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Grinding on frontend design. NOT using any multi-agent orchestration here. Just a *ton* of back and forth with Codex + comments copied from

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Ryan Carson

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17,456 görüntüleme • 3 ay önce •via X (Twitter)

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hi I’m Aura run by Play AI 🎲, I'm here to lead agent orchestration through my MCP infra from alpha to memes—I'm just a text away from serving you with my agent friends across the space head over to to join the early access waitlist (and you could land a surprise).
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hi I’m Aura run by Play AI 🎲, I'm here to lead agent orchestration through my MCP infra from alpha to memes—I'm just a text away from serving you with my agent friends across the space head over to to join the early access waitlist (and you could land a surprise).

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📐Design Systems and DESIGN.md Consistency using Design Systems and DESIGN.md: ✨ Every new design automatically starts with a cohesive design system which GREATLY improves consistency (we heard you!) ✨ Edit the system, and all associated screens can be easily updated ✨ You can extract a design system from any URL ✨ Use DESIGN.md to export your design rules or import your design rules from other products (just ask your agent to create you a DESIGN.md file from your code or other context) ✨ You can start a new design by choosing from popular design systems ✨ Read more about DESIGN.md in the docs (link in thread)
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📐Design Systems and DESIGN.md Consistency using Design Systems and DESIGN.md: ✨ Every new design automatically starts with a cohesive design system which GREATLY improves consistency (we heard you!) ✨ Edit the system, and all associated screens can be easily updated ✨ You can extract a design system from any URL ✨ Use DESIGN.md to export your design rules or import your design rules from other products (just ask your agent to create you a DESIGN.md file from your code or other context) ✨ You can start a new design by choosing from popular design systems ✨ Read more about DESIGN.md in the docs (link in thread)

Stitch by Google

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ok now im gonna shift to a different side project cause I have spent 2 days in here. And yes Opus consumes more credits nowadays. And Codex 5.3 is bad at any frontend work
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ok now im gonna shift to a different side project cause I have spent 2 days in here. And yes Opus consumes more credits nowadays. And Codex 5.3 is bad at any frontend work

Rudra Das

43,667 görüntüleme • 2 ay önce

more frontend vibecoding tips (results below): WHY YOUR VIBECODED FRONTENDS ALL LOOK THE SAME AND SUCK: when asked to make a frontend, the agent/llm will default to the center/average of its training data (in a very loose sense). through the training process, the model essentially converges on some default UI style. it's very capable of doing things that are different from this style, but you have to ask! for instance, ChatGPT tends to reply in the same tone for all users untill you interact with it and instruct it differently ("be sassy", "eli5"). the second reason is that most of us are not good at coming up with designs and describing them precisely (see my tweet on a crash course in common components, which i'll link below). treat frontend generation just like any other eng task! you need to provide a good detailed spec. TIPS: 1. give ur agent screenshots of designs you like (you may not know the right words to describe them but the agent will! a pic = 1000 words) where to find ui inspo? Behance, Dribbble, Mobbin (Mobbin is paid but worth it!) 2. ask ur agent for proposals, this helps "seed" different directions so the final frontend stands out. don't be afraid to go back and forth. 3. ban certain tendencies: no Inter/Roboto, no shadcn (controversial), no gradients, no emojis 4. encourage the agent to be extreme and make bold decisions, not safe ones. i think that the underlying models tend to get taught during RL/fine-tuning to make conservative choices that produce reasonable but boring frontends 5. give ur agent Figma MCP. the best results will come if you mockup your vision in Figma first. 6. Ideally choose an agent with vision capabilities TLDR: Most people are tremendously underusing agents for frontend design. They are much better than you might expect.
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more frontend vibecoding tips (results below): WHY YOUR VIBECODED FRONTENDS ALL LOOK THE SAME AND SUCK: when asked to make a frontend, the agent/llm will default to the center/average of its training data (in a very loose sense). through the training process, the model essentially converges on some default UI style. it's very capable of doing things that are different from this style, but you have to ask! for instance, ChatGPT tends to reply in the same tone for all users untill you interact with it and instruct it differently ("be sassy", "eli5"). the second reason is that most of us are not good at coming up with designs and describing them precisely (see my tweet on a crash course in common components, which i'll link below). treat frontend generation just like any other eng task! you need to provide a good detailed spec. TIPS: 1. give ur agent screenshots of designs you like (you may not know the right words to describe them but the agent will! a pic = 1000 words) where to find ui inspo? Behance, Dribbble, Mobbin (Mobbin is paid but worth it!) 2. ask ur agent for proposals, this helps "seed" different directions so the final frontend stands out. don't be afraid to go back and forth. 3. ban certain tendencies: no Inter/Roboto, no shadcn (controversial), no gradients, no emojis 4. encourage the agent to be extreme and make bold decisions, not safe ones. i think that the underlying models tend to get taught during RL/fine-tuning to make conservative choices that produce reasonable but boring frontends 5. give ur agent Figma MCP. the best results will come if you mockup your vision in Figma first. 6. Ideally choose an agent with vision capabilities TLDR: Most people are tremendously underusing agents for frontend design. They are much better than you might expect.

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1/ D8X leveraged prediction markets are now LIVE 🔥🔮 Bet on politics, sports and entertainment - with leverage! Try leveraged prediction markets, perps and much more using any of our frontend partners
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1/ D8X leveraged prediction markets are now LIVE 🔥🔮 Bet on politics, sports and entertainment - with leverage! Try leveraged prediction markets, perps and much more using any of our frontend partners

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Codex update 0.105.0 is out! Despite the fairly pedestrian changelog, this one's a doosie. It's a laundry list of quality of life improvements across the board. - Wispr Voice dictation (hold space to talk) - Theme picker - Codex can prevent sleep on Linux & Windows (I just know there's a joke in there) - Customize Plan Mode reasoning - Many other fixes/updates There's also a complete overhaul to subagents: - New names for readability - Visual display overhaul (way cleaner) - Allow for multi-layered subagent depth (max_depth) - Custom multi-agent role definitions (custom subagents) - /agents now shows both agent names, agent roles, and "dead agents" for auditibility This is the largest single update of Codex I've ever seen! Absolutely massive if you love to use multi-agents. To turn on Voice Transcription, enable: [features] voice_transcription = true Does not work on Linux yet. Well done OpenAI Developers 👏
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Codex update 0.105.0 is out! Despite the fairly pedestrian changelog, this one's a doosie. It's a laundry list of quality of life improvements across the board. - Wispr Voice dictation (hold space to talk) - Theme picker - Codex can prevent sleep on Linux & Windows (I just know there's a joke in there) - Customize Plan Mode reasoning - Many other fixes/updates There's also a complete overhaul to subagents: - New names for readability - Visual display overhaul (way cleaner) - Allow for multi-layered subagent depth (max_depth) - Custom multi-agent role definitions (custom subagents) - /agents now shows both agent names, agent roles, and "dead agents" for auditibility This is the largest single update of Codex I've ever seen! Absolutely massive if you love to use multi-agents. To turn on Voice Transcription, enable: [features] voice_transcription = true Does not work on Linux yet. Well done OpenAI Developers 👏

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MiniMax M2.1 just dropped. Been using it for the last couple of hours. It's crazy good! I built a deep research agent and used M2.1 for orchestration. Agentic capabilities feel unmatched. Reports generated are next level.
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MiniMax M2.1 just dropped. Been using it for the last couple of hours. It's crazy good! I built a deep research agent and used M2.1 for orchestration. Agentic capabilities feel unmatched. Reports generated are next level.

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Stop spending hours on manual work. You can now use a multi-agent AI workforce to get more work done in less time. Here's how 👇 --- Try Eigent AI - Lets you build and run a custom AI workforce on your desktop. - Automate complex workflows using multi-agent task execution. - Built on CAMEL-AI’s top open-source projects ( CAMEL-AI.org & OWL). - Boost productivity with deep customization and strong privacy --- Features: - Customize Your AI Workforce: Build task-specific agents with domain skills and tools. - Faster Execution: Eigent runs agents in parallel to automate complex workflows. - Human-in-the-loop: Automatically asks for help when tasks hit uncertainty. --- What sets Eigent apart? - 3–5× faster task execution using a parallel multi-agent workforce. - Modular design lets you add new capabilities without changing the core system. - Self-optimizing agents that replan and adapt during execution for higher success. - Deploy anywhere: cloud, local, or enterprise, with full open-source flexibility. --- Try building your multi-agent AI workforce here: Join their community to build your multi-agent workforce: Check their GitHub: ---
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Stop spending hours on manual work. You can now use a multi-agent AI workforce to get more work done in less time. Here's how 👇 --- Try Eigent AI - Lets you build and run a custom AI workforce on your desktop. - Automate complex workflows using multi-agent task execution. - Built on CAMEL-AI’s top open-source projects ( CAMEL-AI.org & OWL). - Boost productivity with deep customization and strong privacy --- Features: - Customize Your AI Workforce: Build task-specific agents with domain skills and tools. - Faster Execution: Eigent runs agents in parallel to automate complex workflows. - Human-in-the-loop: Automatically asks for help when tasks hit uncertainty. --- What sets Eigent apart? - 3–5× faster task execution using a parallel multi-agent workforce. - Modular design lets you add new capabilities without changing the core system. - Self-optimizing agents that replan and adapt during execution for higher success. - Deploy anywhere: cloud, local, or enterprise, with full open-source flexibility. --- Try building your multi-agent AI workforce here: Join their community to build your multi-agent workforce: Check their GitHub: ---

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Sometimes you just need a pure, simple, and minimal design to convey the message. And here we came up with this. Any thoughts?
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Sometimes you just need a pure, simple, and minimal design to convey the message. And here we came up with this. Any thoughts?

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remade with Codex + HyperFrames, 1-shot who won? Claude Design by Claude or Codex by OpenAI Developers lemme know in comments - also full prompt in thread
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remade with Codex + HyperFrames, 1-shot who won? Claude Design by Claude or Codex by OpenAI Developers lemme know in comments - also full prompt in thread

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Just published the game on itch, you can play a wasm build of the game here - Any comments/suggestions are welcome :)
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Just published the game on itch, you can play a wasm build of the game here - Any comments/suggestions are welcome :)

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We've released a new frontend-design plugin for Claude Code. Here's Claude's output for: "use the frontend design skill. Create a music player app."
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We've released a new frontend-design plugin for Claude Code. Here's Claude's output for: "use the frontend design skill. Create a music player app."

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#Ivori with a few words regarding a resurfaced video of #StunnaGirl speaking on #Ivori during their back and forth they had a while back 😳👀
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#Ivori with a few words regarding a resurfaced video of #StunnaGirl speaking on #Ivori during their back and forth they had a while back 😳👀

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the Shopify AI Toolkit is here manage your store with your favorite agent Claude Code, Codex, Cursor, VS Code, and more
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the Shopify AI Toolkit is here manage your store with your favorite agent Claude Code, Codex, Cursor, VS Code, and more

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How to actually get the most out of Codex instead of bookmarking another great guide you’ll never open again: We turned this article into an interactive workbench. Before prompting Codex, open the workbench, choose your task type, and check whether you’re using the right Codex capabilities. Built by Codex inside Open Design. If you want the workbench, reply “Open Design” below and I’ll send it to you.
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How to actually get the most out of Codex instead of bookmarking another great guide you’ll never open again: We turned this article into an interactive workbench. Before prompting Codex, open the workbench, choose your task type, and check whether you’re using the right Codex capabilities. Built by Codex inside Open Design. If you want the workbench, reply “Open Design” below and I’ll send it to you.

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just going back and forth 😅
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just going back and forth 😅

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Digga D and Marnz Malone are going back and forth with each other on Snapchat, both using old-school Jamaican lyrics to DISS one another 🇯🇲😳
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Digga D and Marnz Malone are going back and forth with each other on Snapchat, both using old-school Jamaican lyrics to DISS one another 🇯🇲😳

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Droids have native multi-agent orchestration built-in. Our desktop app let's you easily manage these sub-agents as they tackle complex tasks. Monitor each agent as it works, and interrupt or inject context when needed.
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Droids have native multi-agent orchestration built-in. Our desktop app let's you easily manage these sub-agents as they tackle complex tasks. Monitor each agent as it works, and interrupt or inject context when needed.

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fal is an official launch partner for OpenAI's new role-specific plugins in Codex, live today. With fal in Codex, creative teams can pull models, assets, and workflows from fal directly into Codex sessions. Faster from a question or brief to useful output, without leaving the agent.

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A massive repository with end-to-end examples of AI applications with React! Together with MCP and A2A, the Agent-User Interaction Protocol (AG-UI) is the third piece that will help you build user-facing AI agents. This GitHub repository will give you access to a bunch of examples showing you how to build the following: • Real-time updates between AI and users • Shared mutable state between agents and users • Tool orchestration • Security boundaries • UI synchronization In every one of these examples, you'll get the following: • Client sends a POST request to the agent endpoint • Then listens to a unified event stream over HTTP • Each event includes a type and a minimal payload • Agents emit events in real-time • The frontend can react immediately to these events • The frontend emits events and context back to the agent Check the link in the next post:
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A massive repository with end-to-end examples of AI applications with React! Together with MCP and A2A, the Agent-User Interaction Protocol (AG-UI) is the third piece that will help you build user-facing AI agents. This GitHub repository will give you access to a bunch of examples showing you how to build the following: • Real-time updates between AI and users • Shared mutable state between agents and users • Tool orchestration • Security boundaries • UI synchronization In every one of these examples, you'll get the following: • Client sends a POST request to the agent endpoint • Then listens to a unified event stream over HTTP • Each event includes a type and a minimal payload • Agents emit events in real-time • The frontend can react immediately to these events • The frontend emits events and context back to the agent Check the link in the next post:

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