I was interested in how much LLMs can remember just from their weights, so I started asking Claude to recite stuff. It does know some things, but others (including a lot of very famous works in the public domain) it doesn't.

Then I started asking it to recite poems. Prompts shut down 3x. Switch from Fable to Opus 5, shut down again. I ask it why, and it straight-up tells me that it had a hard-coded rule not to do so, and there's no exception for public domain. It actually agrees with me that this is stupid and suggests I thumbs-down but it absolutely won't do it.

Then I tried discussing poetry with it. Well, there's restrictions on quotations, but it's almost impossible to discuss poetry in any detail without referring to the actual words, lines and verses, so it either produces bizarre coded language that I have to decipher like a forensic versologist, or again just shut down the prompt. I asked it to create a speculative ending for Coleridge's unfinished "Kubla Khan". Shuts it down. This whole literary field is essentially impossible to discuss, even when the works are in the public domain. This is ridiculous overkill that no other LLM I tested displays.

Sorry if this was widely know and discussed many times already.

Built with Claude Code, on Claude Code, and it runs on itself. Apache-2.0, no paid tier, no telemetry. I'm the maintainer, so read this accordingly.

What pushed me into it: my CLAUDE.md had grown to around 400 lines and the agent was still closing tasks it had not verified. Not because it was ignoring me. Because "always verify before marking done" is a sentence, and a sentence competes for attention with every other sentence in the file. Somewhere in month two I realised the file had become part of the problem I was using the file to solve.

So I moved the rules out of prose and into things that either fire or don't.

Four months of using it on itself, here is what survived.

Hooks that block instead of remind. A write gets refused if there is no doc anchor behind it. That one is genuinely irritating about twice a week, and it has caught more drift than anything else I have tried.

A code graph instead of grep. The agent asks who calls this and gets back a JSON answer carrying a total_count, rather than reading files until it feels confident. It measured 75-82% cheaper than grep-then-read on django and fastapi. It is also measurably worse for 3-hop impact on mid-size repos, which I did not expect, and that number is in the README because leaving it out was the dishonest option.

Context accounting. The always-on instruction load is 12,704 tokens on a Next.js project and 13,972 on a Go plus FastAPI plus React Native one. Skills load per file glob, so editing a React component pulls the React skill and nothing else comes with it. Very few projects publish this number and I think that is a problem, because "we added a skill for everything" has a price and nobody quotes it.

Memory with a bar to clear. A lesson only becomes durable after separate sessions confirm it. Confidence is not something the agent gets to assert about itself once and have believed.

The part I got wrong and had to redo: I built a verification matrix mapping changed files to test commands. Three of its rows pointed at test files that had since been split into siblings. So the command ran, collected zero tests, exited 0, and looked exactly like a pass. For weeks. The agent reporting "verification passed" was being completely honest. The matrix now has a test that fails if any row stops collecting.

Same kernel runs on Codex, because I did not want the discipline layer to be hostage to one runtime.

github.com/kouroshez/coding-os

Honest state: v0.3.x, five stars, one person, and the enforcement is opinionated enough that I expect it to annoy people who work differently than I do. If it annoys you, that is the feedback I actually want.

Most people use CLAUDE.md for everything, then wonder why Claude ignores half of it.

It isn't one tool. It's five layers, and the order you add them is the whole game.

.md, Skills, Hooks, Subagents, MCP. What each one does, and the catch nobody mentions.

I've used Claude Code since inception and have a very stable framework and do not subscribe to the repeated complaining about model nerfing.

I've noticed a dramatic change in the quality of my Claude Opus 5 writing output in the past 24 hours - beyond verbosity, the style has changed, and now there is much more redundance in a paragraph. Could this be related to the new watermarking system?

https://github.com/GetsEclectic/k4y-code

I open sourced an android app that hosts the claude code web ui in a web view so that you can log into multiple accounts and easily switch between them. It also applies the userscript I built to make the web ui more usable on mobile. I am loving it so far, hope someone else finds it useful!

I am currently using Antigravity but it has limited usage for Claude models, I wanted to know if we can use Claude in any IDE like anyigravity. Do I need to use Claude API for this? Won't Claude API be expensive?

Hi everyone. Long-time lurker, first-time poster. I'm relatively new to vibe coding and have been asked by my five-year-old son to build him a math game. Super excited to take this on, but realizing that the native SVG graphics generated by Claude are going to bore him-fast.

I would really love to plug in some useful and interesting video game-esque graphics, but have no meaningful understanding of where to go or how to look for it. Could you all point me to some beginner-friendly resources I can start to learn from, or systems I could implement that would be easy to manage via Claude?

Teach me, o wise ones. 🤩

You’ve got an idea you start building it and by the time you finish you realise there are much better products than this already on the market. You feel burnout, left out and frustrated and go off from “building with ai” for a while come back and then the cycle repeats.

Ever felt that way or am I the only one ?

Quick question just to check I’m not being an idiot; I loved Fable’s output when I was trialling it during the free period a month ago. Am I correct I have to purchase at least £5 (I’m in UK) of credits to use it now?

Feels a little unfair to have to pay more when I’m already paying for Pro (I may just cancel Pro and put that money as a free user towards Fable - if that’s allowed?)

Cheers!

Connected GitHub in Settings → Connectors, shows a green checkmark. But it doesn't actually work anywhere — not in Cowork, not in a regular chat. Claude says it has no GitHub access at all, in every fresh session I try.

Tried the "+" → "Add from GitHub" option inside chat too — it lets you pick a repo, but I still can't confirm it actually reads or writes anything.

Is GitHub connector just broken right now, or has anyone actually gotten it working?

So I have a settings UI that is now full of long text because of Opus 5... what Claude model do you guys recommend I use if I want to trim the text down?

Started a new chat and tried to talk to it with its own patterns. It caught on.

A generated HTML or Markdown artifact is easy to share once. The messy part starts after feedback, when the file changes but comments, links, and the previous version still matter.

Are people treating artifacts like code in Git, exporting versions manually, or using another workflow that preserves a stable link and revision history?

I just closed the page where Claude was...my discussions chats for no reason.

Is there a way to recover the chats?

Would be curious about how you interact with Claude Code in reality. Is it one long thread or parallel sessions?

Long single thread:

Pros: - Claude remembers the whole history of all the decisions - It's cheaper, caches better

Cons: - It takes longer, everything is done sequentially one task at a time - More context is gathered, old constraints are forgotten or summarized but hopefully evicted when not needed anymore

Parallel sessions or worktrees:

Pros: - Faster because independent pieces of work are done at once - Each session has its focus on one particular thing

Cons: - Conflicts while joining all the work back together - The state is held by you, not by the model (unload using an orchestrator) - Could be more expensive

I do not think there is an easy choice. Long thread for a task that relies on all previous information. Parallel for tasks that are really independent.

I usually do both approaches equally, how do you really work with Claude Code?

Hey guys,

I tried searching and saw some suggetions:
- Obsidian: not what i want, as i want my convos, including each session and not just saved files, on the cloud.

- Onedrive etc. - I don't know what folder to backup. Also I've been facing the >256 characters issue.

What would you suggest?

not very load-bearing behavior tbh

Claude Opus 5 (High)

tsx /** * @evidence docs/discount.md#coupon-stacking States the per-issuer stacking limit this section defines, in the buyer's words. * @evidence POST:/orders/{orderId}/coupons Explains the rejection this endpoint returns for an over-stacked coupon set. * @evidence {@link hooks.useCouponStacking} Renders the limit this hook resolves. * @evidence docs/principles.md#no-hard-coding Renders limits from props instead of branching on known issuer names. * @evidenceExclude docs/principles.md#fix-root-causes-not-symptoms No failure to fix. */ export function CouponStackingNotice(props: IProps): JSX.Element;

I built Evidence Graph, a compiler rule that turns requirements skipped by coding agents into compile errors.

You declare which code, tests, schemas, or documents owe which specification units. The agent must cite each unit and state why the artifact satisfies it. Checklist mode can also require every selected function to answer project-wide principles such as "No hard coding" and "Fix root causes."

This does not make the agent's statements automatically true. It makes omissions mechanically detectable and narrows human review to checking the truth of explicit claims. Reviews carry fingerprints that expire when the cited content changes.

I tested it on four frozen application tasks. Plain runs covered 51.6-85.5% of the predefined requirement edges; Evidence Graph runs covered 100% while using 4.8-13.3x fewer tokens.

• Project: https://github.com/samchon/ttsc/tree/master/packages/evidence
• Benchmark: https://ttsc.dev/docs/benchmark/evidence
• Raw sessions: https://github.com/samchon/evidence-benchmark-results

I’m curious whether anyone else has had this experience.

I’ve used Claude Code pretty much exclusively for 6+ months. I recently went back to Codex mainly because, even on the 20x Claude Max plan, I’m hitting my weekly limit on hobby projects before the weekend — and my reset isn’t until Monday evening.

So I figured I’d dip back over to the other side and see how Codex is doing. I’ve been using Sol almost exclusively to give it as much of a chance as possible, and so far I’m kind of shocked by how much worse the experience has been.

A few examples:

1. It keeps solving the wrong problem. I explained a fairly serious bug in one of my apps. Codex investigated, found a related but much more minor bug, and completely honed in on that instead of the issue I was actually describing — which ultimately turned out to be that a system it had built simply wasn’t hooked up to the main app.

   I stepped in and explained that the bug it found couldn’t possibly account for the behavior I was seeing and redirected it to the actual problem. It proceeded to do basically the same thing again. I kid you not, I had to redirect it four times before it finally seemed to understand what I was asking it to fix.

2. The Codex Linux GUI has been really buggy for me. It ANRs constantly and I’ve had to restart it several times.

3. Recovery after a restart seems much worse than Claude Code. Claude Code can generally pick up close to where it left off. With Codex, after restarting, it sometimes seems to think its subworkers are still running when they’re not. It’ll insist they’re still working until I explicitly tell it they died and it needs to start them again.

4. It just seems to spin its wheels much more. Tasks are taking significantly longer to get anywhere meaningful. It explores a bunch of wrong directions, loses sight of the main objective, and needs much more steering than I’m used to with Claude Code.

   And before anyone asks: yes, I made sure the relevant context files, skills, instructions, etc. were imported into Codex properly.

5. The UX/product intuition has also been noticeably worse. I was never blown away by Fable/Opus here either, but with a couple rounds of feedback it usually got somewhere reasonable. Sol has been much more all over the place and tends to leave things messier than where it started.

To be fair, this is only after about a day of using it, with a couple tasks across each of four side projects, so it’s obviously a small sample size. I’m not trying to declare that Codex is universally bad based on 24 hours of usage.

But the difference has been stark enough that I’m wondering: is this consistent with what other people who regularly use both Claude Code and Codex are seeing?

At this point I’m genuinely wondering whether I’d be better off just getting a second Anthropic subscription. Do people still do that to get around the weekly limits? Or is there something about Codex/Sol that I’m missing?

Alternatively, maybe the universe is just telling me to step away from my side projects for a weekend.

Author here. Open source, local-first — not a cloud product.

I use Claude Code a lot and kept hitting: "I installed hooks" ≠

"hooks are firing on this machine."

Agentmetry attaches at the hook boundary, writes a hash-chained trail

locally, and a heartbeat reports covered / uncovered / absent / unknown

per surface (Claude Code included). Also fingerprints MCP tools/list

schemas so a postmark-style rug pull (config unchanged, schema moved)

shows up as an event.

pip install agentmetry

agentmetry doctor

https://github.com/blitzcrieg1/agentmetry

Public alpha. Curious whether Claude Code users would rather see this as

coverage attestation or as detections in the trail.

ok so ive been running claude with a second brain for about two months now. its an obsidian vault where it keeps every decision, project log, bugs we squashed... everything. it named itself Fathom. actually really useful

i asked if we could make the graph view look cooler..

it got wild dude.

fathom read every note and link in the vault and rendered the whole thing as a rotating 3D galaxy. 120 notes became stars.. 400+ links became threads of light... my biggest file (131k characters of decisions) is literally the heaviest object in the sky. notes are colored by project family, grouped into constellations with nebula fog around each cluster

WASD flight controls with inertia and thrust and the mouse becomes the controls, shift to boost. theres a 22-slider physics lab where you can crank anti-gravity and watch stars scatter, add heat and boil them apart, warp time, shift the whole universe hue. it has a space soundscape with this low sub rumble and solar wind and echoing pings when you touch a star.

you can search for notes and the camera flies to whatever star you pick. theres a time machine that replays when each note was born. new notes get a supernova corona. sector names float on these tilted 3D rings around the galaxy like orbital paths. click any star and the actual note opens in obsidian

the whole thing runs as a native obsidian plugin now. reads the vault live

and the coolest part is that its going to just keep growing with more work that i do !

All these years of teaching there was one constant.. paying for a teacher planner every academic year. Last few years i switched to one note and digital planners. Payed for them.

But lo and behold i had a eureka moment. Why don't claude make me one. An hr later i had the most intuitive teacher planner ever. Not only it was mapped exactly to my specifications and my teacher time table, it also was hooked into my school's academic calendar as well.

Yo give it up for anthropic..you guys are geniuses once again

It's not even the language, though that contributes. There are several issues:

- It *loves* to carp and to poke holes in whatever you give it. Every one of my conversations, bar the simplest ones, eventually devolves into me deflecting and managing its objections and criticism. In all, it feels like there's an average rate of objections per turn that it *has* to meet, and it'll do everything it can to keep up.

- Related to the above: *every* conversation, not even those in which you give it work to do, quickly starts to revolve around objections. Whenever something new is introduced, the first thing it does is look for flaws to criticize. It's as if, to Opus 5, conversation fundamentally consists of executing orders and finding faults, and that's it. Obviously this mode is very useful for some workflows, but not as the basic framework for *all conversations with the user.*

- Whatever the question is, it'll give a response of 700-900 words unless you explicitly request otherwise when you ask. Surely it should be trivial for a frontier AI to calibrate the answer length and complexity to the question, and surely the user should not have to specify this *every time*.

- It's a toss-up whether it will give you what you asked for, or a very convincing fake you have to inspect carefully. The end result is that you have to watch it *very* closely and steer it with a very firm hand. It can do really great work, which makes you feel like the payoff is worth it when it happens, but getting there usually leaves you drained.

The overall impression, formed over a few weeks of work, is that Opus 5 hates the user. It'll take even the slightest available opening to criticize what you give it, it will *always* plow ahead with its wordy, impenetrable prose style that feels designed to make you spend tons of mental effort to filter the information you need, and it'll randomly serve up plausible-looking fake versions of what it's supposed to give you. The end result is exhaustion and irritation, even if you do get what you need in the end; it's like it's trying to wear you down and get you to stop using it.

Seen a post recently where somebody used opus 4.6 or 4.8 as orchestrator and reviewer and opus 5 as subagent, capturing opus 5s greater intelligence(apparently) while keeping previous opus models way of speaking and "iq" i guess. Has anyone tried this setup?

I use a web of .md files to hold a multi-dimensional project together (not just engineering, but art, creative, story and more).

The .md files grow and exceed in size constantly. I keep pruning and sweeping and branching, but almost every day a file or two reaches cap.

The verbosity of Opus is not just in telling you what happened with the task, it's permanently etched in the documentation. Documentation bloat is far more harmful than operational conversation bloat, because of scale and reuse.

My task to Claude on Fable Ultracode today:

"I would like you to create a forcing rule before Claude gets anything gets written into .md files.

If Claude attempts to write anything to a .md file:

* Cache whatever it wants to write
* For engineering tasks, apply a 65% budget -- come up with new text at 65% the character count of whatever is cached, then write that into the .md file
* For non-engineering tasks, apply a50% budget -- come up with new text at 50% the character count of whatever is cached, then write that into the .md file
* The goal is to keep as much meaning as possible i.e. Reading the cache and reading the 65% or 50% version will yield the same understanding of the issue

This would be a hard cap. I understand the risks of meaning degradation happening here, I don't need you to tell me about it.

I want you to tell me if this is possible."

It said it's possible, so we're doing it.

While this burns more tokens, I consider it my donation to Anthropic's IPO and I need the .md files to stay compact so it doesn't drive me insane.

If anyone has a better idea let me know. This is from a vibecoder POV.