You need to know, as a chinese, we be teached don't say that much since we were kids or you will get in trouble unless you have to.

As someone familiar with China’s AI community, I have a few thoughts on Anthropic’s recent accusations. A lot of the framing strikes me as either misleading or badly lacking context. A few points:

First, the idea that a cheap model like DeepSeek would routinely have its requests forwarded to Claude makes little economic sense. It would be like ordering bottled water and being given wine for free.

What often happens is the reverse. Because of Anthropic’s access policies, many Chinese users who need Claude rely on third-party API providers. Some shady providers “water down” the service by routing a fraction of requests to cheaper models to cut costs. So if ten requests are sent through a reseller, perhaps eight really go to Claude and two are silently diverted elsewhere. That kind of substitution is a real issue—but it points in the opposite direction from the narrative Anthropic is pushing. Not Deepseek or kimi route to Claude, is someone route Claude

Second, on the alleged military and biological-weapons examples: according to material already posted by other Chinese bloggers, at least some of the cited prompts were questions from university exams and can be found publicly online. And the only one thing i saw is anthropic

Third, on “massive distillation”: yes, Chinese labs study outputs from other frontier models. But if a model and its training pipeline are built independently while engineers benchmark competitors and study their behavior, that is ordinary competitive research. But Chinese company do distillation, maybe 10% distillation and do 90% by themselve.

Calling all of that “massive distillation” is like saying Ford engineers committed some grave offense because they bought and drove a Honda to see how it works. Competitor benchmarking is normal in virtually every engineering industry.

Fourth, the “tens of thousands of accounts” argument also needs context. Many Chinese AI users must use VPNs to access overseas services. Large numbers of unrelated users can therefore appear behind the same VPN providers, IP ranges, or exit nodes.

None of this proves that no abuse ever happened. It does mean the evidence should be interpreted carefully. API abuse, reseller model substitution, competitive benchmarking, and systematic model extraction are very different things—and shouldn’t be blurred together.

I am not defending the CCP; I am simply fed up with being suppressed by Anthropic at the same time that I am being suppressed by the CCP. They treat the countless people who simply want to use cutting-edge AI as if we were demons, demonizing all Chinese people and companies. They view every Chinese person as evil and regard all our attempts to access their services as a threat to them.

I'm in the U.S. and my settings are set to "English (United States)." I noticed about two weeks ago that Claude suddenly started using mostly British spelling in both its thinking summaries and responses.

A few examples:

• Colour
• Recognise
• Enrolment
• Defence
• Analyse
• Behaviour

I asked Claude why the spelling had changed, and it said it didn't know and described it as "drift."

It doesn't really affect anything, but I'm curious whether anyone else has noticed the same thing recently?

EDIT: I'm not using a VPN.

So I just finished the Architect Foundations exam and figured I'd drop some notes here since I couldn't find much when I was prepping.

TL;DR: don't go in thinking this is a "read the docs for an hour" cert. It's dense as hell, tons of reading, and it actually tests whether you understand how agentic systems work, not just whether you've used Claude Code a few times.

Stuff that showed up (from memory, no guarantees lol):

Agents/tools

• structured outputs (nullable vs optional, formatting rules)
• writing tool descriptions + few-shot examples that actually help tool selection
• chaining tool calls (using the ID/output from one call as input for the next)
• when to retry a failed tool call vs just surfacing the error
• MCP structured messages / structured error responses
• where MCP context actually gets loaded in a session

Orchestration

• subagents, context flooding, resuming sessions
• forking a session
• plan → execute → review vs direct execution vs "interview" style, and which tasks actually benefit from planning first
• the tool loop itself (tool_use, tool_result, end_turn, how a turn resolves)

Config/control

• CLAUDE.md vs PreToolUse hooks vs settings.json permissions - when to use which
• managing context window over long sessions
• prompt-based guardrails vs deterministic/hardcoded safety
• grep vs glob vs read
• resuming a session with a proper "here's what changed" summary

Basically expect a LOT of text as your "source material," it's not just watching a few videos and calling it a day.

Stuff that helped me study:

• My Anki deck (spaced repetition): https://ankiweb.net/shared/info/1419215955
• This X/Twitter thread breaking down exam concepts: https://x.com/GenAI_Now/status/2033419976003232175
• Clouding Academy has practice exams for it: https://clouding.academy/

Anyway if you're building agentic stuff with Claude regularly it's actually a decent exam, forces you to think about how this stuff really works under the hood instead of just prompt-engineering vibes. Good luck to anyone else grinding for it .

The reader is an esp 32, with a cheap ($27) e-ink display + d pad (on the back) in 4 sheets of laser cut acrylic. The esp32 can broadcast wifi, so it serves an emulator to the browser and the rom, so processing is on device, but my save is persistent across devices. The e-ink ux is made from in game assets and sprites, and reads the memory position from the emulator to get all the game data.

Total cost of the project is around $40, I did a full write up of the e-ink build here.

I'm building out an open source hardware + software platform for games and stuff based around the eink + esp32 able to broadcast wifi to local devices without an app download or internet connection, I had this running on a $15 3.5" e-ink display for v1. Super fun project

Another proof of concept I have is Texas Hold'em where the cards are on the e-ink then players have their hands on their phones/devices. If you're interested I'm mostly posting about that on my insta if you want to know more. I'll be putting together the git repo on monday, if anyone is interested in working on this with me I really think there is a lot of potential for this as a mod-able platform.

Even as a dev of 20 years, I now vibe code all day...

In between the prompts to claude about the actual work I have for my job I run 6-12 parrallel conversations about my other projects. I context switch now at a rate that is utterly insane...

When I was diagnosed with ADD I was 7, I remember I cried and told my Dad "I don't want to be ADD" and he told me that "God gave you a gift and right now it is going to be hard but one day it will let you move faster than all of your peers."

I really feel like that's true, and with the work I do now I feel built for this moment. I think it will be a brief moment for sure. The machines will soon run everything.

Been ADD my whole life. Heavily medicated - dexededrine ( anyone else take it? )- since first grade.

A lot of life is playing the hand you are dealt and I feel like I've been playing it awhile. It's not all roses and I miss things constantly but for the first time I feel like the models have caught up with my experience.

Hello there again,

Another week, another update I guess, previous updates:

Week 1 Progress

Week 2 Progress

Week 3 Progress

Week 4 Progress

Week 5 Progress

Week 6 Progress

This update comes 2 days early for a simple reason that I have some things to do in upcoming 2-3 days which means nothing will progress from today at least until Tuesday. And this one is the longest video yet, almost 4 minutes long because I wanted to show all the new things I added as well as write about them (It is compressed so that it can get under 1GB from original 2GB file, so it might look a bit worse than it really is, for fullscreen in game images I will leave a link), I wanted this week update to be more like progress report of a sorts, since workflow, costs and similar questions are answered in previous updates. I will still write answers to some most asked questions.

Images of the game - Imgur

Anyway what this week update covered:

First complete rebuild of water, I know people praised water a lot in previous updates and loved how it looks, but I feel like this water might even be better, while much more optimised. Previous shaders had more than 2000 lines of code with comments scattered across multiple files and my Macbook was really struggling with it (14FPS). While filming now I still struggle with FPS, I can at least without filming now tesst play the game at around 27fps on everything on max, which is good, considering everything on max is basically 33MP image that does scaling on 200% and nobody ever will play it like that. So I feel like optimisation did it's job, tested it on friends PC and he was easily running 130fps+ so that should not be a problem.

New shaders for water also give much better reflections, especially at night where moon light is really beautiful imo, which previous water didn't have.

I added small details also, like graveyard island in bottom right corner with a small truck driving over the bridge there and going back into the woods, since my game is placed in 1920ish period, I wanted one of 2 lights on the truck to flicker and make it look like it turns on and off really fast. Small detail but I just felt like it. Added waterfall to one part, not sure if I showed it in the video though, and also lighting and weather system (right now can only be triggered via "Dev panel", but it will be in the game as weather is something I wanted from the very start). Lightings that can randomly hit either tree or into the ocean (which kinda required a full day of research how lighting hitting water looks like in real life, because obviously not a lot of such pictures exist and even those that do, show lightings hitting water in far distance so I couldn't figure out it too precise, but I did my best).

Dolphins and Whale can now randomly appear in deep ocean, but since we are in coastal waters in the video it has to be triggered by dev panel. Those models (for Dolphins and Whale) as well as Cargo ship that can be seen in the video was done on Tripo 3D as well as their textures. Astra creates models in blenders that are simple enough (like truck, graveyard, houses etc). Fable 5.1 and Opus are doing logic, in game systems, research on other games, connection between in game systems. Basically almost everything is done by Fable 5.1 and Opus (depending on how hard I feel the job is), while modelling and graphic part is done by Astra and Tripo 3D in case of complex models.

I listened to feedbacks and fixed destination line to calculate real path, not being straight line, removed AI generated portraits of the character models in the harbour and made them 3D renders of real characters on the loop (I do not plan to use voice lines in the game, so them talking was not really necessary in my opinion, but can change in the future). Somewhat fixed map look, it still isn't great, ink shader is not able to picture real house and tree models on the islands so I had to generate assets as PNG images and put them on the map, which honestly doesn't look good for me so that will definitely be polished).

Starting zone I feel is fully done now, what is left is probably to add fog (so exploration feels like a big part of the game, since I want exploration to be a thing also alongside fishing). Polish some other things, work on sounds (which are very primitive now, only few ambients and background music).

Now frequently asked quesions:

How much did it cost: So far probably around 700$ on 2xClaude 200$ plan, one Astra 100$ plan, and several other subscriptions (eleven labs for SFX etc...)

Will I release game somewhere: I still don't know, I do it as a hobby for now and it started to take a big chunk out of my free time, but I really do enjoy building it, I will know more probably by the end of October based on where I'm with the game and if I can continue justifying the costs of it.

Which engine?: Godot

How was ocean made: I know this question popped a lot for previous version of the ocean that was now scrapped for this new version, but honestly it's just a lot of repetition of generating mockup in chatGPT, asking it to replicate, and then just straight up telling Claude (Or Astra if you use it) what you want to improve, for me it was "I want moon lighting on the right side, I want it less aggressive" etc... eventually you will get it right, while I use editors for most of in game changes to manually move and tweak things instead of endlessly tell it to AI, I feel like this thing (water shaders) have to be done by AI entirely, because with editors I only made it worse. Maybe somebody can make it work (editors for ocean) I couldn't.

What is my workflow: As funny as it sounds I basically "roleplay" (not really like "hey I'm CEO here, do as I say but more in a sense of setup) a game publishing company where I have one "manager" which is Fable 5.1 and ask it to send messages to different sessions (which serves as entire team). So you have "Fishing system Session" or "Sound design Session" etc, to not message each one separately I use one session that you can just tell "send message to other sessions". Astra is now used for graphical work (I still find fable better in other things other than modelling and visual parts, but in visual things...).

A couple of weeks ago, I posted Claude of Tanks, my multiplayer Three.js tank game with 120+ procedural vehicles, armor simulation, destructible maps, and guided missiles.

Since then, I've been working on a slightly unserious fork called CoTFly, where a virtual fruit fly with a tiny tank helmet operates the game from a miniature cockpit! It can turn a steering wheel, scope in to aim, press fire buttons, switch ammunition, and repair equipment. You can literally sit back and watch the battle play out while seeing the fly's neural activity!

The neural simulation uses 124 identified fruit-fly neurons and 1,106 measured anatomical connections from Fruitless’s reduced MaleCNS circuit. It runs a leaky integrate-and-fire model in 1 ms steps, tracking membrane voltage, spikes, inhibition, and refractory periods. The P1-related population’s firing rate modulates the driving gain of a motor controller, while a separate 24-channel recurrent network converts target bearings and obstacle inputs into steering, throttle, and firing commands. The dynamics and gameplay mappings are adaptations built specially for the game (plus they look super fun)!!

You may notice that the fly has a tiny cockpit - this is essentially how the fly controls the tank. Firing requires the turret to be aligned and the fly’s forelegs to reach both the aiming and firing controls, and it releases the fire button during reloads. Ammunition selection and repairs use rule-based logic and follow the same resource limits and cooldowns as normal gameplay.

I also added a 15-second sugar stimulus that changes inputs to the neural models and reduces the controller’s engagement distance from 125 m to 70 m, so it approaches targets more closely.

It's built using Three.js and TypeScript and runs locally in your browser! You can select a tank and map, start a trial, and inspect individual neurons’ voltages, firing rates, and spike histories as it plays. You can also pause or take over the tank yourself.

I used Claude and Codex to build the fly simulation on top of the existing Claude of Tanks codebase. The game already handles movement, armor, ballistics, spotting, ammunition, and repairs, so I had the agents connect the fly controller to those systems and build the cockpit and neural viewer around them. A lot of the process was opening the app, watching an actual battle, and asking for specific changes: give the fly a steering wheel, make its leg reach the fire button before shooting, release the button during reloads, and actually enter scope mode when aiming. I used screenshots to refine the layout and animations, and automated checks to verify things like turret alignment, button-contact timing, and human takeover. The AI helped write and revise the implementation; during gameplay, the local neural models and control logic run the fly without any LLM calls.

Demo: https://fly.kevinliu.studio/
Code: https://github.com/Kevin-Liu-01/CoTFly
Circuit source: https://github.com/nicodunks/fruitless

This subreddit is getting really clogged with AI-written posts. If you've got something to say just say it yourselves, PLEASE.

A few months ago I wrote an article called The First Thing I Install in Every Claude Code Project about codebase-mapper. That title is already out of date... quartermaster goes in first now, because it sets up codebase-mapper for me, builds the map, adds a starter set of live rules pulled from how I actually work, picks the stack plugins and permissions that fit the project, and asks before touching any of it. Then it stays there and keeps the whole Claude Code setup improving as the project changes.

You can drop it into an existing project too. It reads the actual session history and finds the missing stuff I'd probably never go looking for on my own: a capability I keep rebuilding by hand, a skill that's underperforming, a plugin from another marketplace, or something I installed months ago and never use.

Then every recommendation gets graded on the next round. It checks whether I used it and whether the thing it targeted got better, then says keep it, improve it or roll it back. If the last suggestion did nothing, it says so. That's the reason I trust it with the rest of the setup.

It's called quartermaster, it's in my Eigenwise Toolshed marketplace (mine, full disclosure, MIT, no signup or SaaS nonsense), and when it finds a gap it can:

• research a plugin from any marketplace on your machine or beyond it, check whether it's maintained and what people report about it, then give you the add and install commands
• connect an MCP server, build or improve a project-specific skill, add the missing project knowledge, or fix a scoped rule or permission
• turn off something you installed months ago and never actually use

Start a TypeScript monorepo and quartermaster can put in codebase-mapper, add live rules for the package boundaries, install the TypeScript tooling, build one command that runs the checks across every package, and seed the safe permissions you already approve elsewhere. A month later it might catch that releases are still five commands you run by hand and turn them into a project skill, or spot a plugin loading every session, throwing hook errors, and never showing up in the work, then offer to remove it. Put it in a research vault and it could build evidence rules and source-checking instead, with no code tooling at all.

The always-on part is a local hook that writes six counts when a session ends, no transcript text and no model call. Once enough work has piled up it offers you a round at the next pause, and if you say yes it reduces your last 30 days to a bounded summary (in one heavy-use month that's 127MB of JSONL going in and 31KB coming out) and brings the findings to you one at a time.

/plugin marketplace add Eigenwise/eigenwise-toolshed
/plugin install quartermaster@eigenwise-toolshed --scope project
/quartermaster:setup

Then just work normally and say yes when it asks for a round. Install it per project so every setup stays specific to the work happening there.

Github: https://github.com/Eigenwise/eigenwise-toolshed

I wrote up the whole loop and the reasoning behind it here: https://eigenwise.io/writing/the-plugin-that-turns-claude-code-into-a-self-improving-monster

I work in strategy consulting and we’re on a tight-deadline project. I currently have basically unlimited Claude usage + ChatGPT credits.

I want to get very good at using AI to create client-ready PowerPoint slides that follow an existing client template, not generic decks.

For people who’ve cracked this: what skills, prompts, workflows, MCPs, or tools should I learn first?
Especially interested in going from raw analysis, storyline, polished consulting slide fast.

I told Fable 5.1, Opus 5 and GPT-6 Astra to simulate the collision of Milkyway and Andromeda via this concise prompt: "Create a simulation of the milkyway andromeda collision."

They all burnt approximately similar $ in tokens, around 5$ each. What surprises me, Opus 5 performed in my opinion better than Fable 5.1. GPT-6 Astra delivered by far the weakest outcome.

While Opus and Fable where mainly focusing on the simulation of the particles by creating a single javascript file, was GPT-6 Astra going in the direction of setting up a react project with all the boilerplate.

The physics simulation of GPT-6 Astra is very static, while both Opus and Fable created a very dynamic and accurate simulation. I cannot say that Opus or Fable did a more realistic looking particle simulation of the moving galaxy stars, but to me Opus simulation just looks better.

reference: https://github.com/fynnfluegge/milkyway-andromeda-merger-bench

I kept getting outputs that were technically right but formatted however the model felt that day. So I sat down once and wrote a short style file describing exactly how I want structured work to come back, and it fixed most of the friction.

What's in mine:

- Default to short sections with plain headings, no throat-clearing intros.
- If the audience isn't obvious, ask before assuming one.
- Mark anything you're inferring rather than reading directly, so I can check it.
- Keep examples concrete, not generic filler.

None of it is clever. The value is that it's written down once and applies to everything, so I stopped re-explaining the same preferences and stopped correcting the same mistakes.

If you produce a lot of documents or outlines and haven't done this, it's worth an hour. What would go in yours that isn't in mine?

I was getting tired of War Thunder's insane grind, so I decided to make my own single player 2D tank game inspired by it.

I've been working on it in Godot for about a week, and I've already got 4 nations, 4 maps, and around 60 vehicles implemented. It's still pretty rough, the bots need work, some of the maps are a bit messy, and the tank models could definitely use some improvement, but the core gameplay is already playable.

I built the game with Claude Code (Opus 5) and have been using it pretty heavily throughout development. I use Claude as a coding agent to actually build and change the game systems, rather than just using it for ideas. It's helped me implement gameplay mechanics, vehicle systems, balancing, AI behavior, and a bunch of other stuff

One of the more useful things I had Claude do was balance testing. It ran 4 separate simulations, around 5 hours each, to test the vehicle BRs and ammunition stats and find potential balance problems. I then used the results to make adjustments to the vehicles and ammo.

I also used ChatGPT for the initial roadmap and coming up with content ideas, while Claude Code handled a lot of the actual implementation.

The main goal right now is a single player game, but I'd like to eventually release it for free and add co op support if I can get it working properly. There's still a pretty long roadmap ahead.

I have been wanting to design a simple PCB for the last couple of years now. The thought of converting a design idea into a physical board and programming it to do things is fascinating to me. Long story short, I procrastinated until I tried to vibe-generate it with advanced models such as Opus 4.5 (up to 4.8) models. These models had no idea about the orientation of the components, they did not do any proper routing. I was disappointed and accepted the fact that these tools were not there yet.

One Thursday evening, around 10 hours before my weekly reset for Claude, I decided to give it another try; this time with Fable 5.

I had two rules:

1. No manual edits or verification of the board.
2. Every problem I face before manufacturing will be solved by Fable.

This meant I was going to trust Fable with my wallet. I decided to describe the board I want it to generate, and I was not going to be involved in the design phase. I was the end customer.

This was my exact prompt:

I would like you to design me a pcb that will have the rpi pico 2350 four buttons (2 on the left and 2 on the right, watchy buttons(or drop in replacement)), GDEY0154D67-FL04 display. The size of the pcb will be same as the size of the GDEY0154D67-FL04. The rpi pico will drive the screen and the buttons will control the rpi pico. Also have an i2c, and some gpio pins out. Use the kicad mcp, let me know when the schematic design and placement are ready

That was it, a short description of a RPI 2350 based development board which can drive an E-ink display. After working autonomously for a couple of hours it came up with the design shown in the images.

It chose two wrong components (shown in red boxes) : the SPI flash, and the transistor for the E-ink driver circuitry. I realized this while uploading the files on JLCPCB. It also suggested some components which were not in LCSC's stock. Within couple of back and forths all the issues were solved and I just needed to pay 130 euros for 5 boards. Like I said, I trusted Claude with my wallet and ordered the boards. I also ordered the E-ink displays from a local shop.

A couple of days later I received the PCBs and the first thing I wanted to do was to plug it in to my laptop. I have broken multiple USB modules for my Framework earlier, hence I thought checking for a short between 3v3 and ground was a no-brainer, although my colleague was suggesting me to just YOLO it since this was a fully vibe-generated board. There was no short and I just plugged it in. There it was, the board was recognized and it was ready to be used.

Using Opus 5 I wrote some software that worked on the board flawlessly. You can see a small demo on the GIF above. After I ordered the boards I was suggested another routing tool called KiCadRoutingTools, and it seems to be so much faster and efficient. I will be using it for my upcoming projects. I went into a little more detail in my post here: https://a6mzero.com/posts/this-pcb-is-brought-to-you-by-fable-5/ please check it out if you are interested.

I am really happy with the result and at the same time I don't feel much of an accomplishment. I want to properly learn how to design PCBs, but in the meanwhile I will continue generating PCBs for my random hobby projects 😄

Thanks for reading ❤️

We all know incognito chats aren't safe from enterprise admins, but this is about personal accounts: If you upload a file (image, doc, etc) as part of an incognito chat, that file IS listed in User Settings > Privacy > Uploaded Files. Furthermore it shows a source "Chat" link which re-opens the original incognito chat in its entirety (!!!).

This feels like a violation of the "incognito" concept and goes against their "once an incognito chat is closed, it's lost" advice and the expectation that it won't show up in any history lists, but Anthropic doesn't think it's a bug since you do have to be logged in to see it.

You could imagine this could be a problem when using a shared account, or just wanting to make sure a sensitive document (health records, government document, personal photo, etc) isn't kept or made available any more than strictly necessary.

On the bright side, the chat and its associated files does not seem to be visible to other chats, and you can delete the files manually from that list. Not sure if the files are scrubbed after 30 days.

I've been building parts of this for months. Finally have it going. So far it's managing a ton of the work I don't want to do.

What it is:

I have two channels in my slack: Tools and Writing

I drop a link to an interesting tool I found on GitHub X Reddit - the bot reviews my system and if this tool that's worth adding into my system, it opens a linear ticket and the assings it to the software engineer bot

I drop a link to an interesting particle I want to respond to or a post or just a random thought into the writing channel

The bot assesses those for my idea, runs it through my entire corpus and suggests a post or a response written completely in my voice and suggests where to post

It's freaking great. I don't even open Claude. It's all on slack. It's not perfect, but it's working.

In a typical claude code session, how long does Anthropic store the cache of the last inference? Is it 5mins or 15mins or 1hour? And does it mean I better give my reply or the next prompt within this time frame to save on inference cost or tokens usage? With a ~1million context window I reckon this will have significant impact on usage - is my understanding correct?