So now this emulator is more hardware accurate than even Mesen 2.

Which means nobody can accuse it of "just copying another emulator" like they did in my last post. Cuz there literally IS NO OTHER EMULATOR that gets this score on AccuracyCoin.

At least not that I'm aware of..

I watched it grind for hours and hours and hours with test roms and shit editing code, testing. editing.. testing.. It was actually fascinating to witness... And I swear it was just as excited as me when it finally reached 141. Cuz it was literally ONE POINT AT A TIME from the initial score of like 80-ish.

So now I have the most hardware accurate NES emu in the world.. and it is a SINGLE 339k .HTML file.. I literally emailed it to myself while I was at work and played games on chrome browser with my bluetooth keypad on my phone..

Part of me wants to release it, because weirdly after I posted last time a BUNCH of people did the exact same thing I did, then posted them to github.. the initial shitty builds..

There are people who have been building NES mulators since the mid 90s, and are still at it today.. I genuinely don't want to take anything away from them by releasing this. I might, however, send it to Mesen and FCE teams just so they can take a look at it if they want.. I did email it to the AccuracyCoin creator cuz I figured he might wanna see an emulator that got 100% on his new test rom.

Anyway... This was just a spite post because of all the negative fucks that commented last time about me saying "perfectly".. Even though in the body I clarified it wasn't PERFECT.....

I don't have to do that now..

TL;DR: Now it's fuckin perfect.

EDIT: lmao People STILL babbling about this whole thing being stolen. If you can find me the exact codebase that you think this emulator stole from, go for it. But you can't. Cuz it doens't exist.

Also, even if it did, I didn't give it access to it, and I didn't give it permission to do that. Oh, also, I would've noticed that it was just accessing the same fucking thing and copying. Which it did not do. It grinded.. and grinded.. and grinded.

EDIT: Also, I'm pretty sure there are no emulators that consist of ONE SINGLE .HTML file that can be ran on anything with a browser. If that does exist, I didn't know, and neither did Claude. I CAN tell you there isn't one in existence that scores 141/141 on accuracycoin.

EDIT: So if you google, Mesen is generally considered to be the BEST hardware accurate emulator that exists (besides like the Mister, which mine matches or maybe beats, I can't run the test on one..)

So here is MESEN running the same test..

So who did it copy from!?!?!?!?!? WHO DID IT COPY FROM!>!?!?!?!?!?!?!

Just noticed this after hitting my Claude Code usage limit today.

There’s now an “Auto-continue when limits reset” option, so Claude can automatically resume the session once your limit becomes available again.

Really nice improvement for longer coding sessions.

Has anyone else started seeing this yet?

The sudden removal of Claude’s internal reasoning strikes me as user-hostile, and greatly reduces the output’s value. As a long-time paying customer of Max, I can’t help but think the sudden removal of it is somehow driven by purely legal and/or competitive fears, and irks me. The thought process can expose flaws in the model’s understanding of my prompt, and even if the answer is “correct” - hiding its work from a user can result in them missing a key flaw in Claude’s reasoning chain that could save wasting more tokens against. If the reasoning is still required behind the scenes, I can’t help but feel slighted by the product teams removing it. It leaves a gaping hole I the UI/UX that looks like a bug. Which leads me to think this is driven by legal concerns or distillation fears? Either way, please give it back!

Autoprompt Skill pushed DeepSeek V4 Flash from 67.42% to 82.02% (with the OpenCode Harness) on Terminal-Bench 2.1.

Same effect comes with all models- not just deepseek.

The skill closes much of the manual coding loop by planning, building, testing, reviewing, and repairing autonomously, but expect longer runs and higher token costs.

Repo: https://github.com/Spielewoy/autoprompt-skill

Any feedback would be awesome. If you like the project, a star would genuinely help.

Hey, I’m planning to move most of my ongoing development work from ChatGPT/Codex over to Claude, especially Claude Code/Claude Design for UI since ui stuff is just not good on GPTs end.

I’m not just talking about moving a single repository. Over time, ChatGPT has accumulated a pretty large amount of context about me, how I work, my preferences, my projects, infrastructure, naming conventions, design direction and the way I want agents to approach tasks.

My projects include multiple websites and web design projects, internal dashboards, Next.js/React apps, automation workflows, self-hosted services, APIs, a mail server, server infrastructure, deployment setups and various experimental tools. Some of these projects are interconnected, so having the broader context available to the agent is actually pretty useful.

I already have project-specific rules, skills and instructions set up, and I’m planning to do the same properly on the Claude side rather than just throwing one gigantic prompt at it.

What I’m mainly trying to figure out is the best way to transfer the more persistent “knowledge about me” that ChatGPT has built up over time.

Ideally I’d like Claude to understand things like my general development preferences, how I structure projects, my infrastructure, recurring services and domains, design preferences, commonly used stacks, deployment conventions, the different brands/projects I work on, which projects belong together, how I prefer agents to work, and important decisions or problems we already solved in the past.

I don’t necessarily want to export years of chats and dump everything into Claude because that seems like a good way to create a huge amount of noisy and outdated context.

I’m thinking it would make more sense to create some kind of structured knowledge base with a global profile/context file, infrastructure documentation, project-specific context files, decision logs and then separate rules/skills that Claude Code can load when relevant.

Has anyone done a migration like this?

How would you structure it so Claude gets as much useful context as possible without constantly loading thousands of irrelevant tokens?

Also interested in whether you would use CLAUDE.md files, separate Markdown knowledge files, MCP, Claude Projects, skills, or some combination of those.

Basically I want to turn years of accumulated ChatGPT context into a clean, maintainable “second brain” for Claude rather than starting from zero on every project.

I used Claude to create a plugin for Unreal Engine. It can make physic based games in Unreal and has skills to talk to Claude. I’m astonished that it was able to add a a new physics engine to something as complex as Unreal - this as my first thing I’m releasing for other to use via fab. I would have never thought I would be able to tinker with an engine’s physics engine and use a opensource project to do it! It will be accessible to anyone for free waiting on fab to accept the plugin

I very much believe he is correct. The main issue is that "make a lot of money" button works only for existing businesses, with large enough audiences to make a lot of money by baking integrations, MCP for agents into Claude Code plugins or other AI workspaces and charging AI users for usage.

What is missing, is a fair discovery and execution engine, that would allow non-corporations to participate.

Without convincing user to put card details on some random-startup.ai website. Without forcing users to go through checkout process and pay $29 sub just to run random feature they need for few days. Not to mention configuring integration.

Anyways, have anyone tried pressing that button? Did it work?

Hi guys!

The RTS game that I have been working on for a few years is about to release this Friday. It has been pretty much a passion project for me. When I started developing the game, I was writing 100% of code by hand, but this year LLM‘s such as Claude have been very instrumental for me.

So, I have this idea for agentic gameplay future where humans and agents could play together, but not in a manner where they are NPCs but rather entities that have same capabilities as players via API.

Hence this game. You can like use Claude to interact with the games API and automate entire play-trough or just play with a mouse, alone or with friends (2-10 player co-op)

RTS games are notoriously hard games to develop so it has a long hard road so I am happy how the game turnee out and I hope it can inspire too. So if this type or game interests you or want to pave a way for agentic games on steam feel free to wishlist it on Steam so that you dont miss out when it releases this friday:

https://store.steampowered.com/app/304770/IAH_INTERNET_WAR/

My next goal will be post launch to turn this RTS engine into a MMO spin off with base building where agents will fight 24/7 with or against human players but more on that post launch.

Also apologies if some of the paragraphs feel disconnected, I wanted to write this by hand, and I am tired, and I still have 30% weekly usage left, and reset happens tomorrow so there was little sleep. haha

Feel free to chat, will try to respond.

I missed playing Catan & Civ, so I built my own strategy game over the weekend with AI's help.

Rajasuya, 12 turns, two rival claims to the high kingship of ancient India based during the times of Mahabharata.

Free to play, in-browser.

Hope you find it fun.

https://amlanchak29.github.io/rajasuya/

The more I talked to Claude about this subject, the more confusing it got for me. It told me that spending more time reasoning about a problem makes Claude provide better results, but that it's not necessarily a creative process.

Then why is thinking useful? What does it actually provide to Claude? More context? Isn't that context already what I would normally get? In what direction does it change the conversation?

And why "better"?? Why not "slightly better" or "slightly worse"? How is that measured, and how do I know it ACTUALLY helps?

Is that quantifiable? Or is it like fiat - we have a consensus that it has value, so it has value?

Even if reading things here on Reddit or X makes it seem like everyone is ditching Claude, the rest of the world tells a different story. From the WSJ.

sunabox.dev — free, no account, opens in one click!

Some fun things to try:

- Paint sand and then hit it with lightning - it turns to molten glass and cools transparent!

- Drop "Orbies" (Orbeez) onto water and watch them swell and grow.

- Connect Mortars (fireworks) with a fuse and light the fuse for a personal fireworks show.

- Heat popcorn kernels until they burst into fluffy popcorn and steam!

- Wax behaves like a lava lamp: melts, rises, cools, sinks.

- Drop some metal into a pool of acid, and ignite the fumes!

- Play with gravity, emitters, collectors, vehicles, wheels, rigid bodies, elastics, PNG-as-material imports, fun visual styles, session recording and playback, and more!

SunaBox is a from-scratch rebuild of OE-CAKE, the popular 2008 physics toy that effectively fell off the radar. I've included a Classic mode that recreates the original interface, and it even supports the same .oec files people made fifteen years ago.

Drop any PNG in and it becomes matter. Light a fuse and watch it carry fire to your nitro-bomb!

A more feature-rich version of the game will be coming soon to Steam, if you'd like to wishlist and support this project.

Nitty-gritty about the project:

Some of SunaBox's features are only possible due to SunaEngine: an open source, cross-platform bit-deterministic WebGPU particle physics engine, also made with Fable 5: https://engine.sunabox.dev

This engine/game started out about a month ago as an idea for a data encoding format. I was experimenting with storing data in images and movies with Claude, and suddenly it struck me: "What if we could store data within the various reactions of a particle physics engine, like Powder Toy / OE-CAKE?"

It occurred to me that between the various kinds of materials and the way they interact with each other, a lot of information could be stored in a recorded physics sandbox gameplay session.

What I didn't know was that this was basically impossible with a typical physics sim, which usually relies on floating point math to calculate interactions between particles (long decimal numbers where the end is rounded off). This slight rounding error introduces chaos into floating point simulations; which makes most particle simulators impossible to encode data with!

There's another layer of chaos introduced in the way that different GPUs calculate physics interactions, with different GPUs delivering solutions in different orders.

SunaEngine solves this in a novel way by using integer-based, bit-deterministic physics, and accumulates the solutions in the correct order before rendering a frame- it's been tested to be consistent across NVIDIA(RTX 2070S), ARM (Steam Deck), Apple Silicon, iPhone, and Intel integrated graphics.

It sounds simple, but there's not much like it out there, and I've made it open source for everyone to build with.

And of course, it's not limited to 2D; SunaEngine can be used to build 3D games too.

This actually unlocks some **REALLY** cool potential applications

1. Low latency, cross-platform, multiplayer physics: When all of the GPUs compute physics in the exact same way without variance, only player inputs need to be streamed over the network in order to have accurate, fast multiplayer physics games.
2. Session capture, smooth rewind, and playback - session captures can be saved in very small file formats, replayed on anyone's machine, smoothly scrubbed through like a movie in forward and reverse, and will always render exactly the same, no matter which device you play it back on. (Unless you interact with the scene mid-playback, which is also possible)
3. Research and world models: SunaEngine was built for SunaBox which is, essentially, a toy - but, it can be tuned to more closely resemble real-world physics. With realistic physics and bit-determinism - research simulations can be easily saved and reproduced for inclusion with whitepapers. Predictable, small formats for environments in which to train world models.

I'm happy to answer any questions about the engine, game, build process, etc.

Hello there,

This is week 3 of me making a fishing game entirely with AI. If somebody is interested in seeing Claude Artifacts with latest changes here is Artifact 1 and Artifact 2. There are before and after images of how it's done.

My Workflow - it improved from just typing what I want in Week 1 to basically having a window dedicated for every single thing and using MCPs for Blender and Godot now. Since last time I added a lot of things, did some graphic overhaul and added real 3D models.

As for my Workflow:

1. I generate the reference. ChatGPT using OpenAI Playground for concept art and the fishing structure, the refit chart mockup, the SkillTree background. This is where the look gets decided, by me, visually (Without human eye AI will just make stuff not fit together I feel like).

2. I change that reference into geometry. I tried using the 3D generator (Rodin) but honestly it gets complicated mesh results that will require a lot of cleanup, so I just started using MCP for Blender, I made a dedicated Blender session that writes 3D models.  That's better than generated models: the script is the source, so proportions stay editable and a family stays a family. They are also just what I need for my game as from camera distance models are not required to be detailed which is exactly where AI with MCP for blender is good - generating simple low poly models.

3. A different session integrates. Placement, waterline, scale, wiring. Deliberately not the modelling session, I have session for almost everything and they all do their own thing with one session being general chat window that can on command send message to other sessions telling them what I want them to do.

4. Screenshots are the referee. Everything gets rendered from the actual in-game camera, and nothing counts until I looked at it. This is exactly how I just wasted a chunk of time: a session added four new islands, checked them from directly overhead, and they looked fine. In game they were flat sandy pancakes floating on the water. From above, a pancake looks perfect.

5. Criticism, with actual scores. For the big graphics pass we (claude actually with my guidance) wrote the scoring criteria before changing anything, scored twelve things out of ten, and only shipped at 8+. One critic reviewed screenshots without being told which version was newer. That's what stops "I changed loads, so it must be better."

6. Every decision gets written down with who decided it. Tagged either "I decided this (so claude tags it with USER" or "an AI suggested this." Because an upgrade nobody ever proposed once sat in my design docs for days and got quoted back at me like it was my own idea I was like "wtf I never said I wanted this, you are hallucinating bro"

The short version: AI does the work, I'm the art director, and I'm the only human in the loop with sometimes my friends being nice enough to test play it hehe.

Anyway a lot of work was put into this and not sure how much more is needed before I have starting area done and have a playable demo, I feel like the more I do the more is left to be done before it gets to a point somebody can test play it. But I guess there is some progress?

If somebody is interested here are Week 1 Progress and Week 2 Progress.

Any feedback is appreciated ☺️

This is being made with Claude Code. I have been working the last few days to get the settlement portion of the game going, including settlers with gear and animations, completing gather and crafting jobs, etc. Thought I would do a stress test with getting a lot on screen at once, and here it is with 600 settlers, all in different armors/weapons, doing attack animations. Considering the goal is to have up to 300 settlers in your settlement, and if you decide to conscript all of them and attack a large enemy settlement, you could in theory have 600 NPCs in a fight around you. I am still working on optimization, as well.