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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 🚀

276,711 subscribers

30,799 次观看 • 1 年前 •via X (Twitter)

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Akshay 🚀 的头像

Akshay 🚀1 年前

Try Augment Code now:

Coral AI News 的头像

Coral AI News1 年前

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

Avi Chawla 的头像

Avi Chawla1 年前

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

Inforida 的头像

Inforida1 年前

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 的头像

Sean Dorofeev1 年前

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 的头像

Gabriel Rymberg1 年前

@threadreaderapp unroll

Thread Reader App 的头像

Thread Reader App1 年前

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

Abhivendra Singh 的头像

Abhivendra Singh1 年前

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 的头像

Ian1 年前

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 的头像

Totalremoto1 年前

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 的头像

Pranav Agarwal1 年前

Looks good

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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

34,856 次观看 • 1 年前

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.

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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.)

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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.🧵

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Scott Dietzen

91,325 次观看 • 1 年前

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🤖 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

15,003 次观看 • 1 年前

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.

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Augment Code

147,001 次观看 • 1 年前

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.

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12,097 次观看 • 1 天前

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)

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CJ Zafir

13,832 次观看 • 10 个月前

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CodeSandbox

103,362 次观看 • 3 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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28,027 次观看 • 6 个月前

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Santiago

64,399 次观看 • 6 个月前

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 次观看 • 7 个月前

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

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Zara Zhang

180,555 次观看 • 2 个月前

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:

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Santiago

296,355 次观看 • 8 个月前

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.

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EyeingAI

26,587 次观看 • 1 年前

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118,161 次观看 • 1 年前

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297,480 次观看 • 1 年前

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Alex Finn

63,789 次观看 • 10 个月前