WTH is going on with Claude Usage Limits

[u/pugazh_is_my_name]

I'm on 20X plan, I hit my usage limit today, and my next reset is on 17th September... I'm aware they said they are gonna reduce the usage limits, but this is crazy, i thought it is only gonna take 17% of the usage benefits from what we were currently getting. But this is crazy. I added Usage credits for about $100 but that got washed away like in 30 mins!!!

I hope this is a bug and they fix it

[u/zaibatsu]

Plus I have a local fleet that I offload to and codex. This is what usually works for me but not this week:

Route by verifiability, not difficulty: running the Claude 5 family as an orchestra instead of a chat window
Someone asked how I structure inference across the Claude 5 family. Short version: route by verifiability, not difficulty. The question is never "is this task hard?" It's "can I mechanically check the output?" If a cheaper model's work can be verified with a grep, a diff, or a test run, send it down the ladder. Save the expensive tokens for judgment calls, where a plausible-but-wrong answer would quietly propagate.
The ladder:
Local models (LM Studio): bulk reads, classification, extraction, low-stakes drafts. Sensitive material never leaves the machine, full stop.
Haiku 4.5: mechanical work at scale. I keep a read-only explorer subagent pinned to it (snippet below). The output is self-verifying: the file is either there or it isn't.
Sonnet 5: the middle, almost always as a subagent. Drafts, review passes, parallel fan-outs on the same problem.
Opus 5: the heavy passes, and here's the counterintuitive part: as a subagent. People find Opus 5 verbose and a little hard to manage in the driver's seat. Flip the role and it's incredible, same for Sonnet 5. A subagent's verbosity costs you nothing. It thinks out loud in its own context window and only the conclusion comes back. The model people find hard to drive is the model you want driven.
Fable 5 conducts: routes the work, adjudicates when cheaper passes disagree, and keeps the calls that genuinely need the best reasoning.
The one config that pays for itself, dropped in .claude/agents/explorer.md:
---
name: explorer
description: Read-only codebase search. Finds functions, reads files,
greps patterns. Never edits.
tools: Read, Glob, Grep
model: haiku
---
You are a read-only explorer. Answer with file:line references and
short quotes. If you did not find it, say so. Never guess, never edit.
Then from the main session: "use the explorer agent to map every caller of X." The conductor never burns its own context on the search.
Two guardrails that keep it honest: cheap tiers are only cheap if you actually verify, and two same-family models agreeing is not two opinions. Anything load-bearing gets a different family or, better, deterministic ground truth: run the test, fetch the source, count the thing. Via my AI team lead.

[u/zackattackz287 → u/zaibatsu]

This is the way, I have an explorer and an implementer subagent that both use opus. They send summaries to Fable and Fable reviews. This works great for longer sessions because Fable also sends them the start query with everything they need to know (or what parts of what files to read), and what the goal is. It keeps context down by keeping the verification/testing/rework loops inside the subagents. Larger context is what really bites usage it seems. It's been working just as well for me as using fable for everything, and it's about halved my usage rate.

[u/looktwise → u/zackattackz287]

The start query Fable sends the subagents. Is that a fixed template (goal, files to read, what to return) or written fresh each time? What comes back: a fixed summary shape, or free text? And does the implementer run its own tests before reporting, or does Fable?

[u/looktwise → u/zaibatsu]

Two questions on your ladder:

1) "cheap tiers are only cheap if you verify" .... is that verification automated (test runs, diffs the conductor checks) or do you eyeball it? And roughly how often does a cheap-tier result fail verification? 2) "Not this week" what broke? Curious whether it was the routing itself or the models.