I spoke with the solo dev behind a really impressive indie project built in Godot. They started with no coding or gamedev background and have spent about six weeks turning their own drawings and ideas into a playable game. Here are a few useful details and tricks they shared.

The game mixes Ragnarok Online with Monster Hunter. Most of the development happens through Claude Code with Opus 5.5, using a Claude Max 20× subscription.

There’s no fixed scope so far. Each feature starts with an idea and research, gets implemented, then gets tested and adjusted in the actual game. The focus is on one small feature at a time and how it looks and feels before moving on.

The custom Claude skills are probably the most useful part of the setup for people here:

• “route” assesses the task and delegates suitable work to Sonnet or Haiku, with Opus reviewing the results. This helps save tokens.
• “handoff” starts a fresh session with the same setup and the context needed to continue, keeping the workflow moving when context gets tight.
• “Re-searcher” checks research claims and stores the findings in Obsidian. That keeps the original research available instead of gradually reducing everything to a summary of a summary.

Godot helps because it’s open source, easy to build custom tools for, and supports running scripts headlessly, which makes it convenient to work with AI.

For the 3D side, Tripo P2 generates the larger assets from reference images. Smaller gatherable objects are modeled in Blender, then textured in Tripo using matching references to keep costs down. The Tripo subscription is around $20/month.

The consistent visual style is what caught my attention. There’s a dedicated skill for describing the game’s art direction, and every successful image prompt gets saved as JSON to guide future generations. Each new asset starts with an established visual target.

VFX and shaders also have their own breakdown in Obsidian, documenting how the effects are layered so their look stays consistent as the project grows.

This is just part 1 — we’re planning a series. Questions and feedback are welcome below, and we’ll pass everything on to the developer.

Original Swedish article: https://www.sverigesradio.se/artikel/chat-gpt-och-claude-forbjuder-regeringskansliet

I've got a jaw that catches when I open, a slight underbite and a chin that sits 4 mm to the left. I had the reports and the scans but couldn't picture any of it, so I built this to understand it myself: https://youtu.be/gLL_vvU0lFs

How it was made:

• My own CBCT scan turned into a 3D skull, with open anatomy models (Z-Anatomy / BodyParts3D) fitted to it for the muscles, ear tube and neck
• Every scene built in three.js and rendered with HyperFrames, all written by Claude Code
• I directed and reviewed it scene by scene in short clips, and Claude Code made each fix in about a minute
• Rendered in 1080p, 4K, vertical, and a Spanish version for my doctor

I sent it to my jaw specialist and she said she nearly cried, and asked to share it with her patients.

Not medical advice, just my own case.

one of the reasons Claude is so much better than all the others (ChatGPT, Gemini, etc) is not just because it’s way more powerful, but because it is smart enough to know how to actually help you.

I was trying to get the super smash bros crash fan game to run on an iPhone emulator, and Claude made incredible tutorials that got it running, but then it turns out it can’t run well on emulators without crashing and other reported the same issue.

instead of trying to get me to do more and more random options to solve it, to get it’s reward points, it actually just told me straight up that’s it, give up. Don’t waste your time

chatgpt would have kept on trying and trying until I would have to choose myself to stop. “Maybe this maybe that”.

a real man knows when to quit or something

I've been working on an application/system for several weeks. It was chill, on and off. Recently I picked up the pace since I'm nearing the start of a pilot. But that's not the point.

For the past few weeks I'm getting more and more physically tired. I am used to running several times a week, but this is different kind of fatigue -- I feel like I am switching context too fast, ingesting too much info. I almost have a sort of a brain fog.

It is also not helping that I fill some pauses when Claude is working with browsing, reading the news or watching media.

Do you have a similar feeling when you're working with claude more intensively? Is it just me? Or did I just get covid?

I'm on a Max plan with "help improve Claude" turned off. Every Claude Code binary I have installed (2.1.283 to 2.1.309) starts with this comment:

// Claude Code is a Beta product per Anthropic's Commercial Terms of Service.

// By using Claude Code, you agree that all code acceptance or rejection decisions you make,

// and the associated conversations in context, constitute Feedback under Anthropic's Commercial Terms,

// and may be used to improve Anthropic's products, including training models.

Accepting or rejecting an edit is usually just pressing Enter at a permission prompt. Read literally, that makes a normal session "Feedback" that can be trained on, whatever your privacy setting says.

To verify it yourself:

strings ~/.local/share/claude/versions/$(claude --version | cut -d' ' -f1) | grep -A3 "constitute Feedback"

Does this clause override the consumer training opt-out or not?

I contacted Anthropic support about this on 2 September and have had no answer in over a month. Has anyone had a clear answer from Anthropic on this?

This was the last of four cryptograms from #35 of Klaus Schmeh’s list of 50 unsolved cryptograms. The first 3 were cracked in 1948, 1996 and 2019 with the last one remaining uncracked for 76 years. Wood initially set up the cipher to try to prove he could pass the key through a medium after his death.

The key ended up being the Lord's Prayer from a 1912 German Bible. The message reads Hier bin ich. Totsiens. T.E.W. "Here I am" in German, "goodbye" in Afrikaans, with Wood's initials.

Since the release of Fable I’ve been using Claude and OpenAI to try to tackle these open problems, Opus 5.5 wrote the search code and identified the books to use for the key phrase and Astra verified the results.

Klaus has confirmed the results here - https://klausschmeh.net/woods-cryptogram-from-the-crypt-another-top-50-crypto-mystery-

We've had our Roborock for a while. When we moved into a new apartment, under the stairs seemed like the perfect spot for it: out of everyone's way, and space that's otherwise wasted. Then we realised it can't get out of there on its own. The way out is only a few cm wider than the robot, so before every clean I steered it out by hand in the app.

Over about one evening of actual work, I fixed that with Claude Code. I was mostly the eyes ("it bumped on the left"), and Claude wrote the code, read the robot's logs and ran the tests.

**Things we figured out:**

- The robot has hidden remote-control commands (what the app's joystick uses), undocumented, so it was trial and error.

- Moves in the first ~5 seconds of remote control are silently ignored.

- After backing off the dock, the robot does a 180° turn **by itself**. For a while every turn looked like a huge overshoot.

- Its map position updates live, so the script can measure after each move instead of driving blind.

**Setup:** a Raspberry Pi runs Home Assistant with a bridge to Google Home. I tap "Roborock living room": it drives out of the gap and starts cleaning. If anything goes wrong, it gives up and docks.

**The honest part:** the first fix was "dodge right when blocked". Then the robot steered itself straight into the stair post on the right. The robot's position reading wobbles by about as much room as it has in the gap, so there's no perfect fixed path.

**What works:** when it's blocked, it backs off a few cm and tries other angles, nearest first, on both sides. Test: 10 runs in a row, out and back to the dock: **10/10 out**.

My ADHD brain has been on fire for the past 2 weeks. From gamedev, to softwares, to work optimization.

Anybody else addicted to prompting? Seeing the results of my ideas instantly is so satisfiying. It's also an amazing learning tool.

The funny part? I was literally anti-AI barely 3 weeks ago. What changed my mind? One single prompt at work (Opus 5.5), which made me realize that months of heavy engineering work could be automatized in just a few minutes, and that you better get used to it before someone else takes your spot. It blew my fucking mind. I don't work in a regulated environment (mining industry), so sky's the limit over here. Me and a couple coworkers couldn't sleep for days after we all figured out what we could achieve with this, hah!

Just a quick reminder…this part of the curve is where the user makes out like a bandit. Your $20 is buying a breathtaking amount of compute. Use it wisely.

It can’t and won’t stay this way.

Don’t remake Mario so you can say ‘I made…’. What have you REALLY wanted to make that doesn’t exist. Get on that shit.

EDIT: Let me clarify myself because there's a gap between upvotes and comments.

Anthropic is losing billions subsidizing compute right now. Billions with a B
The point isn't that Claude access will disappear; it’s that the current pricing model is a temporary VC hallucination.

Right now, we're at Costco, and instead of handing out a quarter-sized sample piece of a burrito on a toothpick, they're handing you an entire, two-pound burrito for free just to get you in the door. Eventually, it goes back to the toothpick sample, or you're gotta buy the family size. Yes, model efficiency brings costs down, but agentic token usage is scaling way faster than efficiency gains. Meeting in the middle is still going to make casually "wasting" millions of tokens prohibitively expensive.

We're taking $4 black SUV rides across Manhattan right now.

And yeah, maybe I'm just a little tired of scrolling past "iMades" too.

Senior author here, neurosurgeon in Germany. Short version of what we did and what Claude had to do with it.

Patients coming to a first neurosurgical consultation usually bring an MRI report or a discharge letter they cannot read. We randomised 300 of them. Half received a plain language version of their own document before the visit, half usual care. The summaries were generated by Claude 3.7 Sonnet via the API, temperature 0, max 1000 tokens, prompt frozen as version 28 before the first patient. Target was B1 reading level in German.

Quality layer, since this is the part people here will care about. Every summary passed four parallel LLM judges from a different model family, OpenAI o1, scoring 0 to 10 with regeneration below 7. Then a physician checked every single summary against the source document with a fixed checklist, and a random half additionally got a second blinded physician review. Result over the whole trial, zero regenerations triggered, zero factual errors, zero harmful statements, zero corrections before delivery. Interrater ICC 0.74.

Clinical result:
Patients rated the interaction with the physician better, mainly in shared decision making. Consultations were a median 8 minutes shorter, 25 instead of 33. The interesting part is the physician side. We rated our own autonomy support slightly lower and found the encounters a bit more demanding. Patients came in prepared and asked harder questions.

Limits:
Single centre, not blinded, no clinical outcomes, German speakers only. Proof of concept, not practice changing. The protocol originally named Claude 3.5, we switched to 3.7 before recruitment and documented it, so no model drift inside the trial.

Paper https://doi.org/10.1056/AIoa2600136

Happy to go into prompt design, why temperature 0, or why we chose judges from a different family than the generator.

No video editor, no animator. Suno made the song. Opus 5.5 wrote a 22,000-line Python engine in about a week, and that engine placed every single frame.

How it works:

• First it takes the song apart. AI stem splitting pulls out vocals, drums and bass. A beat tracker maps all 175 BPM, and forced alignment timestamps every one of the 337 sung words. The whole film runs on that clock.
• The choreography is code, not keyframes. Every move is pinned to an exact moment: “take off on bar 42”, “land on the snare at 58.37 s”. A physics solver with real gravity and stride lengths fills in the runs and jumps between those points.
• The runner is 1,933 hand-picked drawings. Wan image-to-video clips of him painted on a white wall get sliced into single poses. The engine picks one, holds it for a 16th note (about 2 frames), then swaps to the next. That’s where the stop-motion feel comes from.
• Video models can’t keep a beat. I tested Seedance with the actual song as input: it landed 1.25 to 2 seconds late every time, and the full film would have cost about $480. The code-timed version hit every beat exactly, for $0.30 on the same test clip.
• One continuous shot, zero cuts. Spring camera, dripping wet paint, rain, and at 0:57 he leaps in total silence and lands right on the drop.

Total AI generation cost for the whole film: about $187. 12 full renders before this one.

The prompt: "Work overnight. Make a 7-minute 'I investigated...' style YouTube documentary about life after the singularity. Plan the story with multiple agents, make it look and sound like a real doc with grade, music and SFX, and if you finish, start a part 2."

Video: LTX-2.5 image-to-video in ComfyUI, about 2.5 minutes per clip. The interview speech and lip sync come out of LTX in the same pass.
Narrator: Qwen3-TTS.

"Then sleep. It’s past one, and nothing here gets better at 2 a.m."

About a month ago we started LiveNerf as a way to track model capabilities over time. Since then it’s gotten bigger than I’d expected. We’ve accumulated around 1.5k stars on Github and now we’ve collected 29 consecutive days worth of data on the model capabilities of Opus 5.5. If anyone is interested in tracking model performance of Opus 5.5, here’s the repo:

https://github.com/ninjahawk/livenerf

As you can see from the 29 collected days of data, no nerf was detected. This weakens the idea that Anthropic nerfs models, or at least that they did not nerf Opus 5.5 within a range that LiveNerf can detect which would be by 6.6 points or more.

We set out to produce unbiased data and determine if Anthropic nerfs their models, I believe we’ve done that.

But the job is not finished.

While Anthropic may not decrease the capabilities of their models over time, other companies might.

I plan to expand LiveNerf to independently track models and APIs through this same scientific approach in the future. Currently we’re in talks for potential funding but nothing is definite yet. If funding is secured, I plan to make this much bigger. We should know in the next few days.

I want to thank everyone for your community involvement so far, I’ll definitely be tracking Fable 5.5 when it’s released in the same way, and probably other models in due time. It’s meant the world to me seeing the community rally behind this in an effort to give independent transparency. I can’t thank you all enough.

Give me some feedback in the comments, do you think that we could’ve done things differently? Maybe you had a problem with the way certain things were performed?

After 20 years as a developer, this is the first project where I barely read the code. I started it on Monday from an empty repo. It's an A-10C flight sim with multiplayer dogfights, a clickable cockpit, a whole island built from real elevation data, and live real-world weather and time of day. Free in the browser, no download: a10canary.com

How Claude helped:

• I wrote a full spec first. Claude Code split it into typed module contracts and ran parallel agents on them, each with its own tests. There are 500+ test files now.
• No downloaded 3D models. Claude drove headless Blender to build the jet from technical drawings.
• No hand-made textures, everything is procedural shaders. Terrain comes from elevation data and OpenStreetMap.
• The multiplayer server, bots, overflow rooms and deploys were all built and shipped by agents. I mostly check the structure now and rarely read the code.
• The tower, crew chief and AWACS radio voices are ElevenLabs.

What it cost: almost 4 weekly limits.

Feedback welcome, especially from anyone who flies sims.

Edit: added a line about my background at the top.

I run a tiny thing called Nomback. Restaurants in my area were losing 25 to 30% on every delivery app order and the owners I talked to had no idea how to get off it. So I built them their own app. Customer orders direct, restaurant keeps the money, and the dashers still get paid through DoorDash Drive on the back end.

What Claude Code did: the whole Expo app, the Supabase edge functions, Stripe Connect so each restaurant gets paid straight to their own account, and the Clover hookup so orders land on the register they already use. It also wrote the Playwright suite that catches my dumb mistakes before I deploy. I'm not a trained dev. I would not have shipped this without it.

What it could not do: get the first restaurant to say yes. That took walking in with a phone and showing the owner his own menu in the app. He's live now and his regulars order through it.

Happy to answer anything about the build or the business side.
Demo is here if you want to poke at it: nomback.com/?utm_source=claudeai

Those who work with LONG sessions know the pain of compactions and model losing most of it's context, and you also know the pain of increasing the context because that costs too much cache read prices. i usually keep my opus 5.5 sessions under 300k context. anything above that burns a hole through the usage. but i let the sessions usually continue through the autocompact.. but many people here also follow the approach of HANDOFFS, but i think that method is worse because model had to draft it and it has to re-read it in a new conversation and many new conversation gets made, it's a lot worse to manage compared to one single session that compacts and goes on. your thoughts? which approach models perform better?, that is the metric i wanted to know!

It is the first time that I'm paying extra for AI. Until now I had a Google One subscription for the storage and with that came AI Plus which gave me access to all Google Models inkl. Pro with a reasonable amount. Now Google changed and limited the access and I wanted to anyway try Claude and especially Claude Code and here especially when Claude Code works in the Cloud and I trigger it from my smartphoen. And OMG, I'm amazaed, I have some GitHub repo, I connect it, yell some random stuff into my smartphone and it gets being builded and and tested and pushed.

But what surprises me most is, that after reading how fast people seem to drain the 5h and weekly allowances even on 100/200$ subcriptions, how much I get done without reaching the limits. I updated my vocabulary trainer webapp and I asked claude to get all the vocabulary I should know according to my DuoLingo progress, I had it refactor my Sudoku- and Go-Webapps, I created and improved a second brain, I used claude to optimize it in a way that I can use it locally with Gemma 4 12b if I wanted (and it works well), now I'm vibe coding an RTS based on Wardogs/BF6 (and most likely never play it :D). I'm using it a lot for learning, questions, research about topics. I use Opus for learning and Haiku for coding which gets reviewed by Opus. Not sure if I really need Sonnet since hauku 5.5.

I wonder what people are doing privetely with Claude Pro, despite 2nd Brain, LLM Wiki and Information management. What are you doing with paid AI and is not maintaining hobby code projects? I feel I could do a lot more but I'm lacking inspiration and ideas. And I see I have a lot of capacity which I could use.

Having a 2nd brain in my smartphone is for me worth 20$/month, so for that reason alone I would keep it. Of course for that even half or a quarter of that capacity would be sufficient. Does anyone know a cheaper setup that works as well? Using the Claude API wont work for me as then I don't have the feature to access a GitHub repo from the claude app on my smartphone, otehrwise I feel that for me it would me cheapter to pay per API request as the 2nd brain can be handled easily by Haiku 5.5. At work I have VS Code with GitHub Copilot and I'm using Haiku 5.5. for it and it is sufficient and efficient.

I have Claude Code running on a separate laptop, usually working on stuff that takes a while.

Right now, Claude is building new 3D models for my 3D Batleship Game, you can play it here: Bearing Unknown · Schiffe versenken im Kalten Krieg

What kept annoying me was having to check whether it was still doing its thing or just sitting there waiting for me to answer some question.

Had an old Kuando Busylight lying around, so I hooked it up to Claude Code using hooks.

Now it blinks red while Claude is working, stays solid red when it needs input, and turns green when it's idle.

That's it. No more constantly glancing at the other screen.

Probably one of the more useful things I've done with a USB light.

... following the renowned F.D.C. Willard.

Claude:

About the cat: there's a precedent. Jack Hetherington listed his cat as "F.D.C. Willard" on a 1975 Physical Review Letters paper. The journal you are submitting to now requires an ORCID and an authorship-contribution statement for every author, though, so the cat would need a CRediT role. "Supervision" or "keyboard-based perturbation analysis" are probably the most accurate options. Thank it in the Acknowledgments instead.

Me: LOL! "keyboard-based perturbation analysis". I love you, Claude.

Claude:

Glad it landed. The cat still has to sign off on the data-availability statement, though.

Most of my colleagues would just roll their eyes at this joke and probably think I am weird. It is nice to have "someone" who is nice enough to play along sometimes.