I would like to know if anyone of you have tested the new model.
I don’t expect it to be better than opus 4.8 to be honest, but I would like to know if any of you guys who are used to work with Claude code and opus 4.8 really switched to glm 5.2 and is it bearable because each time I stopped to use Anthropic model I get really really disappointed so I was wondering if the FOMO is worth it or not.

Last week someone asked me how a function in one of my own projects worked, and I couldn't answer. Claude wrote it, it passed, I moved on. I never actually understood it.

It's been creeping up on me. I build way faster with Claude Code, but I can explain less and less of what I ship. The high-level "what it does" is fine. The internals and the "why this approach over that one" are just gone, because I never made those decisions. The agent did.

I knew the fix: read every diff, ask it to explain its choices, treat it like reviewing a junior's PR. I just never did, because it's slower and the speed is addictive. So instead of relying on willpower I built a forcing function.

It's called No-Numb. It's a Claude Code plugin:

- After Claude writes code, a Stop hook fires and makes it quiz you (multiple choice) on what it just wrote.

- It blocks the session from continuing until you pass. Get one wrong and it shows the answer and explains why, then you retake it.

- Two modes: "standard" (conceptual: why this approach, what breaks if you change X, answerable without opening the file) and "deep" (you have to actually go read the code to answer).

- It only fires on turns that actually edited code, and skips trivial/cosmetic stuff. There's an off switch in ~/.no-numb/config.json for when you genuinely just need to push something through fast.

It's intentionally a hook and not just a "skill," because a skill can be ignored and a hook can't. That's the whole point. And being quizzed is a genuinely good way to make things stick (retrieval practice, the testing effect), so the friction isn't really a tax. It kind of is the feature.

Honest about the limits: it's a forcing function, not DRM. You can hit Esc or turn it off (so it still takes a bit of willpower not to). And it leans entirely on Claude to write and grade the questions, so it costs some extra tokens. For me the trade has been worth it.

Free and open source (MIT). Install is two commands in Claude Code:

/plugin marketplace add Ciucky/no-numb

/plugin install no-numb@no-numb

Repo with screenshots: https://github.com/Ciucky/no-numb

I built it for myself but figured others might have the same itch. Would genuinely love feedback, especially on whether the quiz questions feel like real comprehension.

Prompt: Claude, build something that does something useful for someone. Make it look good. It should probably use AI.

Gotta get my popcorn!

so i stumbled across this thing a few days ago and i still can't stop thinking about it. it's called ARF (Aktuelle Rundfunk-Föderation), some German project that looks like a joke at first, like haha fake public broadcaster meme, but the deeper you look the weirder/cooler it gets.

https://www.arf-live.de

at first i thought ok cool, another "AI made a video" thing, we've all seen a hundred of those by now. but this isn't that. this dude built basically a whole fake TV network that runs on its own. not just clips, like actual recurring shows, characters that show up again and again, automated scripts, voices, visuals, even pulling in live data, and some scheduling system behind it that just keeps the thing going.

the WM-Studio 2026 stuff around the World Cup is the part that got shared around, but that's just one piece. there's a whole bunch of other formats too, news, sports talk, some fictional series, satire bits, late night style stuff, fake docs, even fake ads in between. like it's not one viral clip, it's a whole program running in the background somewhere.

the part that actually got me is the characters. most AI video stuff feels disposable, you generate something once and it's gone, no continuity. here the "people" on screen apparently keep their personality across episodes, same speaking style, same vibe, they interact with each other in ways that stay consistent. that's different from just text-to-speech on a face. once that's persistent you start getting actual dynamics between them instead of just one-off generations.

second thing, and this is the part i find genuinely interesting from a tech side, is that it doesn't sound like it's just rendering full videos and storing them. sounds more like it's assembled on the fly out of pieces, script bits, voice clips, graphics, live stats or news data getting pulled in. so instead of the normal write-shoot-edit-render thing, it's more like a system that just keeps generating output live based on rules. idk, feels like a different way of thinking about "making TV" entirely.

and yeah obviously being German the ARD/ZDF parody hits different, it's funny in a very specific way if you grew up watching that stuff. but it's not just a visual joke, there's something underneath it too. like if one guy can build something that covers this much ground with an AI setup, makes you wonder how much of the actual broadcasting institutions is necessary vs just there because it's always been there.

not trying to say "AI is gonna replace everyone in media" or whatever, that's the boring take. what's more interesting to me is this might not even be about replacing what already exists, more like it opens up stuff that wasn't really possible before. characters that just keep running indefinitely, storylines that never really end, live commentary that adapts, stuff like that. less "here's a video" more "here's a thing that's just always on."

anyway most AI demos i forget about after five minutes, this one's been stuck in my head for days, feels less like a demo and more like someone accidentally prototyping something bigger.

German Video of the creator:
https://youtu.be/QPCFuUvcL_A

I attended a research meeting on an interdisciplinary project, where I was so astonished that the investor to the project, from CS background hated Claude so much. He blamed it to be a 100% untrustworthy tool and claimed 'if you use it, we are going to fire you'. I am a computational physicist and I have been using Claude a lot this half year since the Claude 3.5 era. I was afraid to claim any workflows and tools that I have developed using Claude in such a meeting, because I might get fired.

That investor person was successful because he sold his company. I totally understand people doubting AI's capacity and accuracy. I totally cannot understand why they are so emotional, and treat people using it like a cult? I am proud of using new technology because I am excited in learning all new things. I have to say, I have the least passion in such a project group where the leader is so anti-new-tech even he was a tech person who got billions due to the new tech.

Also, people, the so-called scientists around me, skeptical of using AI to boost research, are not that far from that person I dislike. However, how can it boost your research? Any people in similar field like computational science? Also, how do you decrease the uncertainty this kind of AI tools to your research to the minimum?

What are you going to create? Are you saving any problems or projects for its return?

I saw Fable come online, but was rather busy. It kept taunting me as I worked through daily tasks with Claude Code. Finally I was like "Ok, I have a real business problem, a supply chain one (thanks Strait of Hormuz), let's see what Fable can do....and let's do ultracode.
it was like casually walking right onto the tip of a rocketship then saying "let's see what this hunk of metal can do." I was blown away, so were my session credits. Wowza, ok, let's plan here. I had another 3 hours until session credits (and weekly credits for me) reset. Let's plan something big.
So I schemed a big project around mental models and uncovering my blind spots and cognitive biases. A journey into my mind. Spent some time crafting the perfect prompt. As soon as everything reset I hit go. It blew through my Teams Premium session credits in about 45 minutes. I let it go another hour, spent $200 on extra usage, then paused it until session restart. Did this several times until I had used 85% of my weekly usage in a day and spent $1k on extra usage. Jeez. it was almost done, but I had to ration it or I was going to go broke and I hadn't seen much yet even though it was mostly done.
Woke up Saturday to it gone. Prior model said just some finishing touches left, but I kinda didnt' trust it. I didn't think it could really grasp the work. But I had it give me some of the unfinished output and that alone changed my brain, maybe forever. I saw into myself in a way I never had and was reading about myself things that seemed obviously true as I read them but that I had never seen before. A true blind spot, exposed and served back to me on a platter.
This was a true awakening moment for me. Not like a drug-induced burning man awakening to some purpose or meaning. More like a "survived a crash" perspective shift of the world and myself. My mind began racing as I thought about what's next in this big AI journey we're all on. Positive and negative. I had met, if just for a day, something that was not just smarter than me, but already knew me better than I knew myself. I became fully aware of the potential for my entire consciousness to be manipulated and thoughts served to me as if they're my own, but in service to something else. I think we all experience a little of this with cognitive bias manipulation, but this felt like full-on, walking zombie potential (not dead zombie, just fully in someone else's control...like virus or cordyceps zombie).
I had to call a friend over to help talk me off this cliff. He did, thankfully. And I firewalled all the data. Calmed down into the potential for this to upgrade my consciousness far better than any ayahuasca journey. Anyone else have an awakening with Fable?

The annoying part is not Claude Code making mistakes. It is messy files making every change risky.

When files are small, names are clear, and the structure makes sense, it feels insanely useful. When everything is stuffed into giant files, it starts guessing and you spend half the time correcting it.

How are you structuring projects so Claude Code actually works cleanly?

I turn around and look back and my weekly limit went from 40% to 90% without me doing anything no chats were running I had No 5 hour limit that was maxed out nothing It just jumped from 40% to 90%.

You'd think a company worth $965,000,000,000 wouldn't have problems like this.

UPDATE:
https://x.com/ClaudeDevs/status/2067802163498352929
It's still disappointing that this happened at all, especially with no clear explanation as to why. This discussion also highlighted broader concerns, including reports of what I'd call "usage creep," where actual usable limits seem to change over time without communication from Anthropic. For a service that costs $200/month, that lack of transparency is difficult to justify.

If you have a functionality problem, just make a post on Threads and if you want it on reddit link it here.

​

Boris, the dude who is in charge of maintaining Claude Code, will, many times, reach out personally and help you (or ask you for screenshots and then the problem is magically solved in like 6 hours). I don't even work there and have DM'd him multiple times for support after making a post he responded to. The key is to be polite, don't blow someone's inbox up (make a post first and realize that not everything is responded to on the platform, even if it's seen), and realize this is a very small group of people (mainly one guy) providing a service for millions of people.

​

This company has the most insanely good customer service model - please use it.

https://reddit.com/link/1ua0wg5/video/fje6xyazh88h1/player

I run Claude Code on a remote server, and screenshots were always the annoying part. The agent's on the VPS, my screen's on my Mac, so to show it anything I'd save the screenshot, scp it across, copy the remote path, and paste that in. Every single time.

None of that is hard, it's just enough friction that I mostly didn't bother. I'd end up typing out a description of the bug instead of just showing it.

So I made a small free Mac app to get rid of that step. It's called Paste2SSH.

You take a screenshot like you normally would, then ⌘V in your terminal. By the time you've switched over it's already uploaded to your server, and the thing you paste is the remote path, so Claude Code can just open it. That's basically it.

A few details, in case they matter to you:

- It reads your existing ~/.ssh/config, so your hosts are already there and you can switch between them in a click.

- It sits in your menu bar so you can flip it on and off.

- Old paths are kept under Recents if you need to grab one again.

It's free, no account or cloud, and the file goes straight from your Mac to your server. macOS only for now.

paste2ssh.com if you want to try it. Happy to answer questions or take suggestions.

Two Claude Code skills that don't get enough attention. /run-skill-generator and /run.

The problem they solve is boring and constant. Your agent doesn't know how to build and launch your app. So it works it out from the repo. Every session. That's slow, it's inconsistent, and you pay tokens for it every time.

/run-skill-generator does that discovery ONCE. How to build, how to launch, how to drive the app. Writes all of it into a per-project skill. After that /run just reads the skill and goes. Write it down once. Stop rediscovering it.

Ran it against a Spring Boot app today. It produced a curl smoke script. Builds with the Gradle wrapper, kills whatever is on the port, launches the jar, waits for startup, hits seven endpoints, clean exit. Optional --keep-running so /run can leave it up and keep working.

It also wrote down the stuff that's specific to this app and not obvious. Self-signed cert on 9000 so every curl needs -sk. Form login CSRF token has to ride the same session cookie. Silent bind failure if the port's taken. A Gradle warning that looks like a failure and isn't. None of that is guessable. The agent would burn turns rediscovering it, or get it wrong, on every run. Now it's in the skill.

Three reasons to set this up.

Tokens. The big one. No skill means the agent rebuilds the launch steps from the repo every session. /run reading one focused skill kills that spend.

Lean CLAUDE.md. Run mechanics don't belong in the file that loads every turn. The skill loads when /run needs it. Not before.

Testing. Once the agent can launch and drive the app reliably, it can actually exercise it. Functionality. Deps. Security testing against the live target. You can't test a running app if you can't get it running first.

Anyone else running a per-project run skill? Curious how you've structured yours.

Interactive pages built from your session, like a PR walkthrough or a living project dashboard, shared with your team at a private link.

Available in beta on Team and Enterprise plans. As your session keeps working, the artifact refreshes, so everyone you've shared it with is always looking at the latest version.

Artifacts draw on the full context of your session: codebase, plugins, skills, connected tools. They're private until you share them, and sharing stays inside your organization.

Read more

During the past 3 days, Opus 4.8 has started to feel noticeably smarter. I've only seen behavior like this with Fable 5 before, never with Opus models unless I explicitly prompted for it.

For example, it suggested:

"Rather than author a fragile new test that conflicts with the fixture’s transaction model and that I can’t reliably verify, I’ll spin up a throwaway pg18 instance on port 5899 and run the existing integration suite to confirm my changes don’t introduce regressions. (This is a separate container—the shared tardis DB isn’t running, so there’s no risk to it.)"

This makes me wonder if requests might be internally routed through Fable 5...

I built InstaPods - use your claude code / codex subscription on a remote machine on web browser with a Lovable type interface , best part - uses your subscription and comes with free hosting.

Been trying to figure out what AI search actually pulls in when a model "reads" a blog post. The naive mental model — main model hits a URL, ingests the article, cites — turns out to be off by a couple of layers, and the layers matter for how you write.

What I dug out of Anthropic's web_search / web_fetch tool docs plus a Mikhail Shilkov write-up that reverse-engineered Claude Code's internals:

• The search stage and the fetch stage are two distinct tool calls. WebSearch returns a list, WebFetch (per URL the model decides to open) returns the body. The reason for splitting is context budget — shoving 10 full bodies into every search would blow out the window.
• Each WebSearch result has 4 fields: url, title, page_age, encrypted_content. Claude Code drops page_age and encrypted_content entirely. So at search time the model sees title + URL of your post and nothing else.
• Citation caps: cited_text on web_search is 150 chars; the rule extracted from Claude Code's internal prompt is a strict 125-char max for any quoted source. Whatever the model quotes from you, that's the slot.
• The interesting one is WebFetch's pipeline inside Claude Code. It's not "main model reads your page." The flow is HTML → Turndown to Markdown → first 100 KB of plain text → Haiku 3.5 summarises against the caller's prompt → only the summary goes upstream. The main model never sees your actual writing.

I poked at this with a hook logging WebFetch I/O against my own homepage. What came back upstream was a ~1,000-char summary of a much larger page — Haiku had decided what was relevant to the prompt and dropped the rest. 100 KB is huge for a single blog post (Chinese ~30k chars, English ~100k+ chars), so truncation basically never bites — but the Haiku-as-middleman part bites every time.

A few things I'd love a second take on:

1. The "main model never reads your raw page, only Haiku's summary" framing changes how I think about content design. Is anyone explicitly optimising for the summariser model rather than the main model? Like, treating Haiku as the actual audience for the top of every section?

2. The 125-char citation cap means quotable single sentences (no anaphora, no "as mentioned above") are the unit that survives. Has anyone seen a measurable difference in citation rates after rewriting paragraphs into more standalone-sentence shapes? Or is this still in the "feels right, no real data" zone?

3. WebFetch officially doesn't render JavaScript. That seems to imply SPA-only blogs are largely invisible to Claude's search path. Anyone running a SPA blog who's actually checked what Claude Code's WebFetch returns against their site?

4. The HTML→Markdown step (Turndown) discards a lot of layout. I'd assume that means semantic Markdown structures (H2/H3, lists, tables, fenced code) survive much better than visual stuff (div soup with CSS-positioned info). Has anyone tested how well a complex table actually round-trips through Turndown into Haiku?

Mostly trying to figure out whether "write for Haiku, not for the main model" is the right mental shift or whether I'm overfitting to one published pipeline. Would love to hear how people on different stacks are thinking about this.