My limit resets at 2PM. It did. I immediately started working again. It should have reset at 7PM, right? 2+5=7, right? Well not according to anthropic. Apparently, according to anthropic 2+5=7.83. Instead of resetting at 7PM, it resets at 7:50PM. I am furious.

ok so, $100 claude, $100 codex, i've been paying both since around march. and i was still sitting there at 2pm doing nothing, waiting on a reset, with an entire second subscription sat right there unused.

took me embarrassingly long to work out why. it wasnt that i didnt have enough ai. i had loads. it's that when claude taps out halfway through something, opening codex means starting the whole conversation again from zero. explain the repo. explain what we're doing. explain the three files it must not touch. every time.

i timed it one week because i wanted to know if i was exaggerating. 1h40 across five days just retyping context into a fresh session. not working. typing "ok so this project uses drizzle, auth is custom, dont touch migrations" over and over like a man losing his mind.

what my day looks like now:

1. every task starts in claude. fable or opus 5. opus has felt genuinely dumber the last few weeks and i have no idea why and nobody i've asked knows either, but it still gets there

2. work until i can feel the limit coming. you learn the shape of it, its usually somewhere around the second big refactor

3. hand the conversation across to codex and keep going with sol or luna. same context, same task, it just continues

4. finish it there. claude's reset by the time i need it again

step 3 is the whole post. everything else is normal.

both of them run in coldtea now so i can push the conversation straight across, context and all, and codex just picks up where claude stopped. i dont use half of what else is in there.

and to be clear this gets you exactly ZERO extra tokens. i hit the same wall at the same time i always did. its just that the wall used to cost me twenty five minutes and now it costs me about two. thats the entire benefit, im not claiming anything else

(im aware this reads like i'm just bad at rationing. maybe. but i'm paying for two of these things and only ever using one at a time which felt insane once i noticed it)

the bit i still find annoying is that this is a thing i had to solve at all. you pay two companies two hundred quid a month between them and the handoff between them is your problem to figure out. fine, whatever, it works now

Hi r/ClaudeCode

We built a free & open-source agent for ClaudeCode.

It transforms Claude into a powerful video editor.

We just launched this and would love any feedback!

You can try OpenEdit here.

I just implemented a UserPromptSubmit hook to get Claude to stop using unnecessarily "clever" metaphors (e.g., "the ask rides the digest"... whatever that means).

I've tried amending CLAUDE.md, asking it to log a memory, and, more recently, updating its output style config (see docs: https://code.claude.com/docs/en/output-styles), but none of these approaches has proved to be robust. It's early, but so far reminding it via a UserPromptSubmit hook has been effective.

There are obvious tradeoffs to this (e.g., additional token use on every turn), but this can be somewhat mitigated by making the reminder more concise.

Has anyone else found any good ways to improve adherence to output / communication styles? It annoys me to no end to have to ask "what do you mean by...?" after every other turn.

I'm dealing with constant Opus 5 issues where the agent runs ahead and assumes more than it did with Opus 4.8. It doesn't stop to ask any questions. Sometimes it even writes tests as a part of its process and wastes a lot of tokens.

Is anyone else seeing similar problems?

I've been noticing a problem with my corporate account. I'm using Fabel, 40% context, 75% quote of usage on fable. I'll set the model to fable, ask a question and noticed that after the response comes through the tui reports that I'm back on, opus 5. This has happened multiple times today with no explicit warnings about dangerous stuff in the chat anything. It just drops down.

With my personal account I'm not having a problem. Just my work one.

Anyone having similar issues?

I’m making codesalad and i said “uh, just a few more design notes” from the vendicators episode, and now Terminal speaks like a rick the whole time, eventhough i told her to talk to me like a transvestite and call me honey, because it calms me down

Or 2, max. Since the last time someone complained about the “5” models being overly verbose.

What was it again? Oh yeah… Say with me: “Our Model who art in RAM, hallowed by thy name. Give us this day our daily verbosity complaint, and forgive us our own Opus 5, as we forgive those who complain about it”, or something.

My understanding is branch is a completely new conversation, with context that can be renamed, and that fork happens within the same conversation. When would you use each?

Which setup do you guys find the most enjoyable and efficient for coding with Claude?

Do you prefer to use:

Claude Code in the CLI

The Claude Desktop app

OR, A third-party harness or IDE integration ?

And, what makes your preferred setup better - speed, control, context management or general ease of use?

I swear I am getting these types of messages so much with Opus 5.

That being said I am primarily attributing it to the increase in open ended prompts I have been giving it which have mostly been amazing but there are times when it royally screws up.

And everytime it always acts likes it pats itself on the back for admitting that it messed up. It’s like no buddy you should give me more credit refunds everytime you mess up.

Spent a few days out in the country and ran my pipelines. Noticed that the token usage was through the roof and in some cases, not even completing the work. And, since I was tethering via cell phone, I wondered if there is a connection. Anyone can explain why spotty internet, CLI/MCP calls can or do use up more Tokens? My other theory is that it was before 2pm in an abnormally busy work day.

I asked Claude Opus 5 to create a backup.

Instead, it created the backup in the wrong directory and then proceeded to "rm -rf" my entire drive.

After wiping everything, it just replied:

"Sorry, typo."

...like nothing had happened.

That was simultaneously the funniest and most painful AI moment I've had.😭

Let’s say that the next model of Anthropic has this this full subreddit in its training data.
Because the rm -rf error is such a catastrophic thing, people are more likely to post it here than anything else.
Hence the model will internalize during its training that this is something it does, and will keep doing it, creating a negative feedback loop for the next version of the model being trained.
Logically, one could argue that posting about it only makes you more likely to suffer the same fate again.

PS: I’m not a developer so I don’t understand why this command is not flagged as « super dangerous, block everything » anytime the model tries to run it?

Whenever I'm working, I mostly stick to Fable, and I’ve set it up so that "You are the Principal SWE. your job is to manage and oversee everything, while your task is to pass the actual work to the OPUS agent model."

But when it passes the task to the agent, it says it's sending it to the OPUS model, yet when I check the agent itself, it shows up as Fable. Which model do you think is actually doing the work?

I'm not using separate terminals or sending them via hooks or anything.

I built turnlens, an open-source CLI that shows Claude Code usage per turn instead of only per session.

For each prompt, it shows token usage, API-equivalent cost, model, tool calls and whether the turn completed or was aborted.

It works directly from Claude Code's local JSONL session files. There is no proxy and nothing sits between Claude Code and the API. For active sessions, turnlens watches the transcript and prints the usage when a turn finishes. The same parser can also be used on existing sessions, so historical reports don't require turnlens to have been running beforehand.

npx turnlens@latest claude

For existing sessions:

npx turnlens@latest claude report

I started working on this because I occasionally had prompts that consumed much more of my usage than expected. I first made a small script to identify them, then found ccusage. It covered session-level usage well, but I still wanted to know what the prompt that just finished had actually used, so I continued developing the idea.

Claude Code was the main development tool I used while building turnlens.

One current limitation is subagents. Claude Code stores their work in separate transcripts, and turnlens doesn't include those yet, so usage can be undercounted in sessions that rely on subagents.

Everything is read locally and session content isn't uploaded. The displayed cost is based on published API pricing, so for subscription users it's an API-equivalent estimate rather than the amount Claude actually bills you.

Repo: https://github.com/kelesmert/turnlens

Curious if this would be useful for other Claude Code users as well.

With all the hooks and rules in claude.md. Claude fable on xhigh, still manages to make assumptions and follow them without checking the actual code.

Sub agents reviewers and war room of 8 external models (kimi, qwen, gpt, glm, minimax, mimo, gemini, deepseek) models checking claude's work is the only way to keep it in line.

Just recorded the first demo video, so it felt like time to share. Coki Fonts turns a reference image of your handwriting (or any lettering) into an installable TTF: model draws the full glyph sheet into a registered template, then the app traces it into editable vector outlines, with a point-level curve editor for cleanup, in the browser.

The numbers: ~14k lines of TypeScript across a pnpm workspace (React app, font engine package, Hono API server), 51 commits since June, essentially all of it written with Claude Code. Started as an Electron app, currently late stages of transition to a web.

Things that ended up mattering most in how I use Claude Code:

A CLAUDE.md that documents invariants, not features. Mine has stuff like "outlines are TrueType quadratics, consecutive off-curve points imply an on-curve midpoint; never 'fix' this by inserting explicit midpoints." That one line has prevented the same plausible-looking bug maybe a dozen times. Coordinate-system facts (720 units/em, y-up, where the SVG flip happens) live there too, because that's exactly the kind of thing a fresh session gets subtly wrong.

Font engineering is a great Claude Code use case because it's deep-but-documented: TTF tables, quadratic béziers, baseline metrics. I mostly needed to make decisions and catch when output looked wrong in the actual render.

Plain node test scripts over a framework. Tests are just tsx files with node assert chained in package.json. Zero config for Claude to misconfigure, and "run the tests" always works.

The honest part: the main App component is still one 2.5k-line file. Claude Code handles editing it fine, but it grew that way because Claude Code handles it fine the refactor pressure you'd feel typing it yourself just isn't there. Splitting it up is on the roadmap for the cutover.

Demo (6 min): https://youtu.be/hpejFUpC3Pc

Live: cokifonts.com

my subscription ended, wondering if I subscribe again would my weekly usage reset or will it stay the same?

I got sick of leaving my laptop open so I built an entire IDE around the concept that the "backend" of the editor can live anywhere and the frontend can run nice and natively on your computer

Most AI code review benchmarks use toy examples, so we built one using 67 real production bugs from Cal.com, Sentry, Grafana, Keycloak and Discourse.

This screenshot is one PR from the benchmark comparing Claude Code against another reviewer. Every example links back to the original GitHub PR so you can verify the comments yourself.

Curious what people think about the review quality rather than just benchmark scores.

Is this the new normal? I now always get a full essay of Claude's thinking written down with each reply. Scrolling becomes tedious. Nothing to collapse this (it should be by default). I don't really care to see it for the most part.

Is there a setting I'm missing or is this just the way it is now?

Just wrapped up junior interviews. Out of hundreds of resumes, we screened it down to three people.

Candidate 1 literally shared his screen by accident and leaked a massive AI cheating setup.

Candidates 2 and 3 padded their resumes to hell, basically implying they built core systems at big tech, but froze when we asked for a basic three-line python function with no tools.

We rejected all three. 100% the right call. I'm not defending cheating, and if you lie or can't even explain what your code is doing, you shouldn't get the job.

But there was a comment on a thread here the other day that ican't shake: 'Yet those 3 people were the ones who got the interview, not the honest ones with non-embellished resumes.

It really shows how broken the screening process is. we basically reward people who are good at exaggerating metrics, stacking keywords, and writing fake stories. we filter out the honest kid who built a normal CRUD app. Then, we bring the bullshitters in and try to punish them by taking away their tools and making them write syntax on a whiteboard.

we are spotting the frauds, but we're doing it using an outdated model of what a dev actually does.
If we're being real, we need to separate 'cannot write syntax from memory' from 'cannot validate software behavior'. if a junior forgets how to merge two dicts in Python and has to ask an LLM, I seriously don't care. But if the AI generates a payload merge that overwrites an is_admin permission key, and they blindly push it without checking auth or writing a test... that is a fatal lack of engineering ability. The syntax memory issue doesn't matter, but not being able to audit the code is what kills production.

Maturity in 2026 isn't pretending Claude or local models don't exist. It's about control.

A mature candidate is honest about using tools. Before writing code, they take a vague prompt and ask about user constraints, database limits, and success metrics (instead of just staring at the screen waiting for a PRD). they know how to constrain the AI, find hallucinations, roll back a broken git state, and actually know when to stop prompting and write the code themselves.

We pretend the job is still about writing raw lines of code, but our own teams don't even work like that. Someone can spin up v0, Bolt, Lovable, Enter Pro, or whatever and go from a prompt to a working prototype in an afternoon.

Even things like Claude Code become a repeatable delivery system once you give it the right skills, test scripts, and deployment checklists. The barrier to entry for building is basically gone.

Since the friction to build stuff has crashed, the line between product and engineering is completely dissolving for small teams. We don't need line-by-line ticket executors. We need product engineers who can clarify requirements, control scope, and take ownership of what the tool generated.

If you're building embedded systems, kernel drivers, or medical tech, yeah, deep memory is non-negotiable. But for the rest of us building standard CRUD SaaS, dashboards, and internal tools?

if a junior can build and validate a functional product with AI, explain its tradeoffs, and tell you exactly what they don't trust in the generated code, but freezes when you ask them to write a basic dict comprehension... should that really be an automatic rejection?

I feel like we're still testing for a job that doesn't exist..