As a current free-tier user, this price & transition plan seems completely reasonable. I'll upgrade when the nudge comes. I've got at least that much utility from it so far.
Very glad this isn't a subscription.
I have found Claude to be especially unpredictable. I've mostly switched to GPT-5.4 now - although it's slightly less capable, it's massively more reliable.
Some of the flak is that issues are often only acknowledged once a fix is in place, and the partial fixes are presented as if they solve the whole problem.
The near-instant transition from "there is no problem" to "we already fixed the problem so stop complaining" is basically gaslighting. (Admittedly the second sentiment comes more from the community, but they get that attitude after taking the "we fixed all the problems" posts at face value.)
And they are often dismissed at first as perception/subjective bias, getting used to models being good and having higher expectations due to that, etc. users are blamed a lot before they are forced to admit that there is an actual problem.
Childhood, at least IME, does a bad job of preparing people for this: fault and blame rarely matter in real interactions. When no teacher is around to play judge, all that matters is that you get a favorable outcome. That's something you need to figure out, usually in the heat of the moment, how to get. It takes active effort to understand the other side.
It works for me Firefox's Cloudflare DNS over HTTP.
For clarity, the recent issue[0] likely wasn't intermittent. Cloudflare's malware blocking DNS server now blocks those archive.today sites. Doesn't affect the non-malware-blocking DNS server (1.1.1.1).
This could be an explanation for the drama - LLMs are trained to learn and emulate correlations in text.
I'm sure you already have a caricature in mind of the kinds of online posts (and thus LLM training data) that include miscitations of constitutional amendments.
It's not perfect but it does have a few opt-in security features: running all tools in a docker container with minimal mounts, requiring approvals for exec commands, specifying tools on an agent by agent basis so that the web agent can't see files and the files agent can't see the web, etc.
That said, I still don't trust it and have it quarantined in a VPS. It's still surprisingly useful even though it doesn't have access to anything that I value. Tell it to do something and it'll find a way!
I'm working in AI, but I'd have made this anyway: Molty is my language learning accountability buddy. It crawls the web with a sandboxed subagent to find me interesting stuff to read in French and Japanese. It makes Anki flashcards for me. And it wraps it up by quizzing me on the day's reading in the evening.
All this is running on a cheap VPS, where the worst it has access to is the LLM and Discord API keys and AnkiWeb login.
Ratio/quantity is important, but quality is even more so.
In recent LLMs, filtered internet text is at the low end of the quality spectrum. The higher end is curated scientific papers, synthetic and rephrased text, RLHF conversations, reasoning CoTs, etc. English/Chinese/Python/JavaScript dominate here.
The issue is that when there's a difference in training data quality between languages, LLMs likely associate that difference with the languages if not explicitly compensated for.
IMO it would be far more impactful to generate and publish high-quality data for minority languages for current model trainers, than to train new models that are simply enriched with a higher percentage of low-quality internet scrapings for the languages.
Many nations are now likely thinking: Why cooperate on international IP enforcement if we get lumped together with adversarial nations anyway?
reply