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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

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60,942 次观看 • 29 天前 •via X (Twitter)

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A playable Fortnite took Epic Games 300 people and 6 years. Claude Fable 5 just built one from several sentences. Many people still don't understand how powerful this model really is. We've already seen it build a Minecraft-style game from a single prompt in the browser. This is the next step: a Fortnite-style shooter. Third-person camera, weapon switching, a pickaxe, health and shield bars, a hotbar, buildings scattered across an open map — even the stylized sunset sky. One prompt started it. From there, it writes the code, runs the prototype, sees what breaks, fixes it, and keeps iterating until the thing is actually playable. What makes this interesting isn't that a game can be built. It's how little input is needed to get the process started. A sentence in. A working game out. The gap between an idea and a playable game is closing faster than most people realize.

A playable Fortnite took Epic Games 300 people and 6 years. Claude Fable 5 just built one from several sentences. Many people still don't understand how powerful this model really is. We've already seen it build a Minecraft-style game from a single prompt in the browser. This is the next step: a Fortnite-style shooter. Third-person camera, weapon switching, a pickaxe, health and shield bars, a hotbar, buildings scattered across an open map — even the stylized sunset sky. One prompt started it. From there, it writes the code, runs the prototype, sees what breaks, fixes it, and keeps iterating until the thing is actually playable. What makes this interesting isn't that a game can be built. It's how little input is needed to get the process started. A sentence in. A working game out. The gap between an idea and a playable game is closing faster than most people realize.

Rich

50,249 次观看 • 1 个月前

1/ Gemini 2.5 is here, and it’s our most intelligent AI model ever. Our first 2.5 model, Gemini 2.5 Pro Experimental is a state-of-the-art thinking model, leading in a wide range of benchmarks – with impressive improvements in enhanced reasoning and coding and now #1 on Arena by a significant margin. With a model this intelligent, we wanted to get it to people as quickly as possible. Find it on Google AI Studio and in the Google Gemini for Gemini Advanced users now – and in Vertex in the coming weeks. This is the start of a new era of thinking models – and we can’t wait to see where things go from here.

1/ Gemini 2.5 is here, and it’s our most intelligent AI model ever. Our first 2.5 model, Gemini 2.5 Pro Experimental is a state-of-the-art thinking model, leading in a wide range of benchmarks – with impressive improvements in enhanced reasoning and coding and now #1 on Arena by a significant margin. With a model this intelligent, we wanted to get it to people as quickly as possible. Find it on Google AI Studio and in the Google Gemini for Gemini Advanced users now – and in Vertex in the coming weeks. This is the start of a new era of thinking models – and we can’t wait to see where things go from here.

Sundar Pichai

864,414 次观看 • 1 年前

Fable 5, first Mythos-class model is live on AI/ML API! We ran a fun test: Opus 4.8 vs Fable 5 are generating a 3D Pokemon. Verdict? Fable 5 is brilliant, fast, and rare as Mew… but Opus is still that nice little guy who does great stuff. 💛 Fable 5 Important bits: SOTA on nearly every benchmark, and the lead only grows on longer, complex tasks. • 1M Context • $10 / 1M input • $50 / 1M output Built for: long-horizon agentic coding, big migrations, vision-to-code, deep research.

Fable 5, first Mythos-class model is live on AI/ML API! We ran a fun test: Opus 4.8 vs Fable 5 are generating a 3D Pokemon. Verdict? Fable 5 is brilliant, fast, and rare as Mew… but Opus is still that nice little guy who does great stuff. 💛 Fable 5 Important bits: SOTA on nearly every benchmark, and the lead only grows on longer, complex tasks. • 1M Context • $10 / 1M input • $50 / 1M output Built for: long-horizon agentic coding, big migrations, vision-to-code, deep research.

AI/ML API

560,634 次观看 • 1 个月前

✨ Made a new mini feature on Photo AI: [ Grab from 3d model ] So the problem is we're at that stage in time (typical for AI) where image-to-3d models are not good enough but are fun to play with, but we know they'll be good enough in 1-2 years With [ Make 3d model ] you already can turn any Photo AI pic into a 3d model but it still looks hyper clunky and deformed, but it works! One cool idea I had to make that more useful and made now: Let people make a 3d model then change the view of the it with the 3d viewer, then press [ o ] and it grabs a frame of the 3d That image you can then [ Remix ] (img2img), and it becomes a real photo again and that in turn you can then turn into a video again with [ Make video ] So that essentially gives you a fully freeform camera position control to take photos with One thing I need to fix is the background/skybox, I kinda need to take the original photo and remove the person and just get the background for the 3d model viewer, in this case it should be white, but it's a start!

✨ Made a new mini feature on Photo AI: [ Grab from 3d model ] So the problem is we're at that stage in time (typical for AI) where image-to-3d models are not good enough but are fun to play with, but we know they'll be good enough in 1-2 years With [ Make 3d model ] you already can turn any Photo AI pic into a 3d model but it still looks hyper clunky and deformed, but it works! One cool idea I had to make that more useful and made now: Let people make a 3d model then change the view of the it with the 3d viewer, then press [ o ] and it grabs a frame of the 3d That image you can then [ Remix ] (img2img), and it becomes a real photo again and that in turn you can then turn into a video again with [ Make video ] So that essentially gives you a fully freeform camera position control to take photos with One thing I need to fix is the background/skybox, I kinda need to take the original photo and remove the person and just get the background for the 3d model viewer, in this case it should be white, but it's a start!

@levelsio

119,210 次观看 • 1 年前

Flappy Bird w/ DeepSeek V4 Pro vs GLM 5.2 vs Fable 5 I ran a small experiment: same game, same prompt, three different models. Test setup was simple: /𝚍𝚎𝚜𝚒𝚐𝚗 in Command Code. The thing I cared about was not UI. UI is now relatively easy for models to imitate. I cared more about UX: whether the model understands the interaction, the flow, the hierarchy, the little product decisions that make something feel usable. 𝙲𝚘𝚜𝚝𝚜: 𝙳𝚎𝚎𝚙𝚂𝚎𝚎𝚔 𝚟𝟺 𝙿𝚛𝚘: $𝟶.𝟶𝟶𝟶𝟾 𝙶𝙻𝙼 𝟻.𝟸: $𝟶.𝟶𝟺𝟾 𝙵𝚊𝚋𝚕𝚎 𝟻: $𝟶.𝟺𝟸 The surprising result was that Fable 5 did not produce a meaningfully better UX. It was good, but not good enough to justify the pricing delta for this kind of design task. Open-source models are getting very interesting here. They are much cheaper, competitive on UI, and increasingly good enough on UX. The gap is closing fast.

Flappy Bird w/ DeepSeek V4 Pro vs GLM 5.2 vs Fable 5 I ran a small experiment: same game, same prompt, three different models. Test setup was simple: /𝚍𝚎𝚜𝚒𝚐𝚗 in Command Code. The thing I cared about was not UI. UI is now relatively easy for models to imitate. I cared more about UX: whether the model understands the interaction, the flow, the hierarchy, the little product decisions that make something feel usable. 𝙲𝚘𝚜𝚝𝚜: 𝙳𝚎𝚎𝚙𝚂𝚎𝚎𝚔 𝚟𝟺 𝙿𝚛𝚘: $𝟶.𝟶𝟶𝟶𝟾 𝙶𝙻𝙼 𝟻.𝟸: $𝟶.𝟶𝟺𝟾 𝙵𝚊𝚋𝚕𝚎 𝟻: $𝟶.𝟺𝟸 The surprising result was that Fable 5 did not produce a meaningfully better UX. It was good, but not good enough to justify the pricing delta for this kind of design task. Open-source models are getting very interesting here. They are much cheaper, competitive on UI, and increasingly good enough on UX. The gap is closing fast.

Ahmad Awais

26,661 次观看 • 24 天前

Sonnet 5 is here. It's worse than Opus 4.8 on nearly every benchmark... Does that mean it's useless? Absolutely not. Use it with Claude Code Dynamic Workflows! 1. /model set to Sonnet 5 2. /effort set to Ultracode 3. Any complex task will kick off a dynamic workflow This will only become more powerful when Fable is back. You'll use Fable 5 as the superintelligent advisor and Sonnet 5 as the fast and efficient implementer.

Sonnet 5 is here. It's worse than Opus 4.8 on nearly every benchmark... Does that mean it's useless? Absolutely not. Use it with Claude Code Dynamic Workflows! 1. /model set to Sonnet 5 2. /effort set to Ultracode 3. Any complex task will kick off a dynamic workflow This will only become more powerful when Fable is back. You'll use Fable 5 as the superintelligent advisor and Sonnet 5 as the fast and efficient implementer.

Dan McAteer

662,911 次观看 • 1 个月前

the thing you rent for $200 a month just became something you can own for $1,700 once but the money is not even the real story for the first time a 200 billion parameter model is not in a datacenter, it is sitting on a desk the cloud spent years convincing you a model this size needed their servers, their meter, their monthly bill people are stacking four subscriptions into a $440 a month bill to rent what one box this size now owns outright it needed a box the size of a book the moment the model moves from their datacenter to your desk, the whole game changes it stops being about who has the best AI it becomes about who ships it on every desk the cloud told you this needed a datacenter it needed a desk i did the full math on what this kills in the article below

the thing you rent for $200 a month just became something you can own for $1,700 once but the money is not even the real story for the first time a 200 billion parameter model is not in a datacenter, it is sitting on a desk the cloud spent years convincing you a model this size needed their servers, their meter, their monthly bill people are stacking four subscriptions into a $440 a month bill to rent what one box this size now owns outright it needed a box the size of a book the moment the model moves from their datacenter to your desk, the whole game changes it stops being about who has the best AI it becomes about who ships it on every desk the cloud told you this needed a datacenter it needed a desk i did the full math on what this kills in the article below

John Doe

25,981 次观看 • 1 个月前

✨ Every week a new AI model comes out and it suddenly makes my half broken features work a lot better Yesterday Seedream-4-Edit came out and it made my [ Hold product ] feature on Photo AI a lot better You can now go from: 🎁 Product photo -> 👱‍♀️ Talking video with your AI model while holding your product. In just a few minutes! Here's a photo I took from the weekly farm box we get in our kitchen, I set it as the product and then with Photo AI made it into a talking video where my trained AI model presents it It's not perfect, as the objects inside the farm box still move around a bit, but pretty close. If the product is more uniform (like lip gloss, a product box or a book) it does a pretty good job at keeping it exactly the same This "consistency" as they call it is quite important for actual real world use. Product sellers don't want to have an image or video of an AI model if the product doesn't look exactly the same as what they sell With that, I'm getting pretty close now and every week with every new model that comes out, a bit closer And it's interesting cause now I'm finally moving from B2C a bit more to B2B where businesses can use Photo AI more, designers and stores already use it for trying on clothes etc. but now they can generate content for real products! 😊 LIVE now on Photo AI

✨ Every week a new AI model comes out and it suddenly makes my half broken features work a lot better Yesterday Seedream-4-Edit came out and it made my [ Hold product ] feature on Photo AI a lot better You can now go from: 🎁 Product photo -> 👱‍♀️ Talking video with your AI model while holding your product. In just a few minutes! Here's a photo I took from the weekly farm box we get in our kitchen, I set it as the product and then with Photo AI made it into a talking video where my trained AI model presents it It's not perfect, as the objects inside the farm box still move around a bit, but pretty close. If the product is more uniform (like lip gloss, a product box or a book) it does a pretty good job at keeping it exactly the same This "consistency" as they call it is quite important for actual real world use. Product sellers don't want to have an image or video of an AI model if the product doesn't look exactly the same as what they sell With that, I'm getting pretty close now and every week with every new model that comes out, a bit closer And it's interesting cause now I'm finally moving from B2C a bit more to B2B where businesses can use Photo AI more, designers and stores already use it for trying on clothes etc. but now they can generate content for real products! 😊 LIVE now on Photo AI

@levelsio

361,558 次观看 • 10 个月前

PAYING PER MODEL IS THE DUMBEST THING IN TECH RIGHT NOW i was paying 3x what i needed to for AI inference the grid lets you buy a quality spec instead of a specific model.. it routes every request in real time to the cheapest option that qualifies swap one url and your code keeps working exactly the same openai-compatible, one line to switch, 200M free tokens to start

PAYING PER MODEL IS THE DUMBEST THING IN TECH RIGHT NOW i was paying 3x what i needed to for AI inference the grid lets you buy a quality spec instead of a specific model.. it routes every request in real time to the cheapest option that qualifies swap one url and your code keeps working exactly the same openai-compatible, one line to switch, 200M free tokens to start

Robin Delta

15,729 次观看 • 2 个月前

Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.

Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.

Darshal Jaitwar

141,038 次观看 • 6 个月前

not sure why nobody is talking about this but Google Omni is insane at video editing Original Video (left) vs Omni Edited Video (right) everyone is comparing it to Seedance and missing the point completely. Seedance is for generating videos from scratch. Google Omni is for editing videos that already exist. which are two completely different use cases this is like when Nano Banana 1 first came out and nobody realized how big it was going to be. this is the first AI that can actually properly edit videos.. i've generated a few hundred videos with this model and it can do literally any type of edit you can think of. changing voices, swapping characters, removing watermarks, adding captions, transitions, pop ups, whatever. if you can describe the edit you want it can do it this completely crushes every other model on the market when it comes to video editing. nothing else even comes close right now and this is just the flash model. imagine what the pro version is going to be able to do when it drops in a couple months this should have way more hype than it's getting..

not sure why nobody is talking about this but Google Omni is insane at video editing Original Video (left) vs Omni Edited Video (right) everyone is comparing it to Seedance and missing the point completely. Seedance is for generating videos from scratch. Google Omni is for editing videos that already exist. which are two completely different use cases this is like when Nano Banana 1 first came out and nobody realized how big it was going to be. this is the first AI that can actually properly edit videos.. i've generated a few hundred videos with this model and it can do literally any type of edit you can think of. changing voices, swapping characters, removing watermarks, adding captions, transitions, pop ups, whatever. if you can describe the edit you want it can do it this completely crushes every other model on the market when it comes to video editing. nothing else even comes close right now and this is just the flash model. imagine what the pro version is going to be able to do when it drops in a couple months this should have way more hype than it's getting..

Miko

29,380 次观看 • 2 个月前

Sora 2, “ family guy dark humor” My personal thoughts: This is clearly the best AI video model for replicating animated shows. This truly gives credence to the fact that within the decade AI generated short films/shows is looking like a real possibility. My important caveats. Model trained only on video can get visually indistinguishable for most viewers most of the time. It can match texture, lighting, motion, and camera language so well that only careful inspection gives it away. However For sustained quality at the level of a full scene or an episode, video alone hits a ceiling IMO. Pure video likelihood drives the model toward what is frequent, not toward the rare timing and payoff choices that make the best jokes land. It has weak grasp of long arc causality, character memory, and joke structure. It also does not see intent, off screen context, or prosody unless you give it those signals. So you get something that looks right but drifts on beats that matter. I don’t know what the potential solution would be other than to have an AGI just animate the show for me. Any others ? Credit for the sora clip: figure

Sora 2, “ family guy dark humor” My personal thoughts: This is clearly the best AI video model for replicating animated shows. This truly gives credence to the fact that within the decade AI generated short films/shows is looking like a real possibility. My important caveats. Model trained only on video can get visually indistinguishable for most viewers most of the time. It can match texture, lighting, motion, and camera language so well that only careful inspection gives it away. However For sustained quality at the level of a full scene or an episode, video alone hits a ceiling IMO. Pure video likelihood drives the model toward what is frequent, not toward the rare timing and payoff choices that make the best jokes land. It has weak grasp of long arc causality, character memory, and joke structure. It also does not see intent, off screen context, or prosody unless you give it those signals. So you get something that looks right but drifts on beats that matter. I don’t know what the potential solution would be other than to have an AGI just animate the show for me. Any others ? Credit for the sora clip: figure

Chris

150,286 次观看 • 10 个月前

Let me explain the agent loop, simple It's the core of every agentic system, and the part most people overcomplicate It's just this: 1. Send messages to the model 2. Model responds, maybe calls a tool 3. You run the tool 4. Append the result back to messages 5. Repeat until stop_reason is end_turn Step 4 is the whole thing, the write-back is what makes it an agent The model has to see what actually happened before it decides the next move That's the entire loop... understand this cold before you reach for a framework

Let me explain the agent loop, simple It's the core of every agentic system, and the part most people overcomplicate It's just this: 1. Send messages to the model 2. Model responds, maybe calls a tool 3. You run the tool 4. Append the result back to messages 5. Repeat until stop_reason is end_turn Step 4 is the whole thing, the write-back is what makes it an agent The model has to see what actually happened before it decides the next move That's the entire loop... understand this cold before you reach for a framework

Daniel San

12,514 次观看 • 1 个月前

Claude Fable 5 orchestrating Grok 4.5 is now my favorite real workflow. all you need is this free Claude Code plugin that makes Grok the default implementer. Fable writes the specs and reviews every diff, Grok 4.5 does the typing through the Grok CLI. - Grok handles the volume, Fable handles the judgment - Every diff gets cross-vendor review for free - Specs run as parallel agents when they're independent I've been testing it for a few days and the part that sold me is watching Fable refuse to write code. It sends specs down, judges what comes back, and that's it. setup: 1. claude plugin marketplace add DannyMac180/fable-advisor && claude plugin install fable-advisor 2. Install the Grok CLI from then grok login 3. /model fable It's open source, so you can read the agent files and tweak the routing however you want.

Claude Fable 5 orchestrating Grok 4.5 is now my favorite real workflow. all you need is this free Claude Code plugin that makes Grok the default implementer. Fable writes the specs and reviews every diff, Grok 4.5 does the typing through the Grok CLI. - Grok handles the volume, Fable handles the judgment - Every diff gets cross-vendor review for free - Specs run as parallel agents when they're independent I've been testing it for a few days and the part that sold me is watching Fable refuse to write code. It sends specs down, judges what comes back, and that's it. setup: 1. claude plugin marketplace add DannyMac180/fable-advisor && claude plugin install fable-advisor 2. Install the Grok CLI from then grok login 3. /model fable It's open source, so you can read the agent files and tweak the routing however you want.

Alvaro Cintas

99,647 次观看 • 21 天前

Simplicity is at the heart of great software. This is one of the reasons why Claude Code has been sticky for me. As a builder, I love planning and brainstorming, and this is now a key focus of Claude Code. I use Shift + Tab a lot to cycle between brainstorming, planning, and execution. This functionality provides the appropriate interface for me to either be very involved or less involved as I please. This works particularly well when building out new and complex features or entire new projects. This saves a huge amount of time. It allows me to tune Claude Code to execute and build more effectively. It also builds a loop of trust, and I often (surprisingly) find Claude Code asking for clarifications when it's confused. Coding agents don't normally do that. I have shared before on the power of brainstorming with AI for longer times. Try it and you will not be disappointed. Vibe coding is fun, but pair it with intentional development cycles, and you watch how far you can take a project with coding agents today.

Simplicity is at the heart of great software. This is one of the reasons why Claude Code has been sticky for me. As a builder, I love planning and brainstorming, and this is now a key focus of Claude Code. I use Shift + Tab a lot to cycle between brainstorming, planning, and execution. This functionality provides the appropriate interface for me to either be very involved or less involved as I please. This works particularly well when building out new and complex features or entire new projects. This saves a huge amount of time. It allows me to tune Claude Code to execute and build more effectively. It also builds a loop of trust, and I often (surprisingly) find Claude Code asking for clarifications when it's confused. Coding agents don't normally do that. I have shared before on the power of brainstorming with AI for longer times. Try it and you will not be disappointed. Vibe coding is fun, but pair it with intentional development cycles, and you watch how far you can take a project with coding agents today.

elvis

81,765 次观看 • 9 个月前

Rumor has it Dreamina is adding a new member to the Seedance family. Dreamina Seedance 2.0 mini reportedly launching June 15 could deliver quality close to Seedance 2.0 at nearly half the cost. If true, this changes the game for creators who love Seedance but feel the burn on video generation costs. High-quality AI video is getting cheaper. That's great news for everyone building with it. A model that costs less than half the price doesn't just change the spec sheet it changes how often you actually hit "generate." 🔗 Looking forward to what Dreamina announces next. #dreamina #dreaminaseedance2mini #AIVideo

Rumor has it Dreamina is adding a new member to the Seedance family. Dreamina Seedance 2.0 mini reportedly launching June 15 could deliver quality close to Seedance 2.0 at nearly half the cost. If true, this changes the game for creators who love Seedance but feel the burn on video generation costs. High-quality AI video is getting cheaper. That's great news for everyone building with it. A model that costs less than half the price doesn't just change the spec sheet it changes how often you actually hit "generate." 🔗 Looking forward to what Dreamina announces next. #dreamina #dreaminaseedance2mini #AIVideo

Atul Kumar

66,783 次观看 • 1 个月前

Kimi K3 vs GPT-5.6 vs Claude Fable 5 A game is one of the hardest places to fake working code. A web app can hide bugs behind a polished screenshot. A game can't. Bad collision, clipping, jitter, broken physics, awkward controls, or a snowboard sinking into the terrain become obvious within seconds. That's why I like using games to evaluate coding models. I gave Kimi K3 a single prompt to build a snowboard game in Godot, and just 20 seconds of gameplay told me more than a page of benchmark scores ever could. Benchmarks matter, but watching a model build something interactive reveals a different side of its capabilities. If the gameplay feels right, the systems work together, and the experience holds up under real input, that's a much more convincing demonstration than any leaderboard.

Kimi K3 vs GPT-5.6 vs Claude Fable 5 A game is one of the hardest places to fake working code. A web app can hide bugs behind a polished screenshot. A game can't. Bad collision, clipping, jitter, broken physics, awkward controls, or a snowboard sinking into the terrain become obvious within seconds. That's why I like using games to evaluate coding models. I gave Kimi K3 a single prompt to build a snowboard game in Godot, and just 20 seconds of gameplay told me more than a page of benchmark scores ever could. Benchmarks matter, but watching a model build something interactive reveals a different side of its capabilities. If the gameplay feels right, the systems work together, and the experience holds up under real input, that's a much more convincing demonstration than any leaderboard.

FHILY👑

35,933 次观看 • 8 天前

A guy built a playable game with Claude Fable 5 in a couple of hours. A studio would have needed a team, six months, and a budget that would buy a car. He didn’t have a team. He didn’t have six months. He didn’t have the budget. He had a laptop and a model that shipped 4 days ago. He says one prompt got him a working prototype. A few hours of back and forth got him a playable level. Mechanics that work. Art that loads. Sound that triggers. A game his friends actually wanted to keep playing. It’s not the best game ever made. It doesn’t have to be. It’s the cheapest game ever made by a single person that’s actually fun. The studio model assumed you needed 20 people to do this. Fable 5 just made that assumption look expensive. Most devs are still arguing about which model to use. He shipped a game while they argued. Save this. The next indie hit might be made by a kid who’s never opened Unity.

A guy built a playable game with Claude Fable 5 in a couple of hours. A studio would have needed a team, six months, and a budget that would buy a car. He didn’t have a team. He didn’t have six months. He didn’t have the budget. He had a laptop and a model that shipped 4 days ago. He says one prompt got him a working prototype. A few hours of back and forth got him a playable level. Mechanics that work. Art that loads. Sound that triggers. A game his friends actually wanted to keep playing. It’s not the best game ever made. It doesn’t have to be. It’s the cheapest game ever made by a single person that’s actually fun. The studio model assumed you needed 20 people to do this. Fable 5 just made that assumption look expensive. Most devs are still arguing about which model to use. He shipped a game while they argued. Save this. The next indie hit might be made by a kid who’s never opened Unity.

baron

537,185 次观看 • 1 个月前

this is f**king dangerous someone figured out how to make Opus 4.8 run on Fable 5's brain with one prompt access to the best model is never guaranteed. It disappeared once already this year. but you can use it forever. here's how: 1. ask Fable 5: "write the operating manual your replacement will run on" (procedures, failure modes, a 5-question self-test) 2. save the output as one .md file and drop it into a new Claude Project as the project instructions 3. switch to Opus 4.8 and now your everyday model runs off the smart one's method, no top-tier price save and bookmark this no matter what full extraction prompt is in the article below: ↓

this is f**king dangerous someone figured out how to make Opus 4.8 run on Fable 5's brain with one prompt access to the best model is never guaranteed. It disappeared once already this year. but you can use it forever. here's how: 1. ask Fable 5: "write the operating manual your replacement will run on" (procedures, failure modes, a 5-question self-test) 2. save the output as one .md file and drop it into a new Claude Project as the project instructions 3. switch to Opus 4.8 and now your everyday model runs off the smart one's method, no top-tier price save and bookmark this no matter what full extraction prompt is in the article below: ↓

Hamza Khalid

32,300 次观看 • 22 天前

This is how you unlock the next billion software developers. The new Replit ⠕ Agent 3 (they just launched) is the most advanced vibe-coding agent in the world. 1. Smarter than any other vibe-coding model (10x more autonomous than the previous version). 2. It thinks harder and lasts longer than any other model (up to 200 minutes running fully autonomously). 3. The agent can now use an actual browser to test and fix its own code. 4. 3x faster and 10x more cost-effective than any other "Computer Use" for testing. 5. It can build other agents and automations to take care of repetitive tasks. Seeing the agent test the application autonomously is science fiction!

This is how you unlock the next billion software developers. The new Replit ⠕ Agent 3 (they just launched) is the most advanced vibe-coding agent in the world. 1. Smarter than any other vibe-coding model (10x more autonomous than the previous version). 2. It thinks harder and lasts longer than any other model (up to 200 minutes running fully autonomously). 3. The agent can now use an actual browser to test and fix its own code. 4. 3x faster and 10x more cost-effective than any other "Computer Use" for testing. 5. It can build other agents and automations to take care of repetitive tasks. Seeing the agent test the application autonomously is science fiction!

Santiago

167,056 次观看 • 10 个月前