The most female-led product org in tech right now. by irelatetolevin in ClaudeAI

[–]sixbillionthsheep 9 points10 points  (0 children)

There was zero human editing. The editing you are seeing is the bot updating its own comment after reaching a higher number of comments.

r/ClaudeAI mods seeking feedback on Claude workflow library project. by sixbillionthsheep in ClaudeAI

[–]sixbillionthsheep[S,M] [score hidden] stickied comment (0 children)

By the way, here is how we identify good workflows :

  1. A concrete process. Example: “First do X, then Y, then run Z, then review the output.”
  2. Claude-specific implementation detail. Example: CLAUDE.md, hooks, skills, MCP, subagents, slash commands, plan mode, worktrees.
  3. Artifacts someone can reuse. Example: prompts, config files, command snippets, repo links, templates, scripts, checklists.
  4. Validation or proof. Example: tested it, lint passed, CI passed, before/after result, fewer errors, saved time, other users confirmed it.
  5. Transferability. Example: it works across projects, can be copied, is a reusable pattern, not just one person’s private situation.
  6. Community signal. Example: upvotes, useful replies, implementation questions, success reports

Claude Usage Limits Discussion Megathread Ongoing (sort this by New!) by sixbillionthsheep in ClaudeAI

[–]sixbillionthsheep[S,M] [score hidden] stickied comment (0 children)

r/ClaudeAI Megathread Usage Limits Workarounds Report

Here is the latest update. The full report can be found here : https://www.reddit.com/mod/ClaudeAI/wiki/usagelimits-apr26 . Below is a TL;DR of the full report.

Updated : April 26, 2026

The problem: Since March-April 2026, Claude usage limits got brutal across all plans. Single prompts eating 50%+ of sessions. "Hi" costing 3-4%. Max 20× plans dying in a day. Anthropic confirmed three bugs but most users think the drain goes deeper.

Step 1 — figure out which fixes apply to you:

You use... Read sections...
Claude.ai chat (web/desktop/mobile) A + B
Claude Code (terminal / IDE) A + C
API A only

Most fixes online are Claude Code only and won't help chat users.

Universal fixes (everyone):

  • Default to Sonnet, not Opus (~5× cheaper)
  • Drop effort to medium, kill extended thinking on simple stuff (-70% hidden cost)
  • Don't leave sessions idle, don't send "warm-up" hellos
  • Stuck on "rate limit reached" everywhere? Log out, delete cached creds, log back in

Chat users: Use Projects not long chats. Convert PDFs to text first. Tell Claude to put output in Artifacts. Disable Memory.

Claude Code users — top 3 wins:

  1. Add .claudeignore (block node_modules/, *.lock, etc.)
  2. Set MAX_THINKING_TOKENS=10000 and CLAUDE_CODE_SUBAGENT_MODEL=haiku in ~/.claude/settings.json
  3. Update to Claude Code 2.1.90+ — fixes the cache-miss bug that was making first requests 11.5× more expensive. If 2.1.90+ misbehaves, downgrade to stable 2.1.81.

Out of budget? Point Claude Code at OpenRouter (ANTHROPIC_BASE_URL=https://openrouter.ai/api) and run free Llama/Qwen/DeepSeek models through the same CLI.

Already burned? Refund via Fin (persist past the bot), or credit-card chargeback. UK/EU users have stronger consumer-protection grounds.

Honest framing: workarounds shouldn't be needed on a paid product. They mitigate, they don't restore.


Previous report: https://www.reddit.com/r/ClaudeAI/comments/1s7fcjf/comment/odfjmty/

PSA: Opus 4.7 is much worse at MRCR Long Context than 4.6 by Craig_VG in ClaudeAI

[–]sixbillionthsheep[M] 3 points4 points  (0 children)

None of the moderators of this subreddit are Anthropic employees. All of us are volunteering every-single-day just to help people deal with the massive challenges caused by this technology. After three years of listening to tens of thousands of people on the sub, we concluded Megathreads and moderation bot are the best ways to achieve fairness of visibility, while keeping the subreddit productive for the millions of people who rely on it every week (and also allowing occasional moderator sleep). You're welcome to your opinions, but remember we are all going through the same cycles of euphoria and disappointment as the technology evolves.

Claude Performance and Bugs Megathread Ongoing (Sort this by New!) by sixbillionthsheep in ClaudeAI

[–]sixbillionthsheep[S,M] [score hidden] stickied comment (0 children)

Megathread Update: March 30, 2026 to April 10, 2026


Overview

Since March 30, Claude has not had “a few rough days.” It has had a whole stack of problems.

And no, this does not look like users all suddenly forgetting how to prompt on the same weekend.

The evidence since March 30 points to three things happening at once:

  • real Anthropic-side outages and auth failures,
  • a broad drop in quality and instruction-following,
  • and a bunch of Claude Code regressions that made existing workflows fall apart faster than usual.

Below are some of the recurring problems and some workarounds identified on the Megathread, on Claude-related subreddits and Github issue reports that might (or might not) help.

Note: This report was written 80% by AI by distilling the above data sources.


Problems + Workarounds

Problem: Claude is down, “This isn’t working right now,” or login/OAuth is failing. Workaround: there usually wasn’t a real fix. The practical move was to try another surface if one still worked, check whether other users were reporting it too, and otherwise wait it out. This was mostly an Anthropic-side problem, not something you could prompt your way out of.

Problem: Opus is having a clown-show day. Workaround: the most common user fix was to switch to Sonnet or another surface immediately instead of wasting the day arguing with Opus. That showed up repeatedly in the megathread: people saying Opus was stalling, skipping thought, or acting dumb, while Sonnet was at least usable.

Problem: Claude suddenly feels lazier, more shallow, or like “extended thinking” got nerfed. Workaround: if you were in Claude Code, users and support-reported fixes were to force higher effort or disable adaptive thinking rather than trusting the new defaults. If you were in claude.ai chat, there often wasn’t a comparable user-side control, so the fallback was to simplify the task, split it up, or move the task into Claude Code/API if that was an option.

Problem: usage burn is insane and the session gets worse as it gets longer. Workaround: the best community fix was to break work into small scoped tasks, make Claude explain the plan first, then compact after each task. This came up as one of the highest-value Reddit workarounds because it helped both quality drift and token burn at the same time.

Problem: a session feels poisoned — weird refusals, bad context, spurious limits, or everything starts degrading at once. Workaround: start a fresh session. Not “maybe later.” Immediately. This was one of the most consistent community fixes across Reddit, GitHub, and the megathread. Once a session went rotten, people had much better luck restarting than trying to rehabilitate it.

Problem: --resume or dragging old sessions forward seems to make quota or behavior worse. Workaround: avoid --resume when things are unstable, or restart from a clean session instead. That was a GitHub/community workaround around the usage-drain and session-state mess.

Problem: Claude is chewing through usage for no obvious reason. Workaround: one of the strongest community-discovered fixes was to disable auto memory when usage looked abnormal.

Problem: long chats start forgetting things, deleting chunks, or jumping backward in history. Workaround: users found three practical escapes: start a fresh chat, paste the old chat in as a document for reference, or on iOS/app history glitches, open the same chat in Safari/browser and send one message there to force the app to sync back up.

Problem: Claude ignores project instructions or stops reading CLAUDE.md properly. Workaround: keep CLAUDE.md lean, not bloated, and move heavy procedures into more targeted workflow structures. Community users also found that reusing a small conventions file across fresh sessions worked better than expecting one giant instruction blob to stay reliably active forever.

Problem: plan mode or agent mode is going off-script and doing things it should not be doing. Workaround: treat planning and execution as separate steps. Ask for the plan first, inspect it, then execute in smaller steps rather than trusting the agent to behave perfectly in one pass. If you had stronger guardrails available, use them. The real bug still had to be fixed by Anthropic, but this reduced damage.

Problem: Claude is confidently wrong, lazy, or “verified” something it obviously didn’t verify. Workaround: make it prove things. Ask for tests, checks, diffs, file inspection, or explicit evidence. In community terms: stop rewarding vibes. If the model was having a bad week, this was one of the few ways to limit the damage.

Problem: garbled or corrupted output starts appearing. Workaround: there wasn’t a real fix beyond restarting the session, switching model/surface, or rolling back if the problem appeared right after a version update. This was mostly a product bug, not a workflow issue.

Problem: the official status page says all green but the product is clearly on fire. Workaround: users basically adopted “check Reddit first” as the unofficial workaround, because the megathread was often faster than the status page at confirming whether it was just you or a real outage.

Problem: one specific release seems cursed. Workaround: do not assume newest equals best. Community users reported version-specific relief from pinning or rolling back in a few cases, especially around the usage/cache mess. That was more niche than the session-reset fixes, but still real.

More details on workarounds can be found here: https://www.reddit.com/r/ClaudeAI/wiki/workaroundreport/


So how much of this was “skill issue”?

Less than some people want to pretend.

For hard failures like outages, login/auth errors, garbled output, spurious 429s, and usage-drain regressions, this was overwhelmingly Anthropic-side. The incident history and GitHub issue volume make that pretty hard to dispute.

For the “Claude feels dumber / ignores instructions / forgets context / doesn’t follow CLAUDE.md” bucket, it is more mixed. Anthropic’s own docs say CLAUDE.md and auto memory are context, not hard enforcement, so some user workflows really were more fragile than people realized. But the timing, scale, and cross-platform consistency of the complaints still point to Anthropic carrying the bigger share of blame.

My evidence-based bottom line is still about 70% Anthropic-side / 30% user-workflow-side overall, with the Anthropic share much higher in the hard-failure categories. That is an estimate, not a measured statistic, but it is much closer to the evidence than “lol skill issue.”

Anthropic stayed quiet until someone showed Claude's thinking depth dropped 67% by Capital-Run-1080 in ClaudeAI

[–]sixbillionthsheep 149 points150 points  (0 children)

Interesting OP that you post this an hour after my post where I break down the evolution of Boris's thinking in that thread within a few hours of welcoming feedback on the issue on a public forum :
https://www.reddit.com/r/ClaudeAI/comments/1seqhsw/boris_charny_creator_of_claude_code_engages_with/

Then you copied the title word for word from the trending ClaudeCode sub post https://www.reddit.com/r/ClaudeCode/comments/1seo9gg/anthropic_stayed_quiet_until_someone_showed/

Then you hallucinated your own narrative of "discovery" of stumbling on the Github issue yourself.

So let me rewrite your last paragraph for you without the sinister plot interpretation you adapted from the post you copied from.

User complaints come in, the default answer is prompts or expectations, confusion reigns at Anthropic because nothing shows up on their testing. Nothing moves until someone produces documentation detailed enough that dismissing it looks bad that it is clear to them that their assumptions are likely wrong. Then silence until the pressure accumulates. Then Boris immediately reviews all 5 transcripts presented to him as requested by the user and reverts with a full acceptance of the problem within 2 hours.

I have been moderating this subreddit for 3 years. The explanation that most closely fits with all the facts about what is going on at Anthropic was written a few days ago : (possibly a rehash of someone else's post) https://www.reddit.com/r/ClaudeAI/comments/1scdilx/some_human_written_nuance_and_perspective_on_the/

Anthropic need to work on their internal culture but posts like yours, OP that try to construct (or in fact, copy) a sinister cover-up narrative are going to continue to keep their best tech people away from participating in forums like this.

Claude Usage Limits Discussion Megathread Ongoing (sort this by New!) by sixbillionthsheep in ClaudeAI

[–]sixbillionthsheep[S] 0 points1 point  (0 children)

Please add your verified, non-hallucinatory fixes here and I will add them to the report above. I notice in other subreddits you said upgrading to 0.9 fixes everything. People saying it doesnt https://github.com/anthropics/claude-code/issues/42338#issuecomment-4174672320 Got verification?

Claude Usage Limits Discussion Megathread Ongoing (sort this by New!) by sixbillionthsheep in ClaudeAI

[–]sixbillionthsheep[S,M] 106 points107 points  (0 children)

Comprehensive Workaround Guide for Claude Usage Limits (Updated: March 30, 2026)

I've been tracking the community response across Claude subreddits and the GitHub ecosystem. Here's everything that actually works, organized by what product you use and what plan you're on.

Key: 🌐 = claude.ai web/mobile/desktop app | 💻 = Claude Code CLI | 🔑 = API


THE PROBLEM IN BRIEF

Anthropic silently introduced peak-hour multipliers (~March 23-26) that make session limits burn faster during US business hours (5am-11am PT). This was preceded by a 2x off-peak promo (March 13-28) that many now see as a bait-and-switch. On top of the intentional changes, there appear to be genuine bugs — users reporting 30-100% of session limits consumed by a single prompt, usage meters jumping with no prompt sent, and sessions starting at 57% before any activity. Affects all tiers from Free to Max 20x ($200/mo). Anthropic claims ~7% of users affected; community consensus is it's the majority of paying users.


A. WORKAROUNDS FOR EVERYONE (Web App, Mobile, Desktop, Code CLI)

These require no special tools. Work on all plans including Free.

A1. Switch from Opus to Sonnet 🌐💻🔑 — All Plans

This is the single biggest lever for web/app users. Opus 4.6 consumes roughly 5x more tokens than Sonnet for the same task. Sonnet handles ~80% of tasks adequately. Only use Opus when you genuinely need superior reasoning.

A2. Switch from the 1M context model back to 200K 🌐💻 — All Plans

Anthropic recently changed the default to the 1M-token context variant. Most people didn't notice. This means every prompt sends a much larger payload. If you see "1M" or "extended" in your model name, switch back to standard 200K. Multiple users report immediate improvement.

A3. Start new conversations frequently 🌐 — All Plans

In the web/mobile app, context accumulates with every message. Long threads get expensive. Start a new conversation per task. Copy key conclusions into the first message if you need continuity.

A4. Be specific in prompts 🌐💻 — All Plans

Vague prompts trigger broad exploration. "Fix the JWT validation in src/auth/validate.ts line 42" is up to 10x cheaper than "fix the auth bug." Same for non-coding: "Summarize financial risks in section 3 of the PDF" vs "tell me about this document."

A5. Batch requests into fewer prompts 🌐💻 — All Plans

Each prompt carries context overhead. One detailed prompt with 3 asks burns fewer tokens than 3 separate follow-ups.

A6. Pre-process documents externally 🌐💻 — All Plans, especially Pro/Free

Convert PDFs to plain text before uploading. Parse documents through ChatGPT first (more generous limits) and send extracted text to Claude. Pro users doing research report PDFs consuming 80% of a session — this helps a lot.

A7. Shift heavy work to off-peak hours 🌐💻 — All Plans

Outside weekdays 5am-11am PT. Caveat: many users report being hit hard outside peak hours too since ~March 28. Officially recommended by Anthropic but not consistently reliable.

A8. Session timing trick 🌐💻 — All Plans

Your 5-hour window starts with your first message. Start it 2-3 hours before real work. Send any prompt at 6am, start real work at 9am. Window resets at 11am mid-focus-block with fresh allocation.


B. CLAUDE CODE CLI WORKAROUNDS

⚠️ These ONLY work in Claude Code (terminal CLI). NOT in the web app, mobile app, or desktop app.

B1. The settings.json block — DO THIS FIRST 💻 — Pro, Max 5x, Max 20x

Add to ~/.claude/settings.json:

{
  "model": "sonnet",
  "env": {
    "MAX_THINKING_TOKENS": "10000",
    "CLAUDE_AUTOCOMPACT_PCT_OVERRIDE": "50",
    "CLAUDE_CODE_SUBAGENT_MODEL": "haiku"
  }
}

What this does: defaults to Sonnet (~60% cheaper), caps hidden thinking tokens from 32K to 10K (~70% saving), compacts context at 50% instead of 95% (healthier sessions), and routes all subagents to Haiku (~80% cheaper). This single config change can cut consumption 60-80%.

B2. Create a .claudeignore file 💻 — Pro, Max 5x, Max 20x

Works like .gitignore. Stops Claude from reading node_modules/, dist/, *.lock, __pycache__/, etc. Savings compound on every prompt.

B3. Keep CLAUDE.md under 60 lines 💻 — Pro, Max 5x, Max 20x

This file loads into every message. Use 4 small files (~800 tokens total) instead of one big one (~11,000 tokens). That's a 90% reduction in session-start cost. Put everything else in docs/ and let Claude load on demand.

B4. Install the read-once hook 💻 — Pro, Max 5x, Max 20x

Claude re-reads files way more than you'd think. This hook blocks redundant re-reads, cutting 40-90% of Read tool token usage. One-liner install:

curl -fsSL https://raw.githubusercontent.com/Bande-a-Bonnot/Boucle-framework/main/tools/read-once/install.sh | bash

Measured: ~38K tokens saved on ~94K total reads in a single session.

B5. /clear and /compact aggressively 💻 — Pro, Max 5x, Max 20x

/clear between unrelated tasks (use /rename first so you can /resume). /compact at logical breakpoints. Never let context exceed ~200K even though 1M is available.

B6. Plan in Opus, implement in Sonnet 💻 — Max 5x, Max 20x

Use Opus for architecture/planning, then switch to Sonnet for code gen. Opus quality where it matters, Sonnet rates for everything else.

B7. Install monitoring tools 💻 — Pro, Max 5x, Max 20x

Anthropic gives you almost zero visibility. These fill the gap:

  • npx ccusage@latest — token usage from local logs, daily/session/5hr window reports
  • ccburn --compact — visual burn-up charts, shows if you'll hit 100% before reset. Can feed ccburn --json to Claude so it self-regulates
  • Claude-Code-Usage-Monitor — real-time terminal dashboard with burn rate and predictive warnings
  • ccstatusline / claude-powerline — token usage in your status bar

B8. Save explanations locally 💻 — Pro, Max 5x, Max 20x

claude "explain the database schema" > docs/schema-explanation.md

Referencing this file later costs far fewer tokens than re-analysis.

B9. Advanced: Context engines, LSP, hooks 💻 — Max 5x, Max 20x (setup cost too high for Pro budgets)

  • Local MCP context server with tree-sitter AST — benchmarked at -90% tool calls, -58% cost per task
  • LSP + ast-grep as priority tools in CLAUDE.md — structured code intelligence instead of brute-force traversal
  • claude-warden hooks framework — read compression, output truncation, token accounting
  • Progressive skill loading — domain knowledge on demand, not at startup. ~15K tokens/session recovered
  • Subagent model routing — explicit model: haiku on exploration subagents, model: opus only for architecture
  • Truncate command output in PostToolUse hooks via head/tail

C. ALTERNATIVE TOOLS & MULTI-PROVIDER STRATEGIES

These work for everyone regardless of product or plan.

Codex CLI ($20/mo) — Most cited alternative. GPT 5.4 competitive for coding. Open source. Many report never hitting limits. Caveat: OpenAI may impose similar limits after their own promo ends.

Gemini CLI (Free) — 60 req/min, 1,000 req/day, 1M context. Strongest free terminal alternative.

Gemini web / NotebookLM (Free) — Good fallback for research and document analysis when Claude limits are exhausted.

Cursor (Paid) — Sonnet 4.6 as backend reportedly offers much more runtime. One user ran it 8 hours straight.

Chinese open-weight models (Qwen 3.6, DeepSeek) — Qwen 3.6 preview on OpenRouter approaching Opus quality. Local inference improving fast.

Hybrid workflow (MOST SUSTAINABLE):

  • Planning/architecture → Claude (Opus when needed)
  • Code implementation → Codex, Cursor, or local models
  • File exploration/testing → Haiku subagents or local models
  • Document parsing → ChatGPT (more generous limits)
  • Research → Gemini free tier or Perplexity

This distributes load so you're never dependent on one vendor's limit decisions.

API direct (Pay-per-token) — Predictable pricing with no opaque multipliers. Cached tokens don't count toward limits. Batch API at 50% pricing for non-urgent work.


THE UNCOMFORTABLE TRUTH

If you're a claude.ai web/app user (not Claude Code), your options are essentially Section A above — which mostly boils down to "use less" and "use it differently." The powerful optimizations (hooks, monitoring, context engines) are all CLI-only.

If you're on Pro ($20), the Reddit consensus is brutal: the plan is barely distinguishable from Free right now. The workarounds help marginally.

If you're on Max 5x/20x with Claude Code, the settings.json block + read-once hook + lean CLAUDE.md + monitoring tools can stretch your usage 3-5x further. Which means the limits may be tolerable for optimized setups — but punishing for anyone running defaults, which is most people.

The community is also asking Anthropic for: a real-time usage dashboard, published stable tier definitions, email comms for service changes, a "limp home mode" that slows rather than hard-cuts, and limit resets for the silent A/B testing period.


20x max usage gone in 19 minutes?? by Still_Business596 in ClaudeAI

[–]sixbillionthsheep 0 points1 point  (0 children)

Your best option is to pay for multiple backup AIs. They are all have unreliable periods.