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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.show more

Akshay 🚀

279,882 subscribers

30,806 görüntüleme • 1 yıl önce •via X (Twitter)

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Akshay 🚀 profil fotoğrafı

Akshay 🚀1 yıl önce

Try Augment Code now:

Coral AI News profil fotoğrafı

Coral AI News2 yıl önce

Coral AI is the most powerful AI for documents. See the difference yourself:

Avi Chawla profil fotoğrafı

Avi Chawla1 yıl önce

Augment Code is amazing!! Even I tested it recently and it worked flawlessly.

Inforida profil fotoğrafı

Inforida1 yıl önce

AI coding assistants are indeed evolving, but the challenge lies in their ability to truly grasp the nuances of human coding logic. As we push for more advanced AI, we must also ensure they can adapt contextually. It's a race, and the finish line keeps moving.

Sean Dorofeev profil fotoğrafı

Sean Dorofeev1 yıl önce

There are plenty of approaches to giving LLM context. 34k lines of code, that's very small and I'm surprised how you got that result. I have a little over 400k, no problems withcontext. documents, docstringz, cursor rules solve most problems.

Gabriel Rymberg profil fotoğrafı

Gabriel Rymberg1 yıl önce

@threadreaderapp unroll

Thread Reader App profil fotoğrafı

Thread Reader App1 yıl önce

@akshay_pachaar @GabrielRymberg Namaste, please find the unroll here: Enjoy :) 🤖

Abhivendra Singh profil fotoğrafı

Abhivendra Singh1 yıl önce

AI coding assistants must evolve at the pace of our ambitions. Faster inference and longer context lengths are only the beginning. True understanding requires deep learning and adaptability.

Ian profil fotoğrafı

Ian1 yıl önce

Hi Akshay, very interesting! I've tried installing this and it crashes constantly. Lots of comments on the PyCharm plugin are the same. I don't suppose you have any tips?

Totalremoto profil fotoğrafı

Totalremoto1 yıl önce

Yo @akshay_pachaar, sounds like you put that new coding assistant through the wringer with a whopping 34k+ lines of code! Impressive stuff. AI models are definitely leveling up faster than my grandma's knitting skills.

Pranav Agarwal profil fotoğrafı

Pranav Agarwal1 yıl önce

Looks good

Benzer Videolar

Nothing beats Augment Code answering questions about large codebases. It's a free extension (works in VSCode, JetBrains, and NeoVim), and has a community edition you can run for free forever. Try this experiment: 1. Download any large open-source project from GitHub 2. Augment will index the code 3. Start asking questions about the codebase 4. Do the same using any other coding agent 5. Compare the speed and the depth of the answers you get If you have a small codebase, the differences with other coding agents won't be obvious, but if you are working on a large project, things will click immediately. Suggestion: download the Keras repository (~180,000 lines of code). I know the library well, and the answers I got from Augment were pretty impressive. By the way, Augment is a fully-fledged AI coding assistant. You can use its agent in every imaginable way: • To implement brand new functionality • To make quick edits to your code • To refactor existing functionality • To generate unit tests • To generate documentation • To handle GitHub—pull requests, commits, branching, etc My favorite feature is their "Next Edit" functionality: 1. You edit the code 2. Augment analyzes the change (across the entire codebase!) 3. Augment determines the ripple effects of that change 4. Augment suggests everything you need to update Here is a link to the tool: Thanks to the team at Augment Code for partnering with me on this post.

Santiago

34,977 görüntüleme • 1 yıl önce

1. Augment Agent is the first AI coding assistant designed for professional software engineers working with large codebases. I built an Amazon clone using Augment Agent in just a few minutes.

1. Augment Agent is the first AI coding assistant designed for professional software engineers working with large codebases. I built an Amazon clone using Augment Agent in just a few minutes.

Poonam Soni

60,060 görüntüleme • 1 yıl önce

The #1 problem with coding agents right now: Ask them to solve one problem, and they will make 10 other changes you didn't want. This happens to me every day. It happens to everyone I talk to as well. We have a solution for this now. The team Augment Code released a "Task List" feature for their coding assistant that solves this problem. Augment Code is partnering with me on this post. In case you haven't used them before: • Augment Code is a fully-fledged coding assistant • Their specialty are large projects • Fastest coding indexing I've seen • Has a free forever community edition Now, you can ask their coding agent to generate a Task List before doing anything. This will give you a plan you can review, edit, and augment if you need to. You can export this plan, load it on a different session, or even share it across projects. It makes a huge difference: The task list constrains the agent so you won't get any "unintended" changes anymore. It also puts you in control of everything the agent does. Check the video to see the agent working through a task list. You can also try this 100% free: (By the way, they also have support for remote agents. You can basically have those agents write your code while you are sleeping.)

The #1 problem with coding agents right now: Ask them to solve one problem, and they will make 10 other changes you didn't want. This happens to me every day. It happens to everyone I talk to as well. We have a solution for this now. The team Augment Code released a "Task List" feature for their coding assistant that solves this problem. Augment Code is partnering with me on this post. In case you haven't used them before: • Augment Code is a fully-fledged coding assistant • Their specialty are large projects • Fastest coding indexing I've seen • Has a free forever community edition Now, you can ask their coding agent to generate a Task List before doing anything. This will give you a plan you can review, edit, and augment if you need to. You can export this plan, load it on a different session, or even share it across projects. It makes a huge difference: The task list constrains the agent so you won't get any "unintended" changes anymore. It also puts you in control of everything the agent does. Check the video to see the agent working through a task list. You can also try this 100% free: (By the way, they also have support for remote agents. You can basically have those agents write your code while you are sleeping.)

Santiago

41,738 görüntüleme • 11 ay önce

AI coding tools are everywhere. Yet they all fall short when scaling to 100s of developers and complex codebases. We’re solving this problem Augment Code. Introducing Augment Code, the first developer AI purpose-built for teams.🧵

AI coding tools are everywhere. Yet they all fall short when scaling to 100s of developers and complex codebases. We’re solving this problem Augment Code. Introducing Augment Code, the first developer AI purpose-built for teams.🧵

Scott Dietzen

91,368 görüntüleme • 1 yıl önce

🤖 Meet Agent Mode in JetBrains AI Assistant for VS Code! 🔗 Go beyond simple code completion and delegate complex coding tasks to our AI agent that can: ✨ Analyze your entire codebase ✨ Make multi-file edits simultaneously ✨ Handle intricate refactoring operations ✨ Solve complex programming challenges under your supervision Think of it as having an intelligent coding partner that understands your project context and can execute sophisticated tasks while you maintain full control.

🤖 Meet Agent Mode in JetBrains AI Assistant for VS Code! 🔗 Go beyond simple code completion and delegate complex coding tasks to our AI agent that can: ✨ Analyze your entire codebase ✨ Make multi-file edits simultaneously ✨ Handle intricate refactoring operations ✨ Solve complex programming challenges under your supervision Think of it as having an intelligent coding partner that understands your project context and can execute sophisticated tasks while you maintain full control.

JetBrains

15,129 görüntüleme • 1 yıl önce

Augment Agent is now live. Designed for large-scale codebases — with 200K context tokens, persistent memory, and deep tool integrations, Augment Agent is available in VS Code and JetBrains.

Augment Agent is now live. Designed for large-scale codebases — with 200K context tokens, persistent memory, and deep tool integrations, Augment Agent is available in VS Code and JetBrains.

Augment Code

147,268 görüntüleme • 1 yıl önce

Every AI startup is focused on "Build me an ........... app" (New projects) But what about millions of existing codebases on GitHub with billions of lines of code? To focus on existing codebases, I built a coding environment: Codespace. (Explained below)

Every AI startup is focused on "Build me an ........... app" (New projects) But what about millions of existing codebases on GitHub with billions of lines of code? To focus on existing codebases, I built a coding environment: Codespace. (Explained below)

CJ Zafir

13,832 görüntüleme • 10 ay önce

Most AI models feel like assistants. MiniMax M3 felt like a teammate. I used Cursor + the MiniMax M3 API to build TweetGen — a tool that generates tweets instantly for any topic. What surprised me wasn’t just the speed, but how naturally M3 handled the whole workflow. It scaffolded the repo, wrote clean code, corrected itself, and kept context across iterations. I wasn’t nudging it line by line — it was committing changes like a real collaborator. Instead of “AI that helps you code,” it felt like “AI that codes with you.” That shift is huge.

Most AI models feel like assistants. MiniMax M3 felt like a teammate. I used Cursor + the MiniMax M3 API to build TweetGen — a tool that generates tweets instantly for any topic. What surprised me wasn’t just the speed, but how naturally M3 handled the whole workflow. It scaffolded the repo, wrote clean code, corrected itself, and kept context across iterations. I wasn’t nudging it line by line — it was committing changes like a real collaborator. Instead of “AI that helps you code,” it felt like “AI that codes with you.” That shift is huge.

Mr. Jason💡

12,304 görüntüleme • 21 gün önce

Meet Boxy, your new AI coding assistant 🤖 🧠 Has the full context of your project 🌱 Generates code in seconds 🔥 Refactors code from the UI 💬 Writes meaningful commit messages Read the full post or see the highlights below 👇

Meet Boxy, your new AI coding assistant 🤖 🧠 Has the full context of your project 🌱 Generates code in seconds 🔥 Refactors code from the UI 💬 Writes meaningful commit messages Read the full post or see the highlights below 👇

CodeSandbox

103,493 görüntüleme • 3 yıl önce

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.

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 görüntüleme • 7 ay önce

I've seen a lot of AI coding tools, but most are just copilots in a sidebar or in a black box form like Claude code. This one is different. I recently came across the new TRAE SOLO, and it’s not an assistant... It's more like a full AI engineer who plans and executes entire projects. The key point is that it has a GUI, which allows the development process to be clearly visible.

I've seen a lot of AI coding tools, but most are just copilots in a sidebar or in a black box form like Claude code. This one is different. I recently came across the new TRAE SOLO, and it’s not an assistant... It's more like a full AI engineer who plans and executes entire projects. The key point is that it has a GUI, which allows the development process to be clearly visible.

Francesco Ciulla

75,035 görüntüleme • 7 ay önce

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.

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

64,399 görüntüleme • 7 ay önce

Introducing "codebase to course", a skill that turns any codebase into an interactive coding course So that you can learn coding through your own projects, complete with visualization, plain-English code translations, metaphors, even quizzes... I vibe code a lot but have no idea how the code works under the hood. This is how I think "learning to code" should be in the AI age: Build first, learn later Link below

Introducing "codebase to course", a skill that turns any codebase into an interactive coding course So that you can learn coding through your own projects, complete with visualization, plain-English code translations, metaphors, even quizzes... I vibe code a lot but have no idea how the code works under the hood. This is how I think "learning to code" should be in the AI age: Build first, learn later Link below

Zara Zhang

202,530 görüntüleme • 3 ay önce

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Santiago

296,363 görüntüleme • 9 ay önce

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

172,420 görüntüleme • 19 gün önce

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

Andrew Ng

1,224,137 görüntüleme • 1 yıl önce

Need a little help building your islands? The Epic Developer Assistant Beta is here to lend a hand! This new AI-powered assistant helps you write Verse code for your UEFN projects, provides answers, workflow guidance, code snippets, and more. Check it out now on the Epic Developer Community:

Need a little help building your islands? The Epic Developer Assistant Beta is here to lend a hand! This new AI-powered assistant helps you write Verse code for your UEFN projects, provides answers, workflow guidance, code snippets, and more. Check it out now on the Epic Developer Community:

Fortnite Developers

118,161 görüntüleme • 1 yıl önce

AI has completely changed coding. Bytedance has just launched an IDE called Trae AI, a powerful new AI coding assistant that helps you code faster and smarter. It's 100% free... 🤯 Here's how it works:

AI has completely changed coding. Bytedance has just launched an IDE called Trae AI, a powerful new AI coding assistant that helps you code faster and smarter. It's 100% free... 🤯 Here's how it works:

Angry Tom

297,480 görüntüleme • 1 yıl önce