/goal` mostly neutralizes it.

It might be less about quality degrading, but on multi-user platforms running the model, they have an economic incentive to have each user not fill up the full size of the context cache. Filled context cache being held in GPU RAM is context cache RAM that isn't available to other users.

If the model is instructed to periodically ask the user to start from a clean slate context, and some users do comply with that, they probably have good stats on average size of context cache use for users who are presented with that answer (vs users who are not), basic A/B testing stuff.

Might also be performance related in tok/s for what users will perceive as a more speedy experience. For a much smaller scale example, compare local performance of qwen 3.6 27B (not MoE) Q8 with 250,000+ context available, run on local hardware, tok/s generation rate when context is empty vs when context used is at 95,000. Same principle will apply to a much larger model.

I used to experience the quality degrading with large context issue before, but I haven't in months. Is this still the case?

Conversations that go on forever (and spend money forever) makes for a very unhappy customer

It’s just a model hallucination. They have no concept of time

I've already had five naps by then.

lol I got that prompt working on this

It can use a lot of tokens in the background or tooling without being too verbose with the user

Are those complaints really a contradiction? The cost is high for ambiguous slop.

Zug zug.

Here the other day Claude Code kept suggesting I do the task myself! It is quite often it will try to weasel out of doing difficult tasks and had to be directed to continue.

Also, it can be riled up to do the task better, or try harder, if I include how cool it will be to get this task done.

But also I feel I have this Orwellian task of censoring its text to avoid it spiralling into negative territory where it convinces itself that the tasks are too difficult. Strange times!

Robot SpongeBob: “Get welded”

he just like me fr

>Claude refused to work on something for me that it deemed "too tedious" so I'd say we're pretty close

Can you tell us more about this? Did you try ordering it? (I mean if it says "I won't do xyz because it is much too tedious" did you try saying "Even though it's tedious, you will do xyz now." - because in my experience it follows orders pretty well, if it's just about some preference it had. Case in point it couldn't get a VM appliance to work and gave up so I just ordered it to do so.

Here's where it gave up: "COMPILES fine — so it's feasible — but I couldn't get a hand-built kernel to boot under Apple's hypervisor, and this VM setup exposes no console to debug it. Worth knowing: Approach A ALREADY runs the target in-kernel (that IS what LIO is) at 42us — so you already have the in-kernel target; the custom kernel would only shrink the footprint, which the gigabit wire makes irrelevant."

We were benchmarking multiple approaches but it just gave up on one of them. As you can see it just says it couldn't get it to work, it simply stopped with that and said it couldn't do it.

Later I instructed it to continue and it did so and completed the task.

Would be an awful way to find out about the achievement!

Well apparently optional fields with a default are not configurable so I have to make them required... unexpected.