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🚨 AI coding agents hallucinate because they can't actually read your codebase. This MCP server fixes that. It's called Context+ and it gives AI 99% accuracy on large-scale engineering projects by building a real semantic map of your code before touching a single line. Here's what makes it different...

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Ihtesham Ali

16,923 subscribers

29,781 次观看 • 2 个月前 •via X (Twitter)

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Make Claude Code 10x more powerful! Code Context is an MCP plugin that brings semantic code search to Claude Code, Gemini CLI, or any AI coding agent. Full codebase indexing means richer context and better code generation. 100% open-source.
1:33

Make Claude Code 10x more powerful! Code Context is an MCP plugin that brings semantic code search to Claude Code, Gemini CLI, or any AI coding agent. Full codebase indexing means richer context and better code generation. 100% open-source.

Akshay 🚀

136,939 次观看 • 10 个月前

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.
0:31

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.

Akshay 🚀

30,789 次观看 • 1 年前

Someone built a tool that converts your entire codebase into a graph database. Instead of dumping code into LLMs, AI can navigate functions, classes, and dependencies like a map. It's called CodeGraphContext.
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Someone built a tool that converts your entire codebase into a graph database. Instead of dumping code into LLMs, AI can navigate functions, classes, and dependencies like a map. It's called CodeGraphContext.

Aman

245,993 次观看 • 2 个月前

Stop...Your AI shouldn’t sit in a sidebar. It should actually work inside your notes. AnySlate just made that real. Your AI can: • read your markdown files • edit sections • create docs • search your workspace • organize everything No copy paste No switching tabs No proprietary lock-in Every file is a real .md file Your notes stay portable forever And the wild part — it supports MCP natively So Claude, Cursor, or Windsurf can directly work inside your workspace This is the shift from AI that helps you write to AI that manages your knowledge Real-time collaboration Built-in AI assistant PDF + web publishing Version history Works on Mac Windows Linux + browser This is what a modern markdown editor should look like
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Stop...Your AI shouldn’t sit in a sidebar. It should actually work inside your notes. AnySlate just made that real. Your AI can: • read your markdown files • edit sections • create docs • search your workspace • organize everything No copy paste No switching tabs No proprietary lock-in Every file is a real .md file Your notes stay portable forever And the wild part — it supports MCP natively So Claude, Cursor, or Windsurf can directly work inside your workspace This is the shift from AI that helps you write to AI that manages your knowledge Real-time collaboration Built-in AI assistant PDF + web publishing Version history Works on Mac Windows Linux + browser This is what a modern markdown editor should look like

Nainsi Dwivedi

13,617 次观看 • 2 个月前

AI Agents can now connect to 100,000+ APIs instantly. Postman's AI Agent builder can turn any API into an MCP server in seconds without writing a single line of Code. You can use it in Claude, Cursor, Windsurf and other AI tools.
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AI Agents can now connect to 100,000+ APIs instantly. Postman's AI Agent builder can turn any API into an MCP server in seconds without writing a single line of Code. You can use it in Claude, Cursor, Windsurf and other AI tools.

Shubham Saboo

79,628 次观看 • 1 年前

Claude Code is terrible at UI design and everyone knows it so this guy fixed it by building an MCP that gives Claude its own AI design tool instead of going back and forth between a design platform and your code editor, Claude now creates the designs itself and drops them straight into your codebase the MCP has full context of your existing design system and project so everything it generates actually matches what you already have. one command to set up and it installs the MCP and skill files so Claude instantly knows how to use it if you're tired of the same Inter font, purple gradient, card grid layout on every project, this is definitely worth trying
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Claude Code is terrible at UI design and everyone knows it so this guy fixed it by building an MCP that gives Claude its own AI design tool instead of going back and forth between a design platform and your code editor, Claude now creates the designs itself and drops them straight into your codebase the MCP has full context of your existing design system and project so everything it generates actually matches what you already have. one command to set up and it installs the MCP and skill files so Claude instantly knows how to use it if you're tired of the same Inter font, purple gradient, card grid layout on every project, this is definitely worth trying

Om Patel

396,051 次观看 • 2 个月前

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.
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Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Santiago

64,392 次观看 • 6 个月前

How to make Claude Code 10x better: Connect it with a tool that reviews your code and generates prompts for Claude to fix any issues with it automatically. Here is what this looks like:
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How to make Claude Code 10x better: Connect it with a tool that reviews your code and generates prompts for Claude to fix any issues with it automatically. Here is what this looks like:

Santiago

98,881 次观看 • 8 个月前

AI can write your code. But who’s making sure it’s actually good? CodeRabbit now gives you free, high-quality AI code reviews, right inside your IDE. Supports and integrates with top AI agents like GitHub Copilot, Claude, Codex, Cursor AI, and more. What makes it different: • No subscription needed • Context-aware reviews • “Fix with AI” feature sends feedback directly to your AI coding agent • One-click commit suggestions • 10M+ PRs reviewed, 50K+ installs on GitHub Marketplace CodeRabbit doesn’t just point out issues. It helps you fix them fast.
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AI can write your code. But who’s making sure it’s actually good? CodeRabbit now gives you free, high-quality AI code reviews, right inside your IDE. Supports and integrates with top AI agents like GitHub Copilot, Claude, Codex, Cursor AI, and more. What makes it different: • No subscription needed • Context-aware reviews • “Fix with AI” feature sends feedback directly to your AI coding agent • One-click commit suggestions • 10M+ PRs reviewed, 50K+ installs on GitHub Marketplace CodeRabbit doesn’t just point out issues. It helps you fix them fast.

Rohit Ghumare

30,686 次观看 • 1 年前

An MCP server that detects production-grade code quality issues in real-time! Even though AI is now generating code at light speed, the engineering bottleneck has just moved from writing to reviewing, and now devs spend 90% of their debugging time on AI-generated code. AI reviewers aren't that reliable either because they share the same fundamental blind spots as AI generators do: - They pattern match, not proof check. - They validate syntax, not system behavior. - They review code, not consequences. I have been using the SonarQube MCP Server (by Sonar) to solve this. It produces enterprise-grade code analysis and returns instant feedback on bugs, vulnerabilities, and code smells right where you're working (Claude Code, Cursor, etc.). Its capabilities have emerged from the 750B+ lines of code SonarQube processes daily, so it has seen every bug pattern that exists. This includes: - Security vulnerabilities (SQL injection, XSS, hardcoded secrets) - Code smells and technical debt - Test coverage gaps - Maintainability issues The setup is simple: - Install the SonarQube MCP server - Add it to your AI assistant's config Done! SonarQube is now part of your AI coding workflow. I have shared the GitHub repo in the replies! P.S. Thanks to Sonar for working with me today.
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An MCP server that detects production-grade code quality issues in real-time! Even though AI is now generating code at light speed, the engineering bottleneck has just moved from writing to reviewing, and now devs spend 90% of their debugging time on AI-generated code. AI reviewers aren't that reliable either because they share the same fundamental blind spots as AI generators do: - They pattern match, not proof check. - They validate syntax, not system behavior. - They review code, not consequences. I have been using the SonarQube MCP Server (by Sonar) to solve this. It produces enterprise-grade code analysis and returns instant feedback on bugs, vulnerabilities, and code smells right where you're working (Claude Code, Cursor, etc.). Its capabilities have emerged from the 750B+ lines of code SonarQube processes daily, so it has seen every bug pattern that exists. This includes: - Security vulnerabilities (SQL injection, XSS, hardcoded secrets) - Code smells and technical debt - Test coverage gaps - Maintainability issues The setup is simple: - Install the SonarQube MCP server - Add it to your AI assistant's config Done! SonarQube is now part of your AI coding workflow. I have shared the GitHub repo in the replies! P.S. Thanks to Sonar for working with me today.

Avi Chawla

28,027 次观看 • 6 个月前

Today, I'm excited to launch Entelligence AI DeepReviews, the next generation AI-powered code reviews. Vibe coded PRs are not production ready often creating more subtle bugs throughout the codebase than before. Entelligence fixes this by understanding the entire codebase and flags bugs, regressions, and breakages across files before you ship. But it goes beyond review comments: ✅ Auto-generated docs with architecture diagrams ✅ Team Insights to improve process, not just code ✅ Real time code reviews within your editor If you're building or leading a dev team, this is what smarter, context-aware reviews look like. Try it out in the link below 👇
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Today, I'm excited to launch Entelligence AI DeepReviews, the next generation AI-powered code reviews. Vibe coded PRs are not production ready often creating more subtle bugs throughout the codebase than before. Entelligence fixes this by understanding the entire codebase and flags bugs, regressions, and breakages across files before you ship. But it goes beyond review comments: ✅ Auto-generated docs with architecture diagrams ✅ Team Insights to improve process, not just code ✅ Real time code reviews within your editor If you're building or leading a dev team, this is what smarter, context-aware reviews look like. Try it out in the link below 👇

Aiswarya Sankar

95,962 次观看 • 1 年前

AI should 10× your shipping speed not 10× your prompt count. Meet Traycer: a planning layer that drafts a per-file blueprint, then hands exact tasks to Cursor, Windsurf, or Claude Code. Less noise, more code. Here’s how it works (with demos): 👇
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AI should 10× your shipping speed not 10× your prompt count. Meet Traycer: a planning layer that drafts a per-file blueprint, then hands exact tasks to Cursor, Windsurf, or Claude Code. Less noise, more code. Here’s how it works (with demos): 👇

Shruti

36,424 次观看 • 11 个月前

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base
1:47

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base

Malte Ubl

124,713 次观看 • 5 个月前

Introducing Deep Graph Codebase to MCP with One Click... Now Available for Gemini CLI too! 🤩 Transform any public GitHub repository into an AI-ready Code Graph by simply changing the URL from to This instantly prepares the repository for seamless integration with AI assistants. It's that easy! You can now use repositories like ollama as a code graph within any project using Gemini CLI... just add the MCP Server JSON configuration to your .gemini/settings.json file
1:01

Introducing Deep Graph Codebase to MCP with One Click... Now Available for Gemini CLI too! 🤩 Transform any public GitHub repository into an AI-ready Code Graph by simply changing the URL from to This instantly prepares the repository for seamless integration with AI assistants. It's that easy! You can now use repositories like ollama as a code graph within any project using Gemini CLI... just add the MCP Server JSON configuration to your .gemini/settings.json file

Daniel San

51,534 次观看 • 11 个月前

Marc Andreessen explains why AI coding won't replace programmers, but fundamentally change what they do. He argues that AI coding is just the latest abstraction layer, and the job of a programmer has always evolved with each one. Andreessen's key reframe of what's actually happening: "AI coding actually abstracts away the process of actually writing the scripting code... This is the next layer of the task redefinition under the job of programmer." He's clear that the best programmers aren't being replaced. They're already adapting, even if their day-to-day looks radically different now. Their job has shifted from writing code line by line to managing dozens of AI agents working in parallel. "The world's best programmers today will tell you, 'My job is I'm sitting there and I'm orchestrating 10 code bots running in parallel.' Their day job now is kind of arguing with the AI bots to try to get them to write the right code." But Marc Andreessen 🇺🇸 is adamant this doesn't make foundational knowledge obsolete — it makes it more important. "You need to still fully understand and learn how to write and understand code, because if it doesn't work or it's not doing what you expect, you need to be able to understand the results of what the AI is giving you." He draws a direct parallel: Just as someone writing scripting languages still needs to understand how a microprocessor works, someone orchestrating AI bots needs to understand the code those bots produce. "It's this upleveling of capability where you actually want the depth to go down and understand what the thing is actually doing, even if you're not spending your day doing that by hand." The result, in his view, is transformative: "Now programmers are going to be 10 times or 100 times or a thousand times more productive. And that is overwhelmingly a good thing." The pattern: New abstraction layer emerges → tasks change → the job gets redefined upward → productivity explodes It raises a question every programmer should be sitting with... Are you building the depth to evaluate what AI gives you, or just accepting the output?
1:50

Marc Andreessen explains why AI coding won't replace programmers, but fundamentally change what they do. He argues that AI coding is just the latest abstraction layer, and the job of a programmer has always evolved with each one. Andreessen's key reframe of what's actually happening: "AI coding actually abstracts away the process of actually writing the scripting code... This is the next layer of the task redefinition under the job of programmer." He's clear that the best programmers aren't being replaced. They're already adapting, even if their day-to-day looks radically different now. Their job has shifted from writing code line by line to managing dozens of AI agents working in parallel. "The world's best programmers today will tell you, 'My job is I'm sitting there and I'm orchestrating 10 code bots running in parallel.' Their day job now is kind of arguing with the AI bots to try to get them to write the right code." But Marc Andreessen 🇺🇸 is adamant this doesn't make foundational knowledge obsolete — it makes it more important. "You need to still fully understand and learn how to write and understand code, because if it doesn't work or it's not doing what you expect, you need to be able to understand the results of what the AI is giving you." He draws a direct parallel: Just as someone writing scripting languages still needs to understand how a microprocessor works, someone orchestrating AI bots needs to understand the code those bots produce. "It's this upleveling of capability where you actually want the depth to go down and understand what the thing is actually doing, even if you're not spending your day doing that by hand." The result, in his view, is transformative: "Now programmers are going to be 10 times or 100 times or a thousand times more productive. And that is overwhelmingly a good thing." The pattern: New abstraction layer emerges → tasks change → the job gets redefined upward → productivity explodes It raises a question every programmer should be sitting with... Are you building the depth to evaluate what AI gives you, or just accepting the output?

Big Brain AI

45,187 次观看 • 3 个月前

The most underrated feature in AI coding tools isn't what you think. One simple rules file - supported by Visual Studio Code, Cursor and @windsurf - can massively increase the quality and reliability of your AI assistant Here's the secret sauce...
13:52

The most underrated feature in AI coding tools isn't what you think. One simple rules file - supported by Visual Studio Code, Cursor and @windsurf - can massively increase the quality and reliability of your AI assistant Here's the secret sauce...

Yifan

69,498 次观看 • 1 年前

You sit down to code. You have your playlist on. Coffee’s still warm. You’re ready to build. Then it starts… You forget a syntax. You open a tab. You Google it. You end up on StackOverflow. You read three different answers. Now you’re in the docs. And suddenly, you’re 10 tabs deep and completely out of flow. Sound familiar? You didn’t stop because the problem was hard. → You stopped because your workflow broke. Too many tabs. Too many distractions. Too much time spent not coding. That’s why AugmentCode exists. It’s a smart AI tool that lives inside VS Code and helps you code faster, smoother, and with way less friction. Let me explain how it helps: 👇 1. AI THAT ACTUALLY UNDERSTANDS YOUR CODE ⚡ Most AI tools guess based on your prompt. AugmentCode reads your actual codebase and gives help that fits. It can: ✅ Explain functions ✅ Fix bugs ✅ Refactor messy logic ✅ Answer your coding questions—in real time All inside your editor. 2. INSTANT DOCUMENTATION, NO TAB-HOPPING⚡ You know when you highlight a function and have no idea what it does? Now you can just select it → press a shortcut → and boom. Documentation shows up right inside VS Code. No more Googling. No more context-switching. 3. ASK IT QUESTIONS—ABOUT YOUR OWN PROJECT ⚡ This part’s WILD. You can literally ask: → “What does this file do?” → “Where is this function used?” → “Can you simplify this logic?” And it answers based on YOUR code. No more copy-pasting into ChatGPT and explaining everything from scratch. 4. GENERATE TESTS WITHOUT THE HEADACHE ⚡ Testing is important but let’s be real, writing unit tests is no one’s favorite part. AugmentCode can generate tests for your actual functions based on their logic. Not generic boilerplate—real, usable tests. 5. YOU NEVER LEAVE VS CODE ⚡ Everything: debugging, docs, AI chat, test generation...happens inside your IDE. It’s just you, your code, and an assistant who actually helps. 6. BUILT FOR REAL DEVELOPERS ⚡ This isn’t a flashy AI toy. It’s a practical tool built for indie hackers, full-stack devs, and shipping teams. → The UX is clean. The output is useful. It just works. 🔥 AugmentCode runs 2 to 3 times faster than GitHub Copilot, making it a powerful choice for large-scale projects where speed matters. It also supports collaborative coding by offering shared context and built-in integrations with tools like Slack, helping teams communicate better. If you write code, you need this. Simple as that. 👉 Because the future of coding isn’t about replacing devs. It’s about AUGMENTING them.
0:25

You sit down to code. You have your playlist on. Coffee’s still warm. You’re ready to build. Then it starts… You forget a syntax. You open a tab. You Google it. You end up on StackOverflow. You read three different answers. Now you’re in the docs. And suddenly, you’re 10 tabs deep and completely out of flow. Sound familiar? You didn’t stop because the problem was hard. → You stopped because your workflow broke. Too many tabs. Too many distractions. Too much time spent not coding. That’s why AugmentCode exists. It’s a smart AI tool that lives inside VS Code and helps you code faster, smoother, and with way less friction. Let me explain how it helps: 👇 1. AI THAT ACTUALLY UNDERSTANDS YOUR CODE ⚡ Most AI tools guess based on your prompt. AugmentCode reads your actual codebase and gives help that fits. It can: ✅ Explain functions ✅ Fix bugs ✅ Refactor messy logic ✅ Answer your coding questions—in real time All inside your editor. 2. INSTANT DOCUMENTATION, NO TAB-HOPPING⚡ You know when you highlight a function and have no idea what it does? Now you can just select it → press a shortcut → and boom. Documentation shows up right inside VS Code. No more Googling. No more context-switching. 3. ASK IT QUESTIONS—ABOUT YOUR OWN PROJECT ⚡ This part’s WILD. You can literally ask: → “What does this file do?” → “Where is this function used?” → “Can you simplify this logic?” And it answers based on YOUR code. No more copy-pasting into ChatGPT and explaining everything from scratch. 4. GENERATE TESTS WITHOUT THE HEADACHE ⚡ Testing is important but let’s be real, writing unit tests is no one’s favorite part. AugmentCode can generate tests for your actual functions based on their logic. Not generic boilerplate—real, usable tests. 5. YOU NEVER LEAVE VS CODE ⚡ Everything: debugging, docs, AI chat, test generation...happens inside your IDE. It’s just you, your code, and an assistant who actually helps. 6. BUILT FOR REAL DEVELOPERS ⚡ This isn’t a flashy AI toy. It’s a practical tool built for indie hackers, full-stack devs, and shipping teams. → The UX is clean. The output is useful. It just works. 🔥 AugmentCode runs 2 to 3 times faster than GitHub Copilot, making it a powerful choice for large-scale projects where speed matters. It also supports collaborative coding by offering shared context and built-in integrations with tools like Slack, helping teams communicate better. If you write code, you need this. Simple as that. 👉 Because the future of coding isn’t about replacing devs. It’s about AUGMENTING them.

EyeingAI

26,587 次观看 • 1 年前

You can now clone any website just by writing a prompt. Simply add the Firecrawl MCP server to your favorite AI coding tool for improved web data extraction, and let Claude code it for you. Here’s how:
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You can now clone any website just by writing a prompt. Simply add the Firecrawl MCP server to your favorite AI coding tool for improved web data extraction, and let Claude code it for you. Here’s how:

Alvaro Cintas

83,022 次观看 • 10 个月前