Posted by y42 19 hours ago
I was worried about Anthropic models quality varying and about Anthropic jacking up prices.
I don't think Claude Code is the best agent orchestrator and harness in existence but it's most widely supported by plugins and skills.
I'm debating trying out Codex, from some people I hear its "uncapped" from others I hear they reached limits in short spans of time.
There's also the really obnoxious "trust me bro" documentation update from OpenClaw where they claim Anthropic is allowing OpenClaw usage again, but no official statement?
Dear Anthropic:
I would love to build a custom harness that just uses my Claude Code subscription, I promise I wont leave it running 24/7, 365, can you please tell me how I can do this? I don't want to see some obscure tweet, make official blog posts or documentation pages to reflect policies.
Can I get whitelisted for "sane use" of my Claude Code subscription? I would love this. I am not dropping $2400 in credits for something I do for fun in my free time.
Plus is still very usable for me though. I have not tried Claude Pro in quite a while and if people are complaining about usage limits I know it's going to be a bad time for me. I had to move up from Claude Pro when the weekly limits were introduced because it was too annoying to schedule my life around 5hr windows.
I started using codex around December when I started to worry I was becoming too dependent on Claude and need to encourage competition. codex wasn't particularly competitive with Claude until 5.4 but has grown on me.
The only thing I really care about is that whatever I'm using "just works" and doesn't hurt limits and Claude code has been flaky as all hell on multiple fronts ever since everyone discovered it during the Pentagon flap. So I tend to reach for ChatGPT and codex at the moment because it will "just work" and there's a good chance Claude will not.
Check any tasks if it's not currently working on one, and to continue until it finishes, dismiss this reminder if it's done, and then to ensure it runs unit tests / confirms the project builds before moving on to the next one. Compact the context when it will move to the next one. Once its exhausted all remaining tasks close the loop.
Works for me for my side projects, I can leave it running for a bit until it exhausts all remaining tasks.
Edit: i forgot HN doesn't do code fences. See https://pastebin.com/2rQg0r2L
Obviously the context window settings are going to depend on what you've got set on the llama-server/llama-swap side. Multiple models on the same server like I have in the config snippet above is mostly only relevant if you're using llama-swap.
TL;DR is you need to set up a provider for your local LLM server, then set at least one model on that server, then set the large and small models that crush actually uses to respond to prompts to use that provider/model combo. Pretty straightforward but agree that their docs could be better for local LLM setups in particular.
For me, I've got llama-swap running and set up on my tailnet as a [tailscale service](https://tailscale.com/docs/features/tailscale-services) so I'm able to use my local LLMs anywhere I would use a cloud-hosted one, and I just set the provider baseurl in crush.json to my tailscale service URL and it works great.
Asked support hey i got nothing back i tried prompting several times used a ton of usage and it gave no response. I'd just like usage back. What I payed for I never got.
Just bot response we don't do refunds no exceptions. Even in the case they don't serve you what your plan should give you.
Heck two weeks ago i tried my hardest to hit my limit just to make use of my subscription (i sometimes feel like i'm wasting it), and i still only managed to get to 80% for the week.
I generally prune my context frequently though, each new plan is a prune for example, because i don't trust large context windows and degradation. My CLAUDE.md's are also somewhat trim for this same fear and i don't use any plugins, and only a couple MCPs (LSP).
No idea why everyone seems to be having such wildly different experiences on token usage.
Chances are one of you has been drafted into an unpleasant experiment.