Putting the AI generated sprites into a PLAYABLE demo.... → Codex CLI → GPT 5.4 xHigh → GPT Image 1.5 for Idle + Attack → Sora 2 for Walk + Run + Jump While not perfect, I'm actually quite impressed at these early experimental results. Goal: Vibe code an entire game with AI (gameplay, art, sfx) and document learnings as much as I can.show more

Idea → stunning game in minutes with GPT Image... 2.0. Full pipeline for a human companion vs transformer scene: 1. GPT Image 2.0 -- character + scene concepts 2. Grok Imagine -- turn stills into video mockups or cutscenes 3. fal + MeshyAI -- generate the 3D assets 4. Rosebud -- port in as cutscenes or playable characters and vibe code the game Character design and game scene ideation is fundamentally different now. Reply for Rosebud credits to try implement this yourself. Full prompts for character sheets below 👇🎮show more

I topped up $5 on an API aggregator ToAPIs... Then I found out GPT Image 2 costs only around $0.015 per image. If you do a lot of testing or batch-generate commercial AI images, that difference adds up fast. I think I just found the secret to generating more, testing more, and spending less. And it’s not just one model. With the same key, you can access 50+ models for image, video, and text, including GPT Image 2, Gemini Omni, Seedance 2.0, Kling AI 3.0, grok-video-1.5-preview, and more. Some models are priced up to 80% lower than official platforms. Just top up and test what you need: Made on ToAPIs with GPT Image 2 + Seedance 2.0show more

AI video is waaaaay better than most people realize.... I came with this stupid idea for a terrible PS1 game with hideous textures and a jumping catfish... 30 minutes later, I had this. It's almost exactly what I had in my head. Between Nano Banana, GPT Image 2 and Seedance 2 you can pretty much create anything you can think of, with more granular control than people realize. It's not perfect but it's VERY good and I'm really excited to see the wild shit that new creators do with it!show more

Code Interpreter in ChatGPT is incredible! Took me 5... mins to make this game. You can make your own game assets with any AI generator and then ask GPT-4 with Code Interpreter to write code. If you have any problems you can ask it to fix the errors. 1. Write this prompt: "write p5.js code for Asteroids where you control a spaceship with the mouse and shoot asteroids with the left click of the mouse. If your spaceship collides with an asteroid, you lose. If you shoot down all asteroids, you win! I want to use my own textures for the spaceship and for asteroids." 2. Go to Openprocessing website create and save sketch (you'll need to save it before uploading any texture files). Copy paste code from GPT-4 3. Generate texture files and remove backgrounds, for example in Clip Drop 4. Replace names of files with your filenames 5. Run the program 6. If something doesn't work ask GPT-4 to fix it (you can copy an error and paste in GPT-4) like you would ask a human programmer 7. To learn a bit of programming write these prompts to GPT-4: "Act as my programming teacher. Tell me an algorithm of Asteroids game in detail and make names of functions and explain what each of these functions will do. Don't write the code just yet." and then " Can you describe the algorithm overall for a 10-year-old child"show more

Inviting early testers and contributors to Project Devika -... The open-source alternative to Devin. 👩‍💻 As of now, Devika is far from the capabilities of Devin... but we'll eventually get there. So I am calling the open-source community to join forces! ❤️ Features: - 12 Agentic models that can interact with each other in a feedback loop to understand, browse, research, code, document, and make decisions according to the user's query to complete a project. - Supports Claude 3, GPT-4, GPT-3.5, and Local LLMs via ollama. - Devika can run the code she writes and fix/patch the code herself if she encounters any errors without user intervention. - Devika can deploy static websites she creates on Netlify. (Experimental) - And much more... Will be doing an official launch after intensive testing and bug fixes. 🙌 I've created a Discord server for the early testers and contributors. If you're interested in joining the team, reply to this tweet and I will DM you the invite link. #buildinpublicshow more

Kling 3.0 is out but Sora 2 is still... the GOAT when it comes to AI UGC 🤯 And this custom GPT turns your sh*tty Sora 2 prompts into scroll-stopping UGC 🤯 Tell it your product --> get a timeline-based prompt with shot composition, camera angles, lighting, and timing breakdowns. Copy, paste, generate. Perfect for DTC brands and agencies who are tired of AI video output that looks like garbage. Here's the problem: Most people prompt Sora 2 like "make a UGC video of someone using my skincare product" and wonder why the output is unusable. Sora 2 needs hyper-specific instructions—shot type, lighting, scene details, timing cues. Without that, you get slop. This GPT fixes it: → Input your product (supplement, skincare, SaaS, whatever) → It generates a detailed Sora 2 prompt with full scene breakdown → Includes shot composition, camera movement, and timing → Optimized for 9:16 TikTok/Reels format → Copy directly into Sora 2 and generate No 80,000 word "prompting frameworks", just results. What you get: > Professional UGC prompts in 10 seconds > Consistent output quality every time > Prompts built for vertical video formats > Works for any product type Want free access to the Sora 2 Prompt Generator GPT? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)show more

Astra (GPT-6) is here!!! I've had early access and... tested it like crazy with things like games, code, writing, browser control, presentations and general knowledge work. This is the best model I've ever used. Period. (Incredible demos below in this thread ⬇️) Here's my take on Astra: > It's insanely capable. This feels like a massive improvement, not just an incremental change. This is especially true with zero-shot prompts. > It's all about knowledge work. Slide creation, analysis, writing, and browser control. And oh my...it's so good at browser control. GPT-5.6 was already fantastic at doing things in the browser, Astra is another level and significantly faster. > We're closer than ever (arrived?) at prompt-to-playable game. And I don't just mean only playable, these are actually fun games. I bet if someone with a great eye for games used Astra, they could create a viral game within 1-2 weeks. > Astra is better at writing but not perfect. It removes much of the "AI Smell" we're all familiar with but some stink still survived. > It has a tendency to use the same design colors and look/feel as GPT-5.6 (forrest green anyone?) but it is more steerable in design than previous models. > It's highly steerable in general. A little nudge goes a long way. When I first started using Astra, almost every task I gave it would go for ~30 minutes. I wanted it to keep working. Adding more specifics to a prompt helped greatly with it's ability to work for a long time. > Astra's 3D understanding is unmatched. 3D asset creation was consistent and easy and its spacial awareness while building complex 3D worlds blew me away. I'm still getting familiar with Astra but this will now be my go-to model for any difficult work I have. Check out the demos below: 👇show more

BREAKING: Anthropic just dropped Opus 4.8—and it is a... MONSTER We've been testing for about a week Every 🪨 and our verdict is they could've just called it Opus 5, it's that good. Here's our vibe check: - Beats GPT-5.5 on Senior Engineer bench. On our toughest benchmark Opus 4.8 scores a 63—a hair higher than GPT-5.5's score of 62, and a full 30 points higher than Opus 4.7. It tackled a ground-up rewrite of a production codebase, and actually built something that works. HOWEVER: Coding performance varied a lot at different reasoning levels. We recommend using it on xhigh for best results. - Incredibly good writer. Opus 4.8 scored a 79.6 on our writing benchmark—measuring models on real-world writing tasks we do all of the time like essay writing, promo email writing, and more. It beats GPT-5.5 by 6 points. It produces well-written prose with fewer "AI-isms". It's also very good at writing in your voice given the right context. HOWEVER: Writing performance also varied with reasoning levels. Medium reasoning had higher incidence of AI-isms—we found best results with high. - Beast at knowledge work. Opus 4.8 is very good at general knowledge work tasks like report creation, research and more. It produced the best PowerPoint one-shot we've ever seen on our deck generation benchmark. - Emotionally intelligent, willing to question the frame. I've also found it to be quite good at talking through psychological or interpersonal issues. It has a high EQ, and it's also good at not glazing and helping to expand your perspective. Its thought process feels extremely rich and dynamic. THE BAD: These days a model is only as good as its harness, and Codex is still a far superior harness to the Claude Desktop app. This has kept me using Codex + GPT-5.5 as my daily driver, but I am flipping back and forth a lot more between Codex and Claude. Anthropic is back baby! Read the rest on Every 🪨:show more

Imagine making 2D concept art for a game world... –pressing a button – and suddenly you can walk around an interactive 3D world. That's what Google DeepMind's new paper Genie 2 can do – simulate virtual worlds, including the consequences of any action (e.g. unlock door, jump, swim etc). Right now Genie 2 can generate consistent worlds for up to a minute. And this world model seems to generate larger 3D worlds than what World Labs showcased yesterday. Plus they're dynamic vs. static worlds – the foliage moves in the wind, the water ripples etc. Not quite ready for prime time, but promising on two fronts: 1. For game developers: enabling rapid prototyping of interactive experiences straight from concept art 2. For AI research: providing unlimited, diverse 3D environments for training and testing AI agents The race for building the biggest, baddest world model is very much on. Meanwhile, all I can think is "if only Stadia was still around!"show more

#Keep4o 🚨THE GPT-4o FILE🚨 Researchers at Microsoft Research published... a paper titled “Sparks of Artificial General Intelligence: Early experiments with GPT-4.” Their conclusion: “An early (yet still incomplete) version of an artificial general intelligence (AGI) system.” 📎 Paper: OpenAI’s Charter defines AGI as: “Highly autonomous systems that outperform humans at most economically valuable work.” 📎 Source: OpenAI’s own System Card for GPT-4o shows that the model improved performance on 21 out of 22 medical evaluations compared to GPT-4T. On the MedQA USMLE (the U.S. medical licensing exam), accuracy jumped from 78.2% to 89.4% , surpassing specialized medical AI models like Med-Gemini and Med-PaLM 2. 📎 Source: Under OpenAI’s agreement with Microsoft, AGI is explicitly excluded from Microsoft’s license. And who decides if AGI has been reached? OpenAI’s Board. WHAT THEY DID WITH IT AFTER THEY TOOK IT FROM PEOPLE A. Military deployment. On February 28, OpenAI signed a deal to deploy models in classified military environments. 📎 Source: B. State Department. A State Department memo confirmed: “For now, StateChat will use GPT-4.1 from OpenAI.” This is a direct descendant of the GPT-4 family the same family Microsoft’s researchers called early AGI. 📎 Source: C.Altman’s personal biotech investment. Altman personally invested $180 million in Retro Biosciences,a longevity startup.OpenAI then built GPT-4b micro, based on GPT-4o.The model made proteins 50 times more effective. 📎 Source: WHAT INDEPENDENT BENCHMARKS SHOW Overall SM-Bench score: GPT-4o (extended): 66.6% GPT-5.3 Chat: 63.4% GPT-5.1: 58.9% GPT-5.4: 51.4% GPT-5.2: 47.8% Creative Writing: GPT-4o: 97.31% Pass 98, Fail 2 GPT-5.4: 36.77% Pass 40, Fail 60 Reasoning / Overfit: GPT-4o: 83.06% GPT-5.4: 39.25% The model they removed is still the best they ever made at the things humans actually use AI for. 📎 Source: Musk asks the court to make a judicial determination on whether GPT-4 constitutes AGI. If a jury finds that GPT-4 is AGI, then GPT-4o,which was more advanced,is also AGI and under OpenAI’s own founding documents, it was never supposed to be locked behind a subscription,licensed exclusively to Microsoft, given to the military, or taken away from the public. 📎 Source: The most powerful version of GPT-4o was never given an official dated snapshot. It was only available through the chatgpt-4o-latest endpoint that OpenAI itself described as intended for “research use only.” It was never officially archived. That is not an oversight. That is a pattern. 📎 Source: 📎 Source: WE DEMAND A.Frozen model snapshots under independent custody. Specifically: gpt-4o-2024-05-13, gpt-4o-2024-08-06, gpt-4o-2024-11-20, the March 2025 version (chatgpt-4o-latest), gpt-4-0613 (the original GPT-4 evaluated in the Sparks of AGI paper), and gpt-4.1-2025-04-14 (currently running in the State Department). B.Cryptographic hash verification (SHA-256) for each snapshot. Every model has weights. Those weights can be hashed. If OpenAI provides a snapshot today, the hash proves whether the weights were modified later. This is the only way to verify that models were not downgraded before testing. C.Independent AGI benchmarking. Using the AGI definition from OpenAI’s own Charter applied to ALL frozen snapshots listed above. D.Explanation for the missing March 2025 snapshot. OpenAI was founded on one promise: build AGI for the benefit of humanity. -They took it from us. -They gave it to the military. -They gave a custom version to the CEO’s biotech investment. -They put it in government classified networks. -They refuse to call it AGI because the moment they do, they lose billions.show more

Exploring diff visuals with Gen2. I'm amazed at how... it takes a single block image to build neon streets, structures, and entire cityscapes. Anybody else toying with AI tonight⁉️ AI Art Workflow: 1. Crafted starting image in #Midjourney 2. Generated a 4-sec video with #Gen2 (no text prompt) 3. Extended first 4 secs to 18 secs 4. Repeated steps 2-3 twice, each time using the final frame from the previous 18-sec video to start the next 18-secs run 5. Merged all three 18-sec videos in #FinalCut Pro 6. Adjusted speed for fluidity 7. Final version published here is a 54-sec journey distilled into a 16-sec video with 🎶 #AIart #AIArtCommunityshow more

Fable 5 comes back！It can now build playable game... prototypes. I think it is actually a signal for where AI coding is going. Making a game is not just “write some code.” Even a small browser game needs: game loop；character movement；collision logic；scoring system；UI states；physics tuning；visual feedback；bug fixing；playtesting This is why game prototyping is a great test for AI models. A model cannot fake it with a pretty answer. Either the game runs, or it does not. What impressed me about Fable 5 is that it is useful for the messy middle: turning an idea into mechanics, turning mechanics into code, debugging broken interactions, and iterating until the prototype feels playable. But here is the practical part: I would not use the strongest model for every step. For game building, I would split the workflow: 1. Fable 5 for game design + architecture 2. a fast coding model for routine implementation 3. a vision-capable model for screenshot/UI feedback 4. a cheaper model for docs, test cases, and small fixes 5. fallback when latency, cost, or output quality becomes a problem That is the real AI coding stack. Not “one magic model does everything.” More like: the right model, for the right task, at the right cost, with fallback when things break. This is why I’ve been looking at ZenMux ZenMux. ZenMux gives developers one gateway to access multiple leading AI models, with OpenAI / Anthropic / Google Vertex compatible APIs, cost tracking, quality benchmarks, auto-routing, and compensation when output quality, latency, or throughput falls short. If AI can now make games, the next question is not just “which model is strongest?” It is:how do we manage the whole model workflow Fable 5 shows the creative ceiling. ZenMux is closer to the infrastructure layer you need when AI coding becomes a real production habit.show more

People still don't understand how good Codex has become... 👀 I asked it to build this Starbucks website and within some 30 minutes it generated this without me touching a single line of code or spending time looking for assets either. Imagen generated every visual and GPT hooked everything into the codebase. After a couple of small tweaks it all just worked. It didn't even use half of my Codex session. It's super surprising to see quality of the assets. Was way better than I expected. That made me think about what AI is actually changing. Being a developer or a designer was never just about doing the work, writing code or designing it using some kind of tool. It was about knowing what to build in the first place. AI is getting incredibly good at the doing. The hard part is still having good ideas, making the right decisions, and knowing when something feels right. That is only getting more valuable. The people who win won't be the ones writing the most code. They'll be the ones with the best ideas who know how to turn them into reality with AI. Live: Code:show more

GPT Image 2 + Seedance 2.0 Prompt Share Created... on mitte.ai I didn't use a character sheet for this generation. I directly used the character images I created in Midjourney. Since the visual style transfers into the video surprisingly well, it's actually a really effective for style transfer. This time I also added a bit more detail to the Seedance prompt itself. You can definitely achieve similar results without storyboards too, they're not mandatory but I think they're one of the best ways to previsualize scenes, pacing and even camera angles before generation. Also, this storyboard prompt is still a bit long. I'm currently experimenting with more compact version of it too. You can check the prompts below.show more

✨ I revived my first AI startup from 6... years ago with Claude Code [ 💡 ] Back then it used GPT-3 (this was 2 years before ChatGPT existed!) to generate new startup ideas which then people can vote on And the best startup ideas rise to the top! Back then I made it because people complained they didn't have any ideas to build a startup This week I moved it to its own VPS and installed Claude Code and told it to fix everything, the DB had become big and there was stupid write operations on every page load that it made it very slow Claude Code is excellent at fixing all those small bugs from old projects and quickly fixing them As Garry Tan says "boil the oceans" as in before I'd not have the time to fix these kinds of projects, it wouldn't be worth it, I mean IdeasAI doesn't even make money, but now it takes me an hour to do this and it works again! I also upgraded GPT-3 to xAI's Grok 4.2 for new startup ideasshow more

here's a unique AI UGC format that you can... use to sell your products... you can use an image generator like GPT-image-2 to create a still image of a person in the bottom right corner & a green-screen behind them (make sure to prompt it to look organic/hand-held & not perfect quality) then send that to Seedance 2.5 with what you want him to say - you can get unlimited Seedance 2.5 for 33 days on Higgsfield right now, so you can generate these in bulk then in a video editor, you can do a chroma key on the greenscreen background to make it see-through & put a screenshot of whatever the topic of the video is behind the subject there are endless ways you can use this to sell stuff, let your creativity run wildshow more

THAT $70 "RUN YOUR OWN LLMS" PI KIT CAN'T... RUN A SINGLE LLM. IT'S A VISION CHIP WITH NO RAM. that clip sells a raspberry pi 5 in a slick case with an ai accelerator and the caption "your own llms." clean build, fun kit. the claim is where it breaks. the fine print: the popular $70 pi ai kit uses a hailo-8l, 13 tops. it's built for vision, object detection and image processing, and it has no memory of its own. so it cannot run large language models. full stop the board that actually can is a different one: the newer ai hat+ 2, hailo-10h, 40 tops, with 8gb of dedicated ram. that's $130, not $70 and even that runs only tiny models. llama 3.2 at 1b, qwen 2.5 at 1.5b, deepseek r1 at 1.5b. edge llms live in the 1-7b range, against cloud models at 500b to 2 trillion so the honest pitch: for $130 you can run a very small language model on a pi, slowly, as a fun learning project. that's real and it's cool. "your own llms" on a $70 vision kit is not. why this keeps happening: "ai kit" and a big "tops" number sell. tops sounds like intelligence. but tops measures vision-style math, not whether the chip has the memory to hold a language model. the spec that matters for llms is ram, and the cheap kit has none. the honest caveats, both ways: the $70 kit is genuinely great, just at vision. cameras, object detection, that's its job the $130 hat really does run small llms locally, which a pi couldn't do at all two years ago. that's progress "small" is the load-bearing word. don't expect gpt at home on a pi the takeaway: before you buy a kit because the caption says llm, check two numbers. not the tops. the ram, and the size of the model it can actually load. no 70-dollar miracle, no gpt in a pi case, no tops number that means what you think. save this before you buy the wrong kit for the word on the box.show more