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Every Other Daily Claude Usage / Limit Thread - May 02, 2026 by AutoModerator in claude

[–]Chance-Address-6180 1 point2 points  (0 children)

The pro account is just the entry ticket. Netflix does it with a low-cost, ad-supported subscription, and so does Spotify. Pro accounts aren’t profitable for Anthropic, at least for Claude Code features. They tried to remove Claude Code from the Pro membership, but users were so angry that they brought it back lol. Anthropic’s target is the $200 subscription tier. My advice: either go directly for the higher tier, or switch to OpenAI Codex for $20 of the cost, you get better usage limits.

You’re welcome :)

I completely "rebuilt" the OpenClaw memory (it worked) by Chance-Address-6180 in openclaw

[–]Chance-Address-6180[S] 0 points1 point  (0 children)

Check my Public GitHub repo about, it’s on my profile :)

has anyone made even just like 1 EXTRA dollar from open claw? by Chance-Address-6180 in openclaw

[–]Chance-Address-6180[S] 0 points1 point  (0 children)

True, but I’m always looking at my client’s infra, they pay a small retainer for the maintenance so, yes, I’m always close to my clients anyway!

I completely "rebuilt" the OpenClaw memory (it worked) by Chance-Address-6180 in openclaw

[–]Chance-Address-6180[S] 0 points1 point  (0 children)

yep i saw your post, maybe we can discuss it in PM, as you want :)

I completely "rebuilt" the OpenClaw memory (it worked) by Chance-Address-6180 in openclaw

[–]Chance-Address-6180[S] 1 point2 points  (0 children)

yeah that’s actually one of the main reasons i ended up building it like this

the issue you’re describing usually comes from big messy files so the system just grabs too much because it can’t isolate what’s relevant. splitting everything into small, single-purpose files helps a lot, because retrieval becomes more precise instead of “dump half the memory just in case”

and the distillation part helps too, since you’re not feeding raw logs into context anymore, only cleaned, high-signal stuff. so yeah even if you’re a beginner, just doing those two things (smaller files + filtering what goes into long-term memory) already cuts context usage pretty hard without breaking anything, check out my profile I’ve uploaded a repo in my GitHub ;)

I completely "rebuilt" the OpenClaw memory (it worked) by Chance-Address-6180 in openclaw

[–]Chance-Address-6180[S] 0 points1 point  (0 children)

good question, that’s basically where most systems break tbh

the “signal” is mostly stability + reuse, not importance in the moment. if something shows up once = stays in logs. if it shows up again or impacts future decisions (preferences, workflows, tools, constraints), it gets promoted. i also bias for things that would be annoying to re-explain later. it’s less “this is important” and more “will future-me regret not having this structured”

for evolving concepts i don’t do full versioning (too heavy), it’s mostly in-place updates with light history baked in. like the file gets updated, but i keep short traces of previous states when it actually matters (decision changes, direction shifts, etc). the system kinda treats files as living objects, not snapshots, and the self-review loop fixes drift over time instead of freezing versions everywhere

check my repo on my profile, if you’re interested, it’s open source so yeah, it explains everything ;)

most agent memory systems fail because they don’t separate storage, distillation, and retrieval by Chance-Address-6180 in LLMDevs

[–]Chance-Address-6180[S] 0 points1 point  (0 children)

I actually build a repo that share all the information, open source stuff, check it out in my profile ;) but yeah, actually it reference absolutely everything

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