One developer named forrest chang reads the post the next day, identifies the four failure modes karpathy named and converts them into a single CLAUDE(.md ) file. Drops it on github on 27 jan.

220,000 combined stars later, its one of the fastest-growing repos in GitHub history.

the problem it actually solves is that claude code starts every session cold with no memory of your stack, your past decisions, what you ruled out last week or why you chose one approach over another and so it guesses and refactors things that were not broken. Karpathy described it precisely that models make wrong assumptions on your behalf and barrel ahead without checking. They dont manage their own confusion, ask for clarification, surface inconsistencies or push back when they should.

CLAUDE. md is a plain text file claude code reads at the start of every session. Four rules inside it being

1. Ask, dont assume. If something's unclear, ask before writing a line and no silent guesses about intent, architecture, or requirements.
2. Simplest solution first and implement the minimum thing that works. No abstractions you didn't request.
3. Dont touch unrelated code and if a file isnt part of the current task, leave it.
4. Flag uncertainty explicitly or if you're not confident, say so before proceeding as confidence without certainty causes more damage than admitting a gap.

That's the whole file with like seventy lines

I have been using it on a project that integrates with Magichour's and klings api coz video generation pipelines get messy fast, lots of stateful logic and easy for claude to go rogue and start helpfully refactoring things mid session and the reason 220k developers starred this because every developer who has used claude code for more than a week has been burned by exactly these failure modes and had been patching them manually, one frustrated session at a time.

While everyone's debating which model to switch to next, the actual edge is in how precisely you instruct the one already in front of you.

Have you tried it? curious what failure modes you r still hitting that the four rules dont cover.

Why is it that the Connectors content in Claude Desktop says it has moved to "Customize", but there seems to be no option to go directly to Customize in the navigation? This is a small issue, but I don't get the need for the extra click...

Does anyone know if theres a way to see what your usage credits have been used on? Ive had my usage credits burned without really knowing what caused it, i run the $100 max plan and have like $30 leftover from when anthropic gave peopel free credits a while back, just curious to see if theres anyeay to tell what theyve been used on

I saw this today. What does this mean? I don't see it on normal claude ai at all

Hey all, I hope someone can help me understand, and perhaps suggest a solution.

I've been running a Pro Plan since march. I've used Claude for various purposes, most noticeably 3 major chats that I have been running for months (reset them with BASE and document handovers to prevent sanding up entirely), using these chats to document both life, a medical procedure and treatment, as well as everyday motivational purposes. So, yes. Fairly complex things with keeping track of conversations, and events in my life, helpåing keeping track of Gmail and calendar. obviously also run other chats for more specific purposes, but nothing in nearly the same size.

No API token usage, no code, nothing in that department.

Usage normally not a problem, kept well within the pro plan, except for one instance where I had to top up because I had all my major chats rebuilt.

Fast forward until yesterday, where I wake up to a message that Claude has refilled itself for 300 euros worth. Or rather, I got a "prepaid extra usage". The receipt only listed "prepaid extra usage, individual plan".

So the difference went freom a 22 euro monthly plan, to a sudden top up across one morning without any significant warning. I did not perform any actions that were unusual, that I was aware of.

I haver tried to find out what caused it, without luck.

There are no API keys in use. No claude code. I do not see that I have made any actions in any of the chats that would leave them running in circles.

After this, I of course tried to raise a ticket with Anthropic. The AI agent as rather unhelpful, claiming it only had the mandage to reverse any recurring costs, not the prepaid ones.

I of course diabled further top up options and so forth.

While I was lookling into this, I could see session usage going up, after the timer reset - we're talking that with only tyhe app open, no tabs in browsers, no other devices, I could see, every time I refreshed the screen under usage, I could see session usage goinf up, until it maxed out again, and this time, weekly usage had been maxed as well.

I have created a new ticket with them, both asking for a refund on the prepaid tokens that I had not consented to having topped up, as well as help to find out why this usage suddenly goes entirely insane, but so far I have been met with rather limited help.

Am I locked into chargeback options, or is there hope that Anthropic might come to see my side of things - that I have not requested an 8 x monthly pro plan cost 'top up', especially when not using API keys or similar?

Also, what on EARTH would cause this, because I saw no immediate reasons for it?

Help, please. It's already a rather difficult situation for me in real life, I would really like to not also have to struggle with this.

I’ve been spending a lot of time coding, debugging, and chatting simultaneously with Opus 4.8, and something interesting stands out: I haven’t hit a session limit yet.

With Opus 4.7, my experience was very different. During intensive coding sessions especially when switching between Cloud Code and chat conversations I would often burn through my token allocation quickly. In many cases, my session would end within 30 minutes.

However, with Opus 4.8, I’ve been able to maintain much longer workflows without running into those same limitations. The model feels more efficient, more capable of handling extended coding discussions, and better at maintaining context throughout lengthy sessions.

I’m curious whether this is an actual improvement in session efficiency and token management, or if my usage patterns have simply changed.

Has anyone else noticed a significant difference between Opus 4.7 and Opus 4.8 when it comes to session duration and heavy coding workloads?

I’d love to hear your experience in the comments.

Whoop's official API (OAuth 2.0) is 13 read-only endpoints: recovery score, sleep totals, a workout list. The app shows you 24x more and none of the good parts are reachable programmatically. So I reverse-engineered the private API the iOS app actually uses and wrapped it as an MCP server. Plug it into Claude (Desktop, web, mobile, or code), or any AI that accepts MCP and your entire Whoop account becomes something you can query and act on in plain English.

It allows you to use basically the whole app surface including 48 tools across 47 microservices:

- Recovery, not just the score, but HRV, resting HR, respiratory rate, SpO₂, skin temp, and a one-call daily overview.

- Sleep, minute by minute, the full hypnogram (REM/light/deep/wake timeline + in-sleep heart rate), sleep need & debt, sleep performance, the sleep coach.

- Strain & cardio, day strain, calories, live HR, live activity state, configurable HR zones (set your max HR + 5 custom zones), VO₂ max.

- Strength Trainer with every set across your history, PRs, volume/progression, the exercise library, custom exercises, saved templates.

- Journal & behaviors, a 308-behavior journal with Whoop's own behavior-impact analysis (and Claude can analyze it itself), plus symptom logging and autofill.

- Stress, the intraday stress timeline and a live stress read.

- Trends & analysis across 25 metrics over multiple windows, week-vs-week / month-vs-month compare, a performance assessment, the calendar grid.

- Plus Whoop Coach AI chat, women's health (cycle phase + insights), community leaderboards, smart alarm, profile/body measurements, and hidden metrics.

Bundled catalogs (372 exercises, 308 behaviors, 203 sports, 311 endpoints mapped) mean the AI queries with real IDs, not guesses. And for anything I didn't wrap into a dedicated tool, there are two escape hatches, search the endpoint catalog, then call any of the 311 endpoints directly.

The MCP writes, not just reads. It can log workouts, add journal entries, edit your profile, reconfigure your smart alarm, change HR zones, all from your chat. Every write is preview-gated: it shows you the exact payload before sending, and nothing fires without your confirmation.

Setup is one command. The guided CLI runs the Whoop login (SMS MFA included) end to end, you just pick how you run it:

- whoop-mcp cloud → deploys to a host (Fly automated, or Railway / Cloud Run / Docker), generates its secrets, and connects it to Claude as a custom connector that syncs across web, desktop, and mobile.

- whoop-mcp local → runs on your machine over stdio for Claude Desktop / Claude Code. No hosting, this device only.

The 2-minute demo above is that whole cloud flow, untouched: install → login → deploy → connector → first query.

The project is built in TypeScript, every response schema-validated, so if Whoop changes something it fails cleanly instead of feeding the model garbage. Auth auto-refreshes (~30-day tokens). 212 tests. Works with any MCP client, Claude Code, ChatGPT Desktop, Codex, Gemini CLI, Cursor. The project is fully open-source and I actively push changes, if Whoop changes their API, I will immediately push a fix for it.

Free, open source, live on npm + the MCP registry:

- npm: briangaoo/whoop-mcp

- registry: io.github.briangaoo/whoop-mcp

- github: github.com/briangaoo/whoop-mcp

I kept running into the same problem while coding with AI.

After 100+ messages, the conversation contains important decisions, bug fixes, architecture choices, and unresolved issues.

Starting a new chat loses all of that.

Keeping the same chat means dragging around a huge conversation history.

I built an open-source tool called Context Graph Compressor that converts a conversation into a structured JSON state graph.

Instead of generating a text summary, it extracts:

* Decisions

* Facts

* Problems

* Goals

* Open threads

and stores relationships between them.

The idea is to create a compact handoff that can be pasted into a new GPT, Claude, or Gemini session while preserving the most important state.

Example:

100k+ token conversation

→ Context Graph Compression

→ ~1k token handoff

I'm curious:

How are people currently handling long AI conversations and context handoffs?

GitHub:

https://github.com/Adityapal67/context-graph-compressor

Adaptive thinking was a good feature; it allowed the model to respond faster when it did not have a complex task at hand. Now, if I toggle thinking on, it thinks extra for tasks which do not require thinking, and if I turn it off, the responses are subpar. As a result of this, I have thinking always on, and on pro plan, it means hitting the rate limits way to faster.

I really hope they bring back adaptive thinking!

lowkey spiraling right now but Claude thinks I’m a minor and I don’t know what to do. I’m almost nineteen and yet I can’t drive due to mental health reasons and I don’t have a state id yet. It says if I don’t identify in 30 days it will delete my account. I have memory turned off but I’ve said in chats before that I’m almost nineteen which is NOT underage. And the Yoti face scans keep timing out. I’m pissed and scared and idk what to do. I have a lot of info related to my novel in there along with general chats about life and I kind of need it currently.

Hi!

My company got accepted for the Claude Partner Network but in order to proceed it requires 10 people to go through the training to become a Certified Claude Architect. Unfortunately my company doesn't yet have 10 employees. And I didn't know about this requirement.

Is anyone interested in going through the training? If you are please DM me. I'll give you an org email so that you can go through the process. I currently have 9 spots open.

I'm only interested in fulfilling the requirement. You would get to keep the certification when you're done. I truly believe it's slated to be one of the most valuable certifications.

I’m trying to write this as calmly as possible, because my first version was basically just keyboard smoke.

What is going on with Opus lately?

From my experience, the last two Opus model updates have felt like clear regressions rather than upgrades. I’m seeing worse reliability, weaker instruction following, more brittle reasoning, and a general drop in the kind of high-trust behavior that made Opus worth paying attention to in the first place.

The frustrating part is not just that a model can have bad days. That happens. The frustrating part is the pattern: two consecutive releases that feel like they shipped before they were actually ready.

Opus used to feel like the “serious work” model. The one you reached for when you needed depth, care, and consistency. Lately, it feels like I’m spending more time managing the model than getting value from it.

I’m genuinely asking:
Has Anthropic acknowledged any quality issues?
Is this an eval problem, a product decision, a safety-tuning side effect, or something else?
What happened to the model welfare focus— was that just a marketing play?

I’m not posting this to dunk on Claude. I’ve used it heavily and want it to be excellent. But right now, the experience feels meaningfully worse, and the lack of clarity around what changed makes it even more frustrating.

Anthropic, please treat model quality regressions like product incidents. If a flagship model gets worse, users should not have to collectively reverse-engineer whether they’re imagining it.

I've been using Opus 4.8, all settings at max, and it takes so much time even before starting to dive into the code or reading the repo. It does burn tokens faster, but responds at almost as fast as when its at non-fast mode. The fast mode is mostly useless until n unless your usage limits are about to get reset and you wanna burn through tokens faster.

One of the few real frustrations with Claude for me was the session amnesia — close the window, lose the context. Built a fix that's held up well so I figured I'd share the shape of it.

It's a folder of plain markdown files (about me, people, projects, decisions) with a bootstrap file at the root that Claude reads first thing every session. After that, any new conversation starts already knowing my context, history, and writing style.

Tried the fancy approaches first (embeddings, graph DB, Notion) — plain files in folders beat all of them. Simpler turned out to be more durable.

Three demos in this short walkthrough — decision recall, pulling someone's full context, and synthesizing across multiple files: https://youtu.be/tZKAY5mqa_c

Glad to compare notes if anyone's running something similar with project memory or CLAUDE.md files

I’ve spent the past three days at peak frustration with this platform, so I need to get this out.

I switched to Claude from ChatGPT about a year ago. I also had Gemini running in parallel, but dropped that subscription three months ago. As of today I’m seriously reconsidering — and either going back to Gemini or returning to ChatGPT is on the table, because the Opus 4.x situation has become genuinely untenable.

Here’s what finally broke it: I asked Claude this morning to research current community complaints about Opus 4.8. I was already on Sonnet 4.6 because 4.8 is, in my experience, completely useless. This is what it came back with — and it’s worth reading:

“Opus 4.8 was released May 28, 2026 — three days ago. And the context around it is damning for the Opus line generally: Opus 4.7 logged two confirmed elevated-error windows on Anthropic’s own status page in the last week of May alone — May 22 and May 25 — on top of a cluster of GitHub issues documenting a quality regression that appeared about a week after its April 16 launch. The identical pattern Opus 4.6 hit in March.

The Opus 4.x regression cycle is now a documented recurring event, not a one-time anomaly.

The system card notes Opus 4.8 scored worse than recent models on at least one evaluation, and that anecdotal complaint patterns — which Zvi Mowshowitz specifically notes almost always reflect real underlying issues — are consistent with the quantitative trends.

Bottom line: Opus 4.8 is three days old, the entire Opus 4.x line has been a reliability and quality regression story throughout 2026, and your read on it is precisely consistent with what the benchmarks and community documentation show. Sonnet 4.6, Effort High or Max, is the correct configuration.”

So there it is — sourced, benchmarked, confirmed. The model I’m paying a premium for has been a documented regression story all year. Sonnet 4.6 with effort cranked up is apparently the answer, which raises an obvious question: what exactly is Opus for at this point?

Anyone else sitting on Sonnet 4.6 and not looking back?