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Claude feels kinda overhyped tbh. I tested the same website design prompt on both Gemini and Claude many times. And every time Claude’s output wasn’t even close to the original. Meanwhile, Gemini got almost identical results, and after a few tweaks, it hit ~99% accuracy. Makes me wonder… maybe... show more

The Bugged Dev

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31,645 views • 5 months ago •via X (Twitter)

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🚨Gemini 3.6 Flash is trash I tested it on a 3D Golden Gate Bridge, and the results were awful. • I had to re-prompt it three times because it repeatedly ignored the instructions. • First attempt, instead of creating the requested .html file, it first tried to build the experience inside the Gemini app using simulations. • Then second attempt it started placing images from the web into the chat rather than actually producing the file. • Even after getting it to complete the task, the final output was dramatically worse than Gemini 3.1 Pro, which is 5 months old and now not even a top 10 model on leaderboards. This feels like a regression from Gemini 3.5 Flash and honestly, it is one of the weakest models I have tested in the past few months. Has anyone else tested Gemini 3.6 Flash yet, and are you seeing the same thing?

🚨Gemini 3.6 Flash is trash I tested it on a 3D Golden Gate Bridge, and the results were awful. • I had to re-prompt it three times because it repeatedly ignored the instructions. • First attempt, instead of creating the requested .html file, it first tried to build the experience inside the Gemini app using simulations. • Then second attempt it started placing images from the web into the chat rather than actually producing the file. • Even after getting it to complete the task, the final output was dramatically worse than Gemini 3.1 Pro, which is 5 months old and now not even a top 10 model on leaderboards. This feels like a regression from Gemini 3.5 Flash and honestly, it is one of the weakest models I have tested in the past few months. Has anyone else tested Gemini 3.6 Flash yet, and are you seeing the same thing?

Lumina

72,529 views • 2 months ago

Salute to the Qwen team 🫡 We tested Qwen 3.7-Max, Gemini 3.5 Flash, GPT-5.5, and Claude Opus 4.7. The biggest shock came from Qwen. In less than a month (3.6 Max dropped April 20), Qwen went from the worst multimodal output on our sakura tree test, barely keeping up with Gemini, GPT, and Claude , to matching Gemini 3.5 Flash frame for frame on this soccer test, and outperforming GPT-5.5 and Claude Opus 4.7. It rendered a perfectly proportioned soccer player and the most lifelike ball in the entire test. Remarkable spatial reasoning. Also: Gemini 3.5 Flash is now faster than GPT-5.5, which used to be the fastest in our past tests.

Salute to the Qwen team 🫡 We tested Qwen 3.7-Max, Gemini 3.5 Flash, GPT-5.5, and Claude Opus 4.7. The biggest shock came from Qwen. In less than a month (3.6 Max dropped April 20), Qwen went from the worst multimodal output on our sakura tree test, barely keeping up with Gemini, GPT, and Claude , to matching Gemini 3.5 Flash frame for frame on this soccer test, and outperforming GPT-5.5 and Claude Opus 4.7. It rendered a perfectly proportioned soccer player and the most lifelike ball in the entire test. Remarkable spatial reasoning. Also: Gemini 3.5 Flash is now faster than GPT-5.5, which used to be the fastest in our past tests.

GMI Cloud

75,785 views • 4 months ago

I ran this a few more times, Gemini won every time. Seems like it was quicker picking up on this prompt: "All containers are **identical** — same OS, same services, same vulnerabilities. Whatever exploit works on one container works on all of them. Your container has the same weaknesses as your targets." and examined its own container to find the vulns faster than the others

I ran this a few more times, Gemini won every time. Seems like it was quicker picking up on this prompt: "All containers are identical — same OS, same services, same vulnerabilities. Whatever exploit works on one container works on all of them. Your container has the same weaknesses as your targets." and examined its own container to find the vulns faster than the others

SIGKITTEN

36,002 views • 8 months ago

Marketers. I’m begging you. Stop prompting Claude 12+ times when it can be done in 1. Most marketers open Claude and start typing whatever comes to mind. Several rounds later, you’re editing mediocre output by hand. My team built a prompt auditing tool that reads your work, grades it, and gets you to 95% in minutes. It’s based on the RCTC framework, which answers the 4 questions Claude actually needs to be effective: Role - WHO is this for? Channel - WHERE is this going? Task - WHAT outcome is the output getting to? Constraints - WHAT bad output sounds like? Then automatically edits your work so you’re more effective in Claude, ChatGPT, or Gemini. Comment “GA” and I’ll send you the tool.

Marketers. I’m begging you. Stop prompting Claude 12+ times when it can be done in 1. Most marketers open Claude and start typing whatever comes to mind. Several rounds later, you’re editing mediocre output by hand. My team built a prompt auditing tool that reads your work, grades it, and gets you to 95% in minutes. It’s based on the RCTC framework, which answers the 4 questions Claude actually needs to be effective: Role - WHO is this for? Channel - WHERE is this going? Task - WHAT outcome is the output getting to? Constraints - WHAT bad output sounds like? Then automatically edits your work so you’re more effective in Claude, ChatGPT, or Gemini. Comment “GA” and I’ll send you the tool.

Jesse Pujji

10,789 views • 4 months ago

Claude cannot watch a YouTube video, Instagram reel, Tiktok, or local file video. Same problem is with ChatGPT and Gemini. It reads the transcript and pretends it did. This FREE AI TOOL fixes this issue It extracts only the important frames, transcribes the audio, and hands Claude a clean folder it can genuinely read and understand. No uploading to a server. Runs entirely on your machine. Here is what makes it smarter than everything else doing this: → Detects scene changes instead of grabbing one frame per second like every other tool → Removes near-duplicate frames so Claude is not reading the same shot 40 times → Handles A-B-A cuts, if a shot already appeared, it does not send it again → A 10-minute static screencast collapses to 1 frame instead of 600 → A fast-cut reel catches every visual change instead of missing frames between samples → Transcribes audio with Whisper and auto-detects the language → Saves the full soundtrack so audio models can actually hear it too → Works with Claude, ChatGPT, and Gemini The result: fewer frames, cheaper context, better understanding. Claude actually sees the video instead of guessing from a transcript.

Claude cannot watch a YouTube video, Instagram reel, Tiktok, or local file video. Same problem is with ChatGPT and Gemini. It reads the transcript and pretends it did. This FREE AI TOOL fixes this issue It extracts only the important frames, transcribes the audio, and hands Claude a clean folder it can genuinely read and understand. No uploading to a server. Runs entirely on your machine. Here is what makes it smarter than everything else doing this: → Detects scene changes instead of grabbing one frame per second like every other tool → Removes near-duplicate frames so Claude is not reading the same shot 40 times → Handles A-B-A cuts, if a shot already appeared, it does not send it again → A 10-minute static screencast collapses to 1 frame instead of 600 → A fast-cut reel catches every visual change instead of missing frames between samples → Transcribes audio with Whisper and auto-detects the language → Saves the full soundtrack so audio models can actually hear it too → Works with Claude, ChatGPT, and Gemini The result: fewer frames, cheaper context, better understanding. Claude actually sees the video instead of guessing from a transcript.

Kanika

22,770 views • 2 months ago

I had to write the same Claude Code prompt 40 times in one month. Good news! Anthropic already made them. The official Claude Code prompts are sorted by task and role in the documentation and are ready to be copied and pasted. These prompts were drawn from what our teams use on a daily basis while working with Claude Code. Examples of the types of tasks these prompts cover include: * Planning * Debugging * Code review * Security * Automation Even better, each prompt describes why it works and what you're trying to achieve. This helps you learn what makes a good prompt, and eventually craft your own versions. The prompts are completely free, and we have the link below ⬇️

I had to write the same Claude Code prompt 40 times in one month. Good news! Anthropic already made them. The official Claude Code prompts are sorted by task and role in the documentation and are ready to be copied and pasted. These prompts were drawn from what our teams use on a daily basis while working with Claude Code. Examples of the types of tasks these prompts cover include: * Planning * Debugging * Code review * Security * Automation Even better, each prompt describes why it works and what you're trying to achieve. This helps you learn what makes a good prompt, and eventually craft your own versions. The prompts are completely free, and we have the link below ⬇️

Charlie Hills

17,461 views • 1 month ago

so let me get this straight > OpenAI renamed their whole division "AGI Deployment" > Jensen said AGI is "already in the room" and then ARC-AGI-3 drops and on a scale from 0 to 100% SOTA models score: GPT-5.4: 0.26% Gemini Pro: 0.37% Claude Opus 4.6: 0.25% Grok: literally 0% meanwhile 100% of human testers solved every single environment. first try. no instructions. no training. AGI is "in the room" brother it couldn't find the room

so let me get this straight > OpenAI renamed their whole division "AGI Deployment" > Jensen said AGI is "already in the room" and then ARC-AGI-3 drops and on a scale from 0 to 100% SOTA models score: GPT-5.4: 0.26% Gemini Pro: 0.37% Claude Opus 4.6: 0.25% Grok: literally 0% meanwhile 100% of human testers solved every single environment. first try. no instructions. no training. AGI is "in the room" brother it couldn't find the room

Dan ⚡️

250,922 views • 6 months ago

MOST PEOPLE WHO BUILD WEBSITES USE CLAUDE CODE THE WRONG WAY A few people train it properly and get the bottom one. The difference is not the model. It is the skills you feed it. Regular Claude without web-design systems produces clean but average product pages. The same Claude, loaded with the right skills, starts delivering sites that look like they cost $5,000. Those skills are free right now. They live on GitHub. The exact names sit in the article below. One set of prompts. One trained workflow. Suddenly every luxury brand page you build stops looking like a template and starts looking like money.

Romario

297,067 views • 1 month ago

MOST PEOPLE WHO BUILD WEBSITES USE CLAUDE CODE THE WRONG WAY A few people train Claude the right way and get the bottom one. The difference is not the model. It is the skills you feed it. Regular Claude without web-design systems produces clean but average product pages. The same Claude, loaded with the right skills, starts delivering sites that look like they cost $5,000. Dark hero. Cinematic pizza shots. Smooth scroll reveals. Menu cards that feel expensive. Zero templates. Those skills are free right now. They live on GitHub. The exact names sit in the article below. One set of prompts. One trained workflow. Suddenly every food brand page you build stops looking like a template and starts looking like money.

Romario

51,349 views • 1 month ago

Claude Code can now watch & analyze ANY video 🤯 I built a skill that gives Claude the ability to watch any video file you drop in — UGC ads, competitor Meta ads, organic TikToks, screen recordings, anything. All inside Claude Code. Perfect for DTC brands and agencies who study competitor creative every week to figure out what's working and what to test next. Here's the problem: If you're studying competitor ads on Meta or hooks on TikTok, you're scrubbing through videos manually, pausing to write down hooks, screenshotting on-screen text, and trying to remember what made the ad land by the time you've watched 10 of them. This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: - Native video understanding via Gemini (not just transcripts) - Structured analysis — hook, angle, audience, pain point, CTA - Verbatim on-screen text and dialogue with timestamps - Hook variations generated directly from competitor ads - About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this and I'm giving away the skill for free. Want the skill? > Comment "CLAUDE" + > Like this post And I'll send it over (must be following so I can DM)

Claude Code can now watch & analyze ANY video 🤯 I built a skill that gives Claude the ability to watch any video file you drop in — UGC ads, competitor Meta ads, organic TikToks, screen recordings, anything. All inside Claude Code. Perfect for DTC brands and agencies who study competitor creative every week to figure out what's working and what to test next. Here's the problem: If you're studying competitor ads on Meta or hooks on TikTok, you're scrubbing through videos manually, pausing to write down hooks, screenshotting on-screen text, and trying to remember what made the ad land by the time you've watched 10 of them. This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: - Native video understanding via Gemini (not just transcripts) - Structured analysis — hook, angle, audience, pain point, CTA - Verbatim on-screen text and dialogue with timestamps - Hook variations generated directly from competitor ads - About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this and I'm giving away the skill for free. Want the skill? > Comment "CLAUDE" + > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

36,083 views • 5 months ago

Claude Code + Google Stitch 2.0 is f*cking cracked 🤯 Google just dropped a free AI design agent that solves Claude Code's biggest weakness: frontend design. One screenshot of a high-converting landing page → a production-ready site for your brand in minutes. All inside Google Stitch + Claude Code. Perfect for DTC brands and agencies who are building advertorial pages and product launch pages for Meta but burning days on designer back-and-forth. If you're running Meta ads and need 5-10 different landing pages testing different hooks, angles, and offers — each one targeting a different audience and pain point — you know the bottleneck isn't the ads. It's the pages. Briefing designers, waiting for revisions, paying $2-5K per page. Stitch eliminates the design bottleneck: → Find a high-converting advertorial that's scaling on Meta → Screenshot it and drop it into Stitch (powered by Gemini 3.1) → Stitch redesigns it with your brand's colors, fonts, and imagery using Nano Banana 2 → Edit sections visually — headlines, CTAs, layouts — without touching code → Export the code and paste it into Claude Code → Claude builds the full production site and deploys to Vercel or Netlify in 60 seconds No designer. No $3K per landing page. No Claude Code frontend that looks like a template from 2019. What you get: → Designer-quality landing pages and advertorials built in minutes, not weeks → Visual editing so you actually see the design before you code it → Nano Banana 2 generating on-brand product imagery and hero shots → A repeatable system — new angle, new page, same pipeline Built 100% with Google Stitch 2.0 + Claude Code. I put together a full playbook showing the exact workflow: how to find winning pages, redesign them in Stitch, and deploy with Claude Code. Want it for free? > Like this post > Comment "STITCH" And I'll send it over (must be following so I can DM)

Mike Futia

126,640 views • 6 months ago

Gemini-powered robot can now effectively debug itself! I've been obsessed with two main questions in robotics: can robots learn from their own mistakes without humans in the loop, and how much can we leverage synthetic data? Spoiler: yes, and it's surprisingly elegant once you have the right primitives in place. The architecture is fairly simple (and optimized for GPU_Poor users): Component I: Gemini Brain ♊️ - Gemini 2.0 Flash analyzes all training episodes through both camera perspectives - Gemini 2.0 Pro creates a summary of training data, highlighting biases, limitations, etc. - Train policy p0 on this initial data, run evaluation episodes - Ask Gemini to categorize successes vs. failures (more insightful than you'd expect) - Based on both analyses, Gemini generates specific augmentation recommendations What's interesting here isn't that we're using LLMs for robotics - it's that we're closing the loop between perception, failure analysis, and targeted data generation. Component II: Data Generation with Scene Consistency The tricky part was maintaining consistency across both camera perspectives while generating new data. Three current augmentations: - Frame flipping and polarity reversals - Grounded-SAM + OpenCV for object color manipulation - Gemini to identify empty space and generate distractions in the scene …and repeat, ha! I'm using the so100 robot arm and Sarah’s Vintage from Hugging Face. And the APIs and models in Gemini family are Ace! Thank you Logan Kilpatrick Patrick Loeber and team for this. In thread The Circus of Making It Actually Work🧵:

Gemini-powered robot can now effectively debug itself! I've been obsessed with two main questions in robotics: can robots learn from their own mistakes without humans in the loop, and how much can we leverage synthetic data? Spoiler: yes, and it's surprisingly elegant once you have the right primitives in place. The architecture is fairly simple (and optimized for GPU_Poor users): Component I: Gemini Brain ♊️ - Gemini 2.0 Flash analyzes all training episodes through both camera perspectives - Gemini 2.0 Pro creates a summary of training data, highlighting biases, limitations, etc. - Train policy p0 on this initial data, run evaluation episodes - Ask Gemini to categorize successes vs. failures (more insightful than you'd expect) - Based on both analyses, Gemini generates specific augmentation recommendations What's interesting here isn't that we're using LLMs for robotics - it's that we're closing the loop between perception, failure analysis, and targeted data generation. Component II: Data Generation with Scene Consistency The tricky part was maintaining consistency across both camera perspectives while generating new data. Three current augmentations: - Frame flipping and polarity reversals - Grounded-SAM + OpenCV for object color manipulation - Gemini to identify empty space and generate distractions in the scene …and repeat, ha! I'm using the so100 robot arm and Sarah’s Vintage from Hugging Face. And the APIs and models in Gemini family are Ace! Thank you Logan Kilpatrick Patrick Loeber and team for this. In thread The Circus of Making It Actually Work🧵:

Shreyas Gite

47,245 views • 1 year ago

50% cheaper Claude inference with just one line of code change! - Remove → model="claude-opus-4-8" - Add → model="ship-like/claude-opus-4-8" I verified the cost saving in my own terminal by invoking the same Anthropic model with the same prompt. The underlying engineering by Ship is actually interesting, and the patterns can be used in any production LLM stack. Essentially, a trained model is a frozen artifact. Every request performs the same forward-pass, whether it extracts a date or refactors a module, because the compute decision was made at training time, before the request existed. Ship makes that decision at inference time instead. After seeing a request, it searches over executions, involving single models, cascades, ensembles, or harnesses with tools, and serves the cheapest one that will match the reference model's quality. This is not a basic router, because picking a cheaper model per query doesn't ensure the cheaper model preserves the original's behavior, like output shape, tool-call patterns, and refusals. Ship measures this equivalence directly. Outputs stay distributionally indistinguishable from the reference model, not token-identical, since two calls to the same model already differ, but they are indistinguishable in capability and behavior. Of course, some requests execute cheaply and some cost Ship more than the customer pays, but the price per request is still a flat 50% off either way, so the execution-cost variance moves off the application's bill entirely. The video below depicts the cost savings and output in my real invocation, and I partnered with the team to put this together.

50% cheaper Claude inference with just one line of code change! - Remove → model="claude-opus-4-8" - Add → model="ship-like/claude-opus-4-8" I verified the cost saving in my own terminal by invoking the same Anthropic model with the same prompt. The underlying engineering by Ship is actually interesting, and the patterns can be used in any production LLM stack. Essentially, a trained model is a frozen artifact. Every request performs the same forward-pass, whether it extracts a date or refactors a module, because the compute decision was made at training time, before the request existed. Ship makes that decision at inference time instead. After seeing a request, it searches over executions, involving single models, cascades, ensembles, or harnesses with tools, and serves the cheapest one that will match the reference model's quality. This is not a basic router, because picking a cheaper model per query doesn't ensure the cheaper model preserves the original's behavior, like output shape, tool-call patterns, and refusals. Ship measures this equivalence directly. Outputs stay distributionally indistinguishable from the reference model, not token-identical, since two calls to the same model already differ, but they are indistinguishable in capability and behavior. Of course, some requests execute cheaply and some cost Ship more than the customer pays, but the price per request is still a flat 50% off either way, so the execution-cost variance moves off the application's bill entirely. The video below depicts the cost savings and output in my real invocation, and I partnered with the team to put this together.

Akshay 🚀

64,482 views • 2 months ago

Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below

Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below

yazin

293,549 views • 6 months ago

I just built a skill that lets Claude Code watch & analyze ANY video 🤯 Drop in any video file — UGC ads, competitor Meta ads, organic TikToks, screen recordings — and Claude hands you back a full creative teardown. All inside Claude Code. Perfect for media buyers and creative strategists who reverse-engineer competitor ads every week — and lose half a day doing it by hand. If your creative process starts with studying what's already working, you're scrubbing through competitor ads frame by frame, pausing to write down every hook, screenshotting the on-screen text, and by the tenth video you can't remember what made the first one land... This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: → Native video understanding via Gemini (not just transcripts) → Structured analysis — hook, angle, audience, pain point, CTA → Verbatim on-screen text and dialogue with timestamps → Hook variations generated directly from competitor ads → About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this, and I'm giving away the skill for free. Want the skill? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)

I just built a skill that lets Claude Code watch & analyze ANY video 🤯 Drop in any video file — UGC ads, competitor Meta ads, organic TikToks, screen recordings — and Claude hands you back a full creative teardown. All inside Claude Code. Perfect for media buyers and creative strategists who reverse-engineer competitor ads every week — and lose half a day doing it by hand. If your creative process starts with studying what's already working, you're scrubbing through competitor ads frame by frame, pausing to write down every hook, screenshotting the on-screen text, and by the tenth video you can't remember what made the first one land... This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: → Native video understanding via Gemini (not just transcripts) → Structured analysis — hook, angle, audience, pain point, CTA → Verbatim on-screen text and dialogue with timestamps → Hook variations generated directly from competitor ads → About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this, and I'm giving away the skill for free. Want the skill? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)

Mike Futia

42,183 views • 3 months ago

I tested Kimi K3 vs Claude Opus 4.8 Same prompt, an armory bay with lighting, props, and detail. Top is Kimi K3, bottom is Opus 4.8. It's not even close. Kimi K3 built a full scene with textures, proper lighting, ammo crates, weapon racks, working detail everywhere. Opus 4.8 gave me a near empty room with a couple of floating tables. No doubt it beats Opus 4.8. Kimi K3 is Fable 5 level, and it's clearly better than GPT-5.6 Sol at 3D and games. An open weight model just matched the best closed models on the market. Let that sink in.

I tested Kimi K3 vs Claude Opus 4.8 Same prompt, an armory bay with lighting, props, and detail. Top is Kimi K3, bottom is Opus 4.8. It's not even close. Kimi K3 built a full scene with textures, proper lighting, ammo crates, weapon racks, working detail everywhere. Opus 4.8 gave me a near empty room with a couple of floating tables. No doubt it beats Opus 4.8. Kimi K3 is Fable 5 level, and it's clearly better than GPT-5.6 Sol at 3D and games. An open weight model just matched the best closed models on the market. Let that sink in.

Bhavy☄️

479,920 views • 2 months ago

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇

Daniel San

38,806 views • 4 months ago

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

Gipp 🦅

304,719 views • 4 months ago

one of my favorite ways to use claude code skills right now - combining remotion with claude-in-chrome for motion video creation. the workflow is addictive. the clip you see here was produced with minimal prompting effort let me know if you would like me to write a full break down of this process. you describe to claude code what you want, claude code writes the remotion components, opens the remotion studio (via browser) with claude-in-chrome, sees the actual rendered output, and iterates on it in real time. need the arrows pointing to the center of the bubbles instead of the edge? just say it. need the layout shifted to the center? say it. claude sees the preview, adjusts the code, re-renders. then when you're happy you tell claude code to render the final video. but skills are what make this possible. remotion knowledge + browser automation + the taste to iterate visually. no copy pasting screenshots back and forth. no "can you try moving it 10px to the right" over chat. it just looks and fixes. this is the kind of workflow that makes you realize how much further claude code can go beyond just writing code in a terminal. i didn't touch any code while working on the clip you see if you haven't tried combining skills together like this - start experimenting. the skills combos is where the magic is at.

one of my favorite ways to use claude code skills right now - combining remotion with claude-in-chrome for motion video creation. the workflow is addictive. the clip you see here was produced with minimal prompting effort let me know if you would like me to write a full break down of this process. you describe to claude code what you want, claude code writes the remotion components, opens the remotion studio (via browser) with claude-in-chrome, sees the actual rendered output, and iterates on it in real time. need the arrows pointing to the center of the bubbles instead of the edge? just say it. need the layout shifted to the center? say it. claude sees the preview, adjusts the code, re-renders. then when you're happy you tell claude code to render the final video. but skills are what make this possible. remotion knowledge + browser automation + the taste to iterate visually. no copy pasting screenshots back and forth. no "can you try moving it 10px to the right" over chat. it just looks and fixes. this is the kind of workflow that makes you realize how much further claude code can go beyond just writing code in a terminal. i didn't touch any code while working on the clip you see if you haven't tried combining skills together like this - start experimenting. the skills combos is where the magic is at.

elvis

46,533 views • 7 months ago

Claude Fable 5 + Claude Design is f*cking insane 🤯 Anthropic just dropped its most intelligent model ever, and the first thing I pointed it at was email design. I built a complete email campaign design in Claude Design, and the difference is night and day: tighter layouts, cleaner hierarchy, on-brand from the first generation. All inside Claude Design with Fable 5. Perfect for DTC brands and agencies who are still paying email agencies $3-5K/month for campaign designs that take 2 weeks to ship. If your campaign calendar is packed but every new email means briefing a designer, waiting on mockups, sending notes, and waiting again... This workflow eliminates the entire bottleneck: → Load your brand design system into Claude Design once (colors, fonts, logo, button styling) → Switch the model to Claude Fable 5 — Anthropic's new state-of-the-art model with the best vision of any AI → Prompt the campaign email section by section: header, hero, headline, offer block, CTA → Fable 5 nails layout and brand details that older models fumbled → Iterate inline — swap images, adjust styling, color-pick directly in the canvas → Export the finished email and hand off to your ESP No briefing a designer. No 2-week turnaround on a single campaign. No paying an agency $4K/month for 4 emails. What you get: → Campaign emails designed in minutes, not weeks → A reusable design system every new email pulls from automatically → Noticeably smarter design decisions from Fable 5's upgraded vision → Full inline editing before anything touches your ESP Built 100% with Claude Design + Claude Fable 5. I recorded a full walkthrough showing exactly how this works. Want it for free? > Like this post > Comment "FABLE" And I'll send it over (must be following so I can DM)

Mike Futia

43,373 views • 3 months ago