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Claude Code Templates is now part of the Neon Postgres Open Source Program. One command to get a full Postgres setup for Claude Code. What you get: - 2 Skills (instant Postgres provisioning + best practices) - 5 Agents (schema design, auth, migrations, optimization, general) - 1 MCP (Neon... show more

Daniel San

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12,443 次观看 • 8 个月前 •via X (Twitter)

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The Neon backend is GA. A complete set of primitives for apps and agents built around the database, with open standards, no lock-in, and branching-first by design. Starting with: Lakebase Postgres, Object Storage, Functions, Managed Better Auth, and AI Gateway. More to come.

The Neon backend is GA. A complete set of primitives for apps and agents built around the database, with open standards, no lock-in, and branching-first by design. Starting with: Lakebase Postgres, Object Storage, Functions, Managed Better Auth, and AI Gateway. More to come.

Neon

28,188 次观看 • 1 个月前

Big moment for Postgres! AI agents broke the idea of what a database is supposed to do. Traditional databases were built for humans, and Agents broke that model. - They branch endlessly. - They run ten experiments at once. - They need isolation, context, memory, structured reasoning, and safe sandboxes. Letting agents touch production systems is terrifying because the old model of Postgres was never built for this kind of behavior. Agentic Postgres is an agent-ready version of Postgres by TimescaleDB (by Tiger Data) that solves this. I think it is one of the biggest upgrades to the Agent stack this year and Tiger Data is working with me on this post to share what they did. Some key features: > It instantly creates branches of an entire database, which is perfect for parallel agent evals, safe experiments, migrations, or isolated testing. Forks take seconds and cost almost nothing. > It comes with a built-in MCP server, which agents can use to get schema guidance, best practices, and safe, structured access to Postgres. This is also helpful to run migrations with a real understanding. > It comes with actual hybrid search (vector search and BM25), so Agents can retrieve data directly inside the database. > The database is Memory native. This gives a persistent context for Agents to evolve. This is one of the first times I have seen Postgres feel ready for the AI native era.

Big moment for Postgres! AI agents broke the idea of what a database is supposed to do. Traditional databases were built for humans, and Agents broke that model. - They branch endlessly. - They run ten experiments at once. - They need isolation, context, memory, structured reasoning, and safe sandboxes. Letting agents touch production systems is terrifying because the old model of Postgres was never built for this kind of behavior. Agentic Postgres is an agent-ready version of Postgres by TimescaleDB (by Tiger Data) that solves this. I think it is one of the biggest upgrades to the Agent stack this year and Tiger Data is working with me on this post to share what they did. Some key features: > It instantly creates branches of an entire database, which is perfect for parallel agent evals, safe experiments, migrations, or isolated testing. Forks take seconds and cost almost nothing. > It comes with a built-in MCP server, which agents can use to get schema guidance, best practices, and safe, structured access to Postgres. This is also helpful to run migrations with a real understanding. > It comes with actual hybrid search (vector search and BM25), so Agents can retrieve data directly inside the database. > The database is Memory native. This gives a persistent context for Agents to evolve. This is one of the first times I have seen Postgres feel ready for the AI native era.

Avi Chawla

94,406 次观看 • 11 个月前

5 GitHub repos with ⭐50K+ combined stars that show how far people are pushing Claude Code beyond a single coding agent 1) instructkr/claude-code 2.3K⭐ -> a research snapshot of Claude Code’s source with the internals exposed for inspection. [ ] 2) codeaashu/claude-code 3.2K⭐ -> another reconstructed Claude Code codebase built for studying how the agent works under the hood, including tools, prompts, MCP. [ ] 3) Donchitos/Claude-Code-Game-Studios 20K+⭐ -> turns one Claude Code session into a game development studio with 49 specialized agents, 73 skills, 12 hooks, 11 rules and 41 templates. [ ] 4) VoltAgent/awesome-claude-code-subagents 24K+⭐ -> 154 specialized Claude Code subagents split across 10 categories. [ ] 5) tanbiralam/claude-code 2.2K⭐ -> a research-oriented Claude Code source reconstruction for inspecting the terminal agent architecture, plugins, tools and internal implementation. [ ] Save these if you want to understand what people are actually building around Claude Code instead of just using the default CLI.

5 GitHub repos with ⭐50K+ combined stars that show how far people are pushing Claude Code beyond a single coding agent 1) instructkr/claude-code 2.3K⭐ -> a research snapshot of Claude Code’s source with the internals exposed for inspection. [ ] 2) codeaashu/claude-code 3.2K⭐ -> another reconstructed Claude Code codebase built for studying how the agent works under the hood, including tools, prompts, MCP. [ ] 3) Donchitos/Claude-Code-Game-Studios 20K+⭐ -> turns one Claude Code session into a game development studio with 49 specialized agents, 73 skills, 12 hooks, 11 rules and 41 templates. [ ] 4) VoltAgent/awesome-claude-code-subagents 24K+⭐ -> 154 specialized Claude Code subagents split across 10 categories. [ ] 5) tanbiralam/claude-code 2.2K⭐ -> a research-oriented Claude Code source reconstruction for inspecting the terminal agent architecture, plugins, tools and internal implementation. [ ] Save these if you want to understand what people are actually building around Claude Code instead of just using the default CLI.

Lummox

12,775 次观看 • 2 个月前

Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!

Big moment for Postgres! AI coding tools have been surprisingly bad at writing Postgres code. Not because the models are dumb, but because of how they learned SQL in the first place. LLMs are trained on the internet, which is full of outdated Stack Overflow answers and quick-fix tutorials. So when you ask an AI to generate a schema, it gives you something that technically runs but misses decades of Postgres evolution, like: - No GENERATED ALWAYS AS IDENTITY (added in PG10) - No expression or partial indexes - No NULLS NOT DISTINCT (PG15) - Missing CHECK constraints and proper foreign keys - Generic naming that tells you nothing But this is actually a solvable problem. You can teach AI tools to write better Postgres by giving them access to the right documentation at inference time. This exact solution is actually implemented in the newly released pg-aiguide by Tiger Data - Creators of TimescaleDB, which is an open-source MCP server that provides coding tools access to 35 years of Postgres expertise. In a gist, the MCP server enables: - Semantic search over the official PostgreSQL manual (version-aware, so it knows PG14 vs PG17 differences) - Curated skills with opinionated best practices for schema design, indexing, and constraints. I ran an experiment with Claude Code to see how well this works, and worked with the team to put this together. Prompt: "Generate a schema for an e-commerce site twice, one with the MCP server disabled, one with it enabled. Finally, run an assessment to compare the generated schemas." The run with the MCP server led to: - 420% more indexes (including partial and expression indexes) - 235% more constraints - 60% more tables (proper normalization) - 11 automation functions and triggers - Modern PG17 patterns throughout The MCP-assisted schema had proper data integrity, performance optimizations baked in, and followed naming conventions that actually make sense in production. pg-aiguide works with Claude Code, Cursor, VS Code, and any MCP-compatible tool. It's free and fully open source. I have shared the repo in the replies!

Avi Chawla

187,280 次观看 • 9 个月前

Claude Code Templates just hit 100+ Skills on Installing is easy - one click to copy the install command, paste it in your project's .claude folder, done. - 67K npm installs - 13K+ GitHub stars - fully open source Thanks to the community for contributing Skills and components. In the video I show how to add a Data Privacy Compliance Skill to your project.

Claude Code Templates just hit 100+ Skills on Installing is easy - one click to copy the install command, paste it in your project's .claude folder, done. - 67K npm installs - 13K+ GitHub stars - fully open source Thanks to the community for contributing Skills and components. In the video I show how to add a Data Privacy Compliance Skill to your project.

Daniel San

164,913 次观看 • 10 个月前

this is pure f*cking treasure Anthropic devs just posted 20 GitHub repos that turn your Claude Code into a f*cking engineering team: Exposed for Opus 5.5 1. rtk: squeezes command output before it hits your context. the authors claim 60-90% fewer tokens 2. claude-mem: memory across sessions. records what the agent did and brings back what matters 3. ccusage: shows where your tokens and money went. one command, npx ccusage 4. Serena: search and edit code by meaning, not by text 5. Context7: up-to-date library docs, so Claude stops writing for last year's API 6. claude-context: your whole codebase searchable through MCP 7. Repomix: packs an entire repo into one AI-friendly file skills and method 8. superpowers: a skills framework and a full development methodology. the one almost everyone installs 9. skills: the official Agent Skills repo from Anthropic 10. spec-kit: spec-driven development, from GitHub itself 11. agents: a plugin marketplace for Claude Code and six other harnesses 12. claude-code-templates: ready configs and monitoring from one CLI 13. claude-code-hooks-mastery: hooks explained with working examples 14. awesome-claude-code: the hand-picked map of everything else running more than one agent 15. container-use: a separate container for every agent, so they stop breaking each other 16. claude-squad: several terminal agents in one window 17. Happy: control your agents from your phone, iOS and Android 18. claude-code-router: route requests across different models 19. ccstatusline: a status line that shows what your session is doing 20. tweakcc: edit Claude Code's own system prompts, toolsets and themes the stack in one line: memory keeps the context, skills set the method, containers let you run five agents instead of one. check each repo before you install. save this.

this is pure fcking treasure Anthropic devs just posted 20 GitHub repos that turn your Claude Code into a fcking engineering team: Exposed for Opus 5.5 1. rtk: squeezes command output before it hits your context. the authors claim 60-90% fewer tokens 2. claude-mem: memory across sessions. records what the agent did and brings back what matters 3. ccusage: shows where your tokens and money went. one command, npx ccusage 4. Serena: search and edit code by meaning, not by text 5. Context7: up-to-date library docs, so Claude stops writing for last year's API 6. claude-context: your whole codebase searchable through MCP 7. Repomix: packs an entire repo into one AI-friendly file skills and method 8. superpowers: a skills framework and a full development methodology. the one almost everyone installs 9. skills: the official Agent Skills repo from Anthropic 10. spec-kit: spec-driven development, from GitHub itself 11. agents: a plugin marketplace for Claude Code and six other harnesses 12. claude-code-templates: ready configs and monitoring from one CLI 13. claude-code-hooks-mastery: hooks explained with working examples 14. awesome-claude-code: the hand-picked map of everything else running more than one agent 15. container-use: a separate container for every agent, so they stop breaking each other 16. claude-squad: several terminal agents in one window 17. Happy: control your agents from your phone, iOS and Android 18. claude-code-router: route requests across different models 19. ccstatusline: a status line that shows what your session is doing 20. tweakcc: edit Claude Code's own system prompts, toolsets and themes the stack in one line: memory keeps the context, skills set the method, containers let you run five agents instead of one. check each repo before you install. save this.

kiosa

55,680 次观看 • 10 天前

If you use Claude Code, install this immediately. It's called Claude Code Templates. It adds an entire ecosystem of AI tools to Claude. Here's what you get: 1. Agent Teams Visual dashboards showing how multiple AI agents collaborate on code. 2. Specialized Agents Front-end developers, backend engineers, QA testers, marketers. 3. MCP Integrations Connect Claude to external tools and workflows. 4. Real-Time Monitoring Track AI development sessions and performance analytics. 5. Automation Scheduling Run tasks automatically every day. Example: You can schedule an agent team to run daily at 5AM. It researches trends, generates content, and builds workflows. All automatically. The best part? Everything is free and open source.

If you use Claude Code, install this immediately. It's called Claude Code Templates. It adds an entire ecosystem of AI tools to Claude. Here's what you get: 1. Agent Teams Visual dashboards showing how multiple AI agents collaborate on code. 2. Specialized Agents Front-end developers, backend engineers, QA testers, marketers. 3. MCP Integrations Connect Claude to external tools and workflows. 4. Real-Time Monitoring Track AI development sessions and performance analytics. 5. Automation Scheduling Run tasks automatically every day. Example: You can schedule an agent team to run daily at 5AM. It researches trends, generates content, and builds workflows. All automatically. The best part? Everything is free and open source.

Julian Goldie SEO

107,454 次观看 • 7 个月前

Introducing Claude Code Analytics Dashboard 🙌 Open source project to monitor your Claude Code agents in real-time as they work on your projects. Just run: npx claude-code-templates@latest --analytics Dashboard opens at localhost:3333 showing: - All active Claude Code sessions - Token usage & conversation stats - Real-time activity monitoring - Message history with export (CSV/JSON) Perfect for devs running multiple Claude Code agents - finally see what they're actually doing! The conversation view shows full chat history, token breakdowns, and current status. Finally understand your AI workflow patterns. Best part... Everything runs locally with total privacy! Sharing repo in first comment if you want to star or contribute 👇

Introducing Claude Code Analytics Dashboard 🙌 Open source project to monitor your Claude Code agents in real-time as they work on your projects. Just run: npx claude-code-templates@latest --analytics Dashboard opens at localhost:3333 showing: - All active Claude Code sessions - Token usage & conversation stats - Real-time activity monitoring - Message history with export (CSV/JSON) Perfect for devs running multiple Claude Code agents - finally see what they're actually doing! The conversation view shows full chat history, token breakdowns, and current status. Finally understand your AI workflow patterns. Best part... Everything runs locally with total privacy! Sharing repo in first comment if you want to star or contribute 👇

Daniel San

62,057 次观看 • 1 年前

Cursor for Design? This Claude Code UI workflow is insane And many vibe coders not aware of it: 1. Claude Code can assign parallel tasks to sub agents 2. Integrate with git worktree to create sandbox env This means you can get Claude Code generate 10 design at the same time, fork & iterate 🔁 Design is an explorative process, by leveraging sub agent + parallel task capabilities, many interesting product UX can be built; Also turned this workflow into an open-source IDE extension here:

Cursor for Design? This Claude Code UI workflow is insane And many vibe coders not aware of it: 1. Claude Code can assign parallel tasks to sub agents 2. Integrate with git worktree to create sandbox env This means you can get Claude Code generate 10 design at the same time, fork & iterate 🔁 Design is an explorative process, by leveraging sub agent + parallel task capabilities, many interesting product UX can be built; Also turned this workflow into an open-source IDE extension here:

Jason Zhou

40,635 次观看 • 1 年前

Let Postgres own the Iceberg catalog and delegate analytics to DuckDB. The result => transactional lakehouse updates with fast analytical queries. This isn’t a concept. It’s exactly what pg_lake delivers today. pg_lake combines a set of extensions and components that let you query and modify Iceberg tables (and other lakehouse formats) directly from Postgres. DuckDB is used to accelerate analytical queries and runs in a sidecar process called pgduck_server, which communicates with Postgres during query execution. How it works (diagram below): 1. An application sends a query to Postgres to calculate unrealized PnL (Profit and Loss) for the Disney ticker. 2. Postgres parses the query and identifies the part that computes the average price from historical lakehouse data. 3. That part is forwarded to pgduck_server for accelerated execution. 4. pgduck_server delegates execution to DuckDB, which queries the lakehouse (reusing cached data if available). 5. DuckDB computes the average price and returns it to Postgres. 6. Postgres joins the result with local portfolio data and computes the unrealized PnL. 7. The final result is returned to the application.

Let Postgres own the Iceberg catalog and delegate analytics to DuckDB. The result => transactional lakehouse updates with fast analytical queries. This isn’t a concept. It’s exactly what pg_lake delivers today. pg_lake combines a set of extensions and components that let you query and modify Iceberg tables (and other lakehouse formats) directly from Postgres. DuckDB is used to accelerate analytical queries and runs in a sidecar process called pgduck_server, which communicates with Postgres during query execution. How it works (diagram below): 1. An application sends a query to Postgres to calculate unrealized PnL (Profit and Loss) for the Disney ticker. 2. Postgres parses the query and identifies the part that computes the average price from historical lakehouse data. 3. That part is forwarded to pgduck_server for accelerated execution. 4. pgduck_server delegates execution to DuckDB, which queries the lakehouse (reusing cached data if available). 5. DuckDB computes the average price and returns it to Postgres. 6. Postgres joins the result with local portfolio data and computes the unrealized PnL. 7. The final result is returned to the application.

Denis Magda

28,597 次观看 • 8 个月前

Claude Code Templates now has a web interface for browsing and contributing templates 🙌 What it does: Install templates for different languages/frameworks to get started with Claude Code faster. How to use: - Go to - Run: npm install -g claude-code-templates - Pick a template from the site - Copy and run the template command - Start coding with Claude Code The whole thing runs on GitHub - no fancy backend, no hidden stuff. Everything you're installing is right there in the repo for you to inspect. Contributing: Want to add your own template? Just follow the contribution guide and send a PR. Once merged, it automatically shows up on the site. That's it... nothing fancy, just something to save a few minutes when starting new projects with Claude Code Repo:

Claude Code Templates now has a web interface for browsing and contributing templates 🙌 What it does: Install templates for different languages/frameworks to get started with Claude Code faster. How to use: - Go to - Run: npm install -g claude-code-templates - Pick a template from the site - Copy and run the template command - Start coding with Claude Code The whole thing runs on GitHub - no fancy backend, no hidden stuff. Everything you're installing is right there in the repo for you to inspect. Contributing: Want to add your own template? Just follow the contribution guide and send a PR. Once merged, it automatically shows up on the site. That's it... nothing fancy, just something to save a few minutes when starting new projects with Claude Code Repo:

Daniel San

60,766 次观看 • 1 年前

Our beloved solana-claude is now Solana AI Kit ⚡ The best Solana AI skills, one command away. Check out our curated aggregator of agents, commands, skills, MCPs & config for Claude Code, Codex & any agentic setup. What's new: 🧠 15 agents + 29 commands: incl. new /doctor (env health-check), /audit-infra (secrets, supply-chain, CI/CD + OWASP/STRIDE), /product-review --harsh, /dream (memory consolidation) 🧩 18 expert skill submodules: now with Quicknode, eth→Solana migration, Ghost Security & Anthropic's defending-code ⚙️ Stack refresh: OtterSec's Anchor 1.0, blueshift's Quasar, Surfpool MCP, SendAI's & more 📚 Extended skill registry: 39 install-on-demand tools covering design, forensics, animation, UX, testing & data, curated from the best of the ecosystem 💚Install: curl -fsSL | bash 🔌 Now on the Claude Code plugin marketplace /plugin install solana-ai-kit@stbr

Our beloved solana-claude is now Solana AI Kit ⚡ The best Solana AI skills, one command away. Check out our curated aggregator of agents, commands, skills, MCPs & config for Claude Code, Codex & any agentic setup. What's new: 🧠 15 agents + 29 commands: incl. new /doctor (env health-check), /audit-infra (secrets, supply-chain, CI/CD + OWASP/STRIDE), /product-review --harsh, /dream (memory consolidation) 🧩 18 expert skill submodules: now with Quicknode, eth→Solana migration, Ghost Security & Anthropic's defending-code ⚙️ Stack refresh: OtterSec's Anchor 1.0, blueshift's Quasar, Surfpool MCP, SendAI's & more 📚 Extended skill registry: 39 install-on-demand tools covering design, forensics, animation, UX, testing & data, curated from the best of the ecosystem 💚Install: curl -fsSL | bash 🔌 Now on the Claude Code plugin marketplace /plugin install solana-ai-kit@stbr

Superteam Brasil

20,596 次观看 • 4 个月前

Coding agents that actually get better the more your team uses them. Introducing Hivemind: continual learning for AI coding agents. Hivemind turns the traces from every agent your team runs (Claude Code, Codex, Cursor, Hermes, OpenClaw, Pi) into reusable skills, then pushes those skills across all of them. All on your cloud storage. Now with SkillOpt built in, your skills get trained: +19.1 points of accuracy in Claude Code, +24.8 in Codex, best or tied on all 52 setups tested. Open source, one line install.

Coding agents that actually get better the more your team uses them. Introducing Hivemind: continual learning for AI coding agents. Hivemind turns the traces from every agent your team runs (Claude Code, Codex, Cursor, Hermes, OpenClaw, Pi) into reusable skills, then pushes those skills across all of them. All on your cloud storage. Now with SkillOpt built in, your skills get trained: +19.1 points of accuracy in Claude Code, +24.8 in Codex, best or tied on all 52 setups tested. Open source, one line install.

Davit

423,450 次观看 • 4 个月前

Introducing Jev Skill Suggestion for Claude Code Now you can keep your skills completely out of the context window until they’re actually needed Set your skills as user invocable only, and the Mod sends the available skill list to Jev For every request, Jev classifies which skill best matches the task, then injects only that skill into Claude’s context Works with both the TypeSafe AI API and Vercel AI Gateway Install it with one command: npx claude-code-templates@latest --mod productivity/jev-skill-suggestion Full implementation details on the Mod page at

Introducing Jev Skill Suggestion for Claude Code Now you can keep your skills completely out of the context window until they’re actually needed Set your skills as user invocable only, and the Mod sends the available skill list to Jev For every request, Jev classifies which skill best matches the task, then injects only that skill into Claude’s context Works with both the TypeSafe AI API and Vercel AI Gateway Install it with one command: npx claude-code-templates@latest --mod productivity/jev-skill-suggestion Full implementation details on the Mod page at

Daniel San

81,168 次观看 • 28 天前

Here's how to do months of SEO work in one afternoon with Claude Code: Step 1: Feed AI your site, ask for 25-50 keywords Step 2: Filter for buying intent (who's ready to call NOW) Step 3: Build a landing page for each keyword + location Step 4: Run an SEO audit ("ultra think" goes deep) Step 5: Fix technical issues (sitemap, schema, speed) Step 6: Spin up sub-agents to research competitors while you work THE KEY: One afternoon of Claude Code > 6 months with an agency. Go vibe market something.

Here's how to do months of SEO work in one afternoon with Claude Code: Step 1: Feed AI your site, ask for 25-50 keywords Step 2: Filter for buying intent (who's ready to call NOW) Step 3: Build a landing page for each keyword + location Step 4: Run an SEO audit ("ultra think" goes deep) Step 5: Fix technical issues (sitemap, schema, speed) Step 6: Spin up sub-agents to research competitors while you work THE KEY: One afternoon of Claude Code > 6 months with an agency. Go vibe market something.

The Startup Ideas Podcast (SIP) 🧃

84,834 次观看 • 9 个月前

NVIDIA just dropped free API keys for every top AI model You don't need your own GPU and you don't pay per token. GLM-5.2, MiniMax, Kimi, DeepSeek, OpenAI, all running on NVIDIA's servers, called through a normal API. Link: How to use one: 1. Create a free NVIDIA account. 2. Pick a Free Endpoint model and open its Build tab. You'll see ready-to-copy code with the base URL 3. Hit Generate API Key, copy it and paste that base URL and key into Claude Code, Cursor, or Cline. Bonus: NVIDIA also dropped 237 official skills that install into Claude Code and Codex in one command. Bookmark this.

NVIDIA just dropped free API keys for every top AI model You don't need your own GPU and you don't pay per token. GLM-5.2, MiniMax, Kimi, DeepSeek, OpenAI, all running on NVIDIA's servers, called through a normal API. Link: How to use one: 1. Create a free NVIDIA account. 2. Pick a Free Endpoint model and open its Build tab. You'll see ready-to-copy code with the base URL 3. Hit Generate API Key, copy it and paste that base URL and key into Claude Code, Cursor, or Cline. Bonus: NVIDIA also dropped 237 official skills that install into Claude Code and Codex in one command. Bookmark this.

Yarchi

64,348 次观看 • 3 个月前

A designer who can ship code is one of the most valuable hires in tech today. Here's my new episode with Felix Lee (CEO of ADPList) where he showed me how to use Claude Code and Figma MCP to go from: ✅ Figma → Code: Design to website in 15 min ✅ Code → Figma: App back to editable design Felix also demoed a few apps he's designed and built in Claude Code, including a 3D globe website and a landing page analyzer. Some takeaways from Felix: 1. Stop pasting screenshots into Claude Code. Instead, use Figma MCP to pull in all your assets, icons, and images automatically. 2. You can use the same MCP to convert code back into editable Figma layers to explore more variations. 3. An underrated way to build: Use FigJam to plan a flowchart of your app first, then paste the link into Claude Code with the MCP. 📌 Watch now: Thanks to our sponsors: Replit ⠕: Plan, design, and build with AI agents Linear: The AI agent platform for modern teams

A designer who can ship code is one of the most valuable hires in tech today. Here's my new episode with Felix Lee (CEO of ADPList) where he showed me how to use Claude Code and Figma MCP to go from: ✅ Figma → Code: Design to website in 15 min ✅ Code → Figma: App back to editable design Felix also demoed a few apps he's designed and built in Claude Code, including a 3D globe website and a landing page analyzer. Some takeaways from Felix: 1. Stop pasting screenshots into Claude Code. Instead, use Figma MCP to pull in all your assets, icons, and images automatically. 2. You can use the same MCP to convert code back into editable Figma layers to explore more variations. 3. An underrated way to build: Use FigJam to plan a flowchart of your app first, then paste the link into Claude Code with the MCP. 📌 Watch now: Thanks to our sponsors: Replit ⠕: Plan, design, and build with AI agents Linear: The AI agent platform for modern teams

Peter Yang

77,115 次观看 • 7 个月前

ONE PROMPT AND ONE BUTTON NOW BUILDS A FULL SYSTEM, DATABASE, BACKEND, AND FRONTEND INCLUDED Most people still picture AI as something you ask questions to, then copy the answer into your own code by hand. A builder wired Claude into Obsidian through MCP instead, so a single written prompt becomes the actual spec for the system. Claude breaks that prompt into database schema, UI components, and API endpoints on its own, then writes, runs, and fixes the code until it actually works. MCP is what makes this possible, it lets the agent see the filesystem, installed packages, and running services before it starts building anything. The output isn't a code snippet sitting in a chat window, it's a live local app running on its own server, ready to open in a browser. What used to need a backend developer, a DevOps engineer, and two weeks now finishes in under fifteen minutes. See the full architecture and prompt structure below👇

ONE PROMPT AND ONE BUTTON NOW BUILDS A FULL SYSTEM, DATABASE, BACKEND, AND FRONTEND INCLUDED Most people still picture AI as something you ask questions to, then copy the answer into your own code by hand. A builder wired Claude into Obsidian through MCP instead, so a single written prompt becomes the actual spec for the system. Claude breaks that prompt into database schema, UI components, and API endpoints on its own, then writes, runs, and fixes the code until it actually works. MCP is what makes this possible, it lets the agent see the filesystem, installed packages, and running services before it starts building anything. The output isn't a code snippet sitting in a chat window, it's a live local app running on its own server, ready to open in a browser. What used to need a backend developer, a DevOps engineer, and two weeks now finishes in under fifteen minutes. See the full architecture and prompt structure below👇

wast3

20,348 次观看 • 3 个月前