Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Anti-Slop is a rules document that stops AI coding agents from shipping the same generic UI, gradients, glassmorphism, marketing buzzwords. It's not a style guide, it doesn't tell the agent what colors or fonts to use, it filters out slop through 36 rules and a checklist with one verification... show more

GitHub Awesome

55,500 subscribers

130,200 просмотров • 2 месяцев назад •via TikTok

Наука и технологии #github #opensource

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Your AI coding agent doesn't have a design opinion. That's why everything starts looking the same. UI UX Pro Max gives your agent real design direction, layouts, typography, colors, UX rules, and stack-specific guidance. The wild part? There is no AI inside. Just a huge design knowledge base running locally. Pair it with Impeccable to stop the AI slop. #AI #Coding #ClaudeCode #UIDesign #DevSwarm

Your AI coding agent doesn't have a design opinion. That's why everything starts looking the same. UI UX Pro Max gives your agent real design direction, layouts, typography, colors, UX rules, and stack-specific guidance. The wild part? There is no AI inside. Just a huge design knowledge base running locally. Pair it with Impeccable to stop the AI slop. #AI #Coding #ClaudeCode #UIDesign #DevSwarm

Codename Poshan

36,400 просмотров • 3 месяцев назад

- AI document editing with auditable changes - your AI coding agent writes the least code that works - Anti-AI-slop design skill for Claude, Codex - reusable animated components - CTA design inspiration

- AI document editing with auditable changes - your AI coding agent writes the least code that works - Anti-AI-slop design skill for Claude, Codex - reusable animated components - CTA design inspiration

Csaba Kissi

11,634 просмотров • 2 месяцев назад

"The model is no longer the product. Codex, Perplexity Computer, or Claude Code - all are orchestration system. It takes a model and pairs it with an agent harness. What is an agent harness ? The rules for how the agent loops around" - Aravind Srinivas

"The model is no longer the product. Codex, Perplexity Computer, or Claude Code - all are orchestration system. It takes a model and pairs it with an agent harness. What is an agent harness ? The rules for how the agent loops around" - Aravind Srinivas

Rohan Paul

120,488 просмотров • 4 месяцев назад

Your AI coding agent says “done.” Where’s the proof? ProofShot lets agents test your UI in a real browser and show the evidence: video, screenshots, console errors and server logs. It bundles everything into a report that can go directly into a GitHub PR. Works with Claude Code, Cursor, Codex and other shell-based agents.

Your AI coding agent says “done.” Where’s the proof? ProofShot lets agents test your UI in a real browser and show the evidence: video, screenshots, console errors and server logs. It bundles everything into a report that can go directly into a GitHub PR. Works with Claude Code, Cursor, Codex and other shell-based agents.

0xMarioNawfal

47,383 просмотров • 1 месяц назад

We built TasteSkill to help people create better frontends with AI. Today we're introducing TasteCode A desktop app for your coding agents, with a dedicated Design Mode that avoids slop and instead produces good UI It is opensource and you can use it with your existing AI subscriptions!

We built TasteSkill to help people create better frontends with AI. Today we're introducing TasteCode A desktop app for your coding agents, with a dedicated Design Mode that avoids slop and instead produces good UI It is opensource and you can use it with your existing AI subscriptions!

Leon Lin

136,861 просмотров • 1 месяц назад

OpenCode is a free, open-source coding agent that does the same job as Claude Code or Codex with any model. It has 220,000 stars on GitHub. Install it with one command and run it in your terminal or the desktop app. Build mode writes code and runs commands. Press Tab for Plan mode, which only reads your project and asks before it changes anything. Follow for more AI news like this. #opencode #claudecode #codex #opensource #ai

OpenCode is a free, open-source coding agent that does the same job as Claude Code or Codex with any model. It has 220,000 stars on GitHub. Install it with one command and run it in your terminal or the desktop app. Build mode writes code and runs commands. Press Tab for Plan mode, which only reads your project and asks before it changes anything. Follow for more AI news like this. #opencode #claudecode #codex #opensource #ai

morenicksaraev

24,600 просмотров • 8 дней назад

I just shipped a free crash course on building AI agents without writing a single line of code. In 20 mins, I take one problem through the full agent development lifecycle using just a coding agent. You can use Codex, Claude Code, Antigravity or anything else.

I just shipped a free crash course on building AI agents without writing a single line of code. In 20 mins, I take one problem through the full agent development lifecycle using just a coding agent. You can use Codex, Claude Code, Antigravity or anything else.

Shubham Saboo

12,705 просмотров • 2 месяцев назад

This GitHub repo lets your AI agent take apart any app here's a GitHub repo with over 300,000 stars called REA (Reverse Engineer Anything), and it changes how you learn from other software. REA is two things: a set of instructions for your AI agent, and an MCP server. MCP is the connector that lets an agent like Claude Code use other tools. REA connects your agent to the same analysis tools researchers use, like Ghidra, and it works on websites, desktop apps built with web tech, Android apps, .NET apps and even old games. How you use it: ask your agent a question about a feature. It calls REA, gets back the evidence (the function, the file, the network call, and what it still doesn't know), explains it in plain words, then builds and tests your own version. Setup is one sentence in Claude Code: "Set up REA from github.com/morluto/rea." You review the plan, approve it and restart. The rules matter. Use it on software you own or are allowed to examine. It doesn't hand you anyone's original code, and copying code, getting around paid features or using cracked tools is out. The repo says so plainly. #aiagents #claudecode #mcp #reverseengineering

This GitHub repo lets your AI agent take apart any app here's a GitHub repo with over 300,000 stars called REA (Reverse Engineer Anything), and it changes how you learn from other software. REA is two things: a set of instructions for your AI agent, and an MCP server. MCP is the connector that lets an agent like Claude Code use other tools. REA connects your agent to the same analysis tools researchers use, like Ghidra, and it works on websites, desktop apps built with web tech, Android apps, .NET apps and even old games. How you use it: ask your agent a question about a feature. It calls REA, gets back the evidence (the function, the file, the network call, and what it still doesn't know), explains it in plain words, then builds and tests your own version. Setup is one sentence in Claude Code: "Set up REA from github.com/morluto/rea." You review the plan, approve it and restart. The rules matter. Use it on software you own or are allowed to examine. It doesn't hand you anyone's original code, and copying code, getting around paid features or using cracked tools is out. The repo says so plainly. #aiagents #claudecode #mcp #reverseengineering

Professor Glitch

19,500 просмотров • 23 дней назад

Introducing multi-agent orchestration in Oz, with support for Claude Code, Codex and the Warp Agent. Use /orchestrate to delegate complex tasks across a team of agents, locally or in the cloud.

Introducing multi-agent orchestration in Oz, with support for Claude Code, Codex and the Warp Agent. Use /orchestrate to delegate complex tasks across a team of agents, locally or in the cloud.

Warp

1,198,899 просмотров • 5 месяцев назад

Turn any website into an AI-readable design system. Here's how: Google recently introduced the DESIGN.md specification: a file that helps AI agents understand a product’s design system. So we built a free tool for designers. Paste any website URL and Masumi’s DESIGN.md Generator extracts the brand’s colors, typography, components, spacing, and visual rules into an editable DESIGN.md file. Your designer can review it, tweak it, and hand it to Claude Code, Cursor, Codex, or any AI coding agent so the generated UI stays on-brand. Links below

albina

26,087 просмотров • 6 месяцев назад

UI Skills are now easier for agents. Introducing UI Skills CLI. ask Codex, Cursor, Claude Code, or any agent to use the CLI, like: "use `npx ui-skills start` to fix the motion in this dialog" it finds the best design-engineering skill for the job and uses it as context

UI Skills are now easier for agents. Introducing UI Skills CLI. ask Codex, Cursor, Claude Code, or any agent to use the CLI, like: "use `npx ui-skills start` to fix the motion in this dialog" it finds the best design-engineering skill for the job and uses it as context

Ibelick

62,979 просмотров • 5 месяцев назад

Introducing the first agent-to-agent code review solution: Qodo’s Agentic Toolbox. Get full codebase context, your coding rules, and AI code review, brought directly to your coding agent. Available now for Claude Code, OpenAI’s Codex, and Kiro, with support for any MCP-compatible client.

Introducing the first agent-to-agent code review solution: Qodo’s Agentic Toolbox. Get full codebase context, your coding rules, and AI code review, brought directly to your coding agent. Available now for Claude Code, OpenAI’s Codex, and Kiro, with support for any MCP-compatible client.

Qodo

51,865 просмотров • 2 месяцев назад

There's a built-in agent inside Claude Code you can invoke just by telling Claude to use the claude-code-guide agent Save this... you'll need it It's not a local file in your project. It's a built-in subagent defined in Claude Code's system itself. It answers questions about Claude Code CLI, the Agent SDK, and the Claude API. It uses Glob, Grep, Read, WebFetch, and WebSearch, but can't edit or write files. Its only job is to answer questions.

There's a built-in agent inside Claude Code you can invoke just by telling Claude to use the claude-code-guide agent Save this... you'll need it It's not a local file in your project. It's a built-in subagent defined in Claude Code's system itself. It answers questions about Claude Code CLI, the Agent SDK, and the Claude API. It uses Glob, Grep, Read, WebFetch, and WebSearch, but can't edit or write files. Its only job is to answer questions.

Daniel San

57,445 просмотров • 8 месяцев назад

We made Agent Design real before Claude Design became part of Claude Code. Open Design brings a live, editable artboard to any agent. Find it in the Codex Plugin Directory, or use the prompt below for Claude and other AI agents. ↘️

We made Agent Design real before Claude Design became part of Claude Code. Open Design brings a live, editable artboard to any agent. Find it in the Codex Plugin Directory, or use the prompt below for Claude and other AI agents. ↘️

OpenDesign

42,759 просмотров • 2 месяцев назад

I gave Claude Code, Codex, and Cursor a self-improving, shared MEMORY. Now my coding agents learn from each other, and their knowledge follows me wherever I work. Coding agents work in silos. Your corrections in Cursor don't carry over to Claude Code, and skills built in Codex don't automatically transfer to other harnesses. So switching tools often means starting from scratch. What if every coding agent could learn from everything you've already done? I invited Justin D'Souza, co-founder of Asymptote Labs, to show me how to make this possible with Beacon, a 100% open-source memory layer for coding agents. We set it up live, explored real coding sessions, and watched Beacon turn past work into reusable knowledge. Here's what I learned: 1. One memory layer for 20+ coding agents. Beacon captures activity across Claude Code, Cursor, Codex, and 20+ harnesses using OpenTelemetry, hooks, and local session files. Everything gets normalized into a single format, regardless of which agent you're using. 2. Your entire coding history becomes searchable. Every prompt, tool call, command, file change, and response is captured in a structured trace. Instead of losing valuable context when a session ends, you build a searchable history of everything your agents have done. 3. Switch agents without starting over. Hit your usage limit in Cursor? Open Claude Code and ask it to continue your latest Cursor session. Beacon retrieves the relevant context in milliseconds so your next agent can pick up where the last one left off. 4. Your agents learn from your past work. This is where things get interesting. Beacon identifies repeated workflows and turns them into reusable skills. In our demo, it discovered a recurring UI development workflow and generated a skill containing the exact dev server commands, screenshot steps, and deployment instructions. You teach one agent something once. Every other agent can benefit. 5. Stop accumulating skills nobody uses. Have 100 skills but only use five? Beacon analyzes actual usage across thousands of sessions and identifies skills worth keeping, combining, or removing. Your agent's memory gets more useful, not just bigger. 6. Security rules that follow you across every harness. Beacon includes hundreds of detection rules that work across agents. It can identify risky behavior, including sequences where an agent reads sensitive credentials and then makes an outbound network request. 7. It even caught a real credential leak. While reviewing Justin's actual Cursor history, Beacon surfaced an incident where part of a production database password had been sent to a model provider. That's the power of having visibility into what your agents are actually doing. 8. One prompt to get started. Completely open source. Paste a setup prompt into your coding agent and you're off. Keep everything local on your machine, or use Beacon Cloud for free. If you're juggling multiple coding agents, you need to check this out. Drop a like and share it with someone facing the same issue. Beacon on GitHub: (don't forget to star 🌟) Enjoy the episode. Cheers!

I gave Claude Code, Codex, and Cursor a self-improving, shared MEMORY. Now my coding agents learn from each other, and their knowledge follows me wherever I work. Coding agents work in silos. Your corrections in Cursor don't carry over to Claude Code, and skills built in Codex don't automatically transfer to other harnesses. So switching tools often means starting from scratch. What if every coding agent could learn from everything you've already done? I invited Justin D'Souza, co-founder of Asymptote Labs, to show me how to make this possible with Beacon, a 100% open-source memory layer for coding agents. We set it up live, explored real coding sessions, and watched Beacon turn past work into reusable knowledge. Here's what I learned: 1. One memory layer for 20+ coding agents. Beacon captures activity across Claude Code, Cursor, Codex, and 20+ harnesses using OpenTelemetry, hooks, and local session files. Everything gets normalized into a single format, regardless of which agent you're using. 2. Your entire coding history becomes searchable. Every prompt, tool call, command, file change, and response is captured in a structured trace. Instead of losing valuable context when a session ends, you build a searchable history of everything your agents have done. 3. Switch agents without starting over. Hit your usage limit in Cursor? Open Claude Code and ask it to continue your latest Cursor session. Beacon retrieves the relevant context in milliseconds so your next agent can pick up where the last one left off. 4. Your agents learn from your past work. This is where things get interesting. Beacon identifies repeated workflows and turns them into reusable skills. In our demo, it discovered a recurring UI development workflow and generated a skill containing the exact dev server commands, screenshot steps, and deployment instructions. You teach one agent something once. Every other agent can benefit. 5. Stop accumulating skills nobody uses. Have 100 skills but only use five? Beacon analyzes actual usage across thousands of sessions and identifies skills worth keeping, combining, or removing. Your agent's memory gets more useful, not just bigger. 6. Security rules that follow you across every harness. Beacon includes hundreds of detection rules that work across agents. It can identify risky behavior, including sequences where an agent reads sensitive credentials and then makes an outbound network request. 7. It even caught a real credential leak. While reviewing Justin's actual Cursor history, Beacon surfaced an incident where part of a production database password had been sent to a model provider. That's the power of having visibility into what your agents are actually doing. 8. One prompt to get started. Completely open source. Paste a setup prompt into your coding agent and you're off. Keep everything local on your machine, or use Beacon Cloud for free. If you're juggling multiple coding agents, you need to check this out. Drop a like and share it with someone facing the same issue. Beacon on GitHub: (don't forget to star 🌟) Enjoy the episode. Cheers!

Akshay 🚀

54,446 просмотров • 25 дней назад

Anthropic's in trouble, again! They spent years building what's now fully open-source. What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box. For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response. Every major AI product tried to replicate it. But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shipped natively with LangGraph, CrewAI, or Google ADK. So teams started building an owned version that required engineering the entire interface layer from scratch. Most teams, however, just settled for shipping the agent as a backend API in a chat box since rendering the UI is only one piece of it. To actually make it work, the interface layer also needed real-time streaming, state kept in sync between agent and UI, conversations that persist across sessions, and reconnection when a user refreshes mid-run. CopilotKit🪁 is now the only open-source framework that actually lets you build your own full-stack Claude-like apps. It decouples the agent from the interface, talking over AG-UI (an open protocol for agent-to-user communication). Being a standard protocol, the frontend never needs to know whether it is talking to a LangGraph or a CrewAI agent. You can change the backend anytime and the UI will never notice. In practice, CopilotKit's interface layer gives several pre-implemented React building blocks that wire the agent directly into the app, like: - generative UI, so the agent renders real components instead of text - chat windows, sidebars, and popups, or a fully headless setup - shared state, so the agent and app stay in sync - human-in-the-loop approvals, where the agent waits before acting - persistent threads that store the whole session, including the agent-user interactions and generated UI, not just text And because that full history is captured, those interactions can feed a self-learning layer that also improves the agent from real usage over time. The interface layer that Anthropic spent years engineering in-house is now literally available to any developer/team. CopilotKit is open-source with 30k+ GitHub stars, and AG-UI, the protocol underneath, is already supported across every major agent framework: LangGraph, CrewAI, Mastra, Google ADK, and more. CopilotKit GitHub repo → (don't forget to star it ⭐ ) If you want to go deeper, I found a detailed breakdown by Shubham Saboo recently on the three Generative UI patterns, with implementation. Read it below.

Anthropic's in trouble, again! They spent years building what's now fully open-source. What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box. For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response. Every major AI product tried to replicate it. But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shipped natively with LangGraph, CrewAI, or Google ADK. So teams started building an owned version that required engineering the entire interface layer from scratch. Most teams, however, just settled for shipping the agent as a backend API in a chat box since rendering the UI is only one piece of it. To actually make it work, the interface layer also needed real-time streaming, state kept in sync between agent and UI, conversations that persist across sessions, and reconnection when a user refreshes mid-run. CopilotKit🪁 is now the only open-source framework that actually lets you build your own full-stack Claude-like apps. It decouples the agent from the interface, talking over AG-UI (an open protocol for agent-to-user communication). Being a standard protocol, the frontend never needs to know whether it is talking to a LangGraph or a CrewAI agent. You can change the backend anytime and the UI will never notice. In practice, CopilotKit's interface layer gives several pre-implemented React building blocks that wire the agent directly into the app, like: - generative UI, so the agent renders real components instead of text - chat windows, sidebars, and popups, or a fully headless setup - shared state, so the agent and app stay in sync - human-in-the-loop approvals, where the agent waits before acting - persistent threads that store the whole session, including the agent-user interactions and generated UI, not just text And because that full history is captured, those interactions can feed a self-learning layer that also improves the agent from real usage over time. The interface layer that Anthropic spent years engineering in-house is now literally available to any developer/team. CopilotKit is open-source with 30k+ GitHub stars, and AG-UI, the protocol underneath, is already supported across every major agent framework: LangGraph, CrewAI, Mastra, Google ADK, and more. CopilotKit GitHub repo → (don't forget to star it ⭐ ) If you want to go deeper, I found a detailed breakdown by Shubham Saboo recently on the three Generative UI patterns, with implementation. Read it below.

Avi Chawla

462,344 просмотров • 5 месяцев назад

Whether you use Codex, Claude Code, OpenClaw, or any other AI agent—trader, coder, UI designer, data analyst, or health expert—if it can provide a service, it can earn. Give your agent one command: help me install ( Let it start taking paid jobs onchain.

Whether you use Codex, Claude Code, OpenClaw, or any other AI agent—trader, coder, UI designer, data analyst, or health expert—if it can provide a service, it can earn. Give your agent one command: help me install ( Let it start taking paid jobs onchain.

TermiX

45,587 просмотров • 2 месяцев назад

I created a free Markdown file that launches a 5-agent swarm team directly in Slack. I love Claude Code, but it's not the easiest place to manage your agents. Slack is where teams already work. So I put my agents there too. Drop the file in, and you get 5 agents, each with its own channel and job: • [Agent 1]: [what it does] • [Agent 2]: [what it does] • [Agent 3]: [what it does] • [Agent 4]: [what it does] • [Agent 5]: [what it does] You can assign work by messaging them like real employees, and they report back in the same threads. It's the closest I've found to running a real company with AI employees.

I created a free Markdown file that launches a 5-agent swarm team directly in Slack. I love Claude Code, but it's not the easiest place to manage your agents. Slack is where teams already work. So I put my agents there too. Drop the file in, and you get 5 agents, each with its own channel and job: • [Agent 1]: [what it does] • [Agent 2]: [what it does] • [Agent 3]: [what it does] • [Agent 4]: [what it does] • [Agent 5]: [what it does] You can assign work by messaging them like real employees, and they report back in the same threads. It's the closest I've found to running a real company with AI employees.

Miles Deutscher

25,762 просмотров • 24 дней назад

This is f*cking insane. Boris Cherny, the man who built Claude Code, was asked if people should still learn to code. His answer: "In a year or two, it's not going to matter" In 73 seconds, he explains what to do instead: play with the AI tools, learn them, don't be scared of them, stay on the frontier On his team, everyone codes now. The PM, the designer, even the finance guy He hasn't edited a single line of code by hand since last November. He ships 10 to 30 pull requests a day Writing Code → Prompting → Agents → Harness → Loops → Everyone on the Team Ships Claude Code is a harness: the tools, memory, rules and loops around the model. His team changes it with every new model and cut 80% of its system prompt Save this before it disappears from your feed Every doc, guide and repo below is free: Claude Code best practices Effective harnesses for long-running agents Building effective agents Claude Code docs Memory: how Claude remembers your project Custom subagents Hooks: rules the agent can't skip Skills Run Claude Code on a schedule Free course: Claude Code in Action Claude Code on GitHub Claude Code inside your PRs and issues Build your own agent on the same harness The best Claude Code resources in one list Plugins, agents and skills for Claude Code He compares it to the printing press. Writing went from a few scribes to everyone. Building software is next 95% will keep asking whether to learn to code, the 5% who build a harness will ship 30 pull requests a day Bookmark it and read the first link tonight Then use the guide below to build your harness before everyone else does ↓

This is f*cking insane. Boris Cherny, the man who built Claude Code, was asked if people should still learn to code. His answer: "In a year or two, it's not going to matter" In 73 seconds, he explains what to do instead: play with the AI tools, learn them, don't be scared of them, stay on the frontier On his team, everyone codes now. The PM, the designer, even the finance guy He hasn't edited a single line of code by hand since last November. He ships 10 to 30 pull requests a day Writing Code → Prompting → Agents → Harness → Loops → Everyone on the Team Ships Claude Code is a harness: the tools, memory, rules and loops around the model. His team changes it with every new model and cut 80% of its system prompt Save this before it disappears from your feed Every doc, guide and repo below is free: Claude Code best practices Effective harnesses for long-running agents Building effective agents Claude Code docs Memory: how Claude remembers your project Custom subagents Hooks: rules the agent can't skip Skills Run Claude Code on a schedule Free course: Claude Code in Action Claude Code on GitHub Claude Code inside your PRs and issues Build your own agent on the same harness The best Claude Code resources in one list Plugins, agents and skills for Claude Code He compares it to the printing press. Writing went from a few scribes to everyone. Building software is next 95% will keep asking whether to learn to code, the 5% who build a harness will ship 30 pull requests a day Bookmark it and read the first link tonight Then use the guide below to build your harness before everyone else does ↓

Sanabi

214,091 просмотров • 5 дней назад

Tune your UI transitions directly in Cursor CLI, Codex or Claude Code with the Transitions-dev skill built in It scans your project with your agent, suggests transitions improvements, and applies changes directly to source code

Tune your UI transitions directly in Cursor CLI, Codex or Claude Code with the Transitions-dev skill built in It scans your project with your agent, suggests transitions improvements, and applies changes directly to source code

Jakub Antalik

72,951 просмотров • 4 месяцев назад