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Better Cursor alternative? I've been playing with the new AI IDE Windsurf launched by Codeium past few days, and the result was impressive, particularly: 1. Code base understanding: One thing Windsurf did really well is its understanding of the whole code base & dependencies; This led to a big... difference in terms of final code quality 2. Context aware: It actually knows everything I did in the editor, e.g. it automatically knows code edits I made without me prompt it; 3. Reflection: I noticed Windsurf has been finetuned to reflect and try to iterate/improve code it generated autonomously; This was a magic moment for me .... I shared key highlights i had and showcase my process of building a PDF converter product using windsurf 0:00 Platform overview 6:21 How does context aware engine works 10:45 Case study: Build PDF converter Sass ---- If you have any further question or want to get deep dive into more AI coding, you can join my community where I post tips weekly:show more

Jason Zhou

29,101 subscribers

64,713 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 10

Фото профиля Julian Harris

Julian Harris1 год назад

@codeiumdev If I’m working with APIs or libraries that are new or changed in the last 12 months (hint: almost everything) the only way code-gen works reliably for me is if there’s a web search in the loop. I’ve struggled to get Cursor to do this reliably. What about Windsurf?

Фото профиля Jason Zhou

Jason Zhou1 год назад

@codeiumdev Ideally yes.. I just paste doc in, and I found windsurf follows better than cursor in my experience; But still, it tends to revert back to old knowledge unless you prompt it hard

Фото профиля Edwardooo

Edwardooo1 год назад

@codeiumdev I have been using cursor for three months daily. I just tried Windsurf. I say it is pretty smart. It learned the code base to make a new page that plot all the locations. (with auto zoomout to see all the spots )

Фото профиля Phatic

Phatic1 год назад

@codeiumdev Welp

Фото профиля Jason Zhou

Jason Zhou1 год назад

@codeiumdev Oh woah, didn’t know about this, pretty exciting

Фото профиля Louiepecan.base.eth🗡🛡

Louiepecan.base.eth🗡🛡1 год назад

@codeiumdev @grandorganics

Фото профиля George Siosi Samuels

George Siosi Samuels1 год назад

@codeiumdev Just downloaded

Фото профиля Axel Sachmann

Axel Sachmann1 год назад

@codeiumdev Thx for the great presentation 🙏

Фото профиля konstantinpaulus

konstantinpaulus1 год назад

@codeiumdev

Фото профиля pharo

pharo1 год назад

@codeiumdev I tried it today Feels more powerful than cursor But I have to test it more

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Is Windsurf better than Cursor? impossible to say, but... it does one thing better: soooo... I spent an hour testing windsurf... and this is what i created... and app called "boop-boop" lol... one thing windsurf does is it searches the internet. If you've been watching my videos you know that i go to perplexity all the time to get code examples and docs. but with windsurf you can just say, "search the replicate top image gen models and add them to the chat we just created" It will search the internet, find the right model then write the code. This is great for replicate and openrouter. You can have one api key in your .env file then just tell windsurf to search for docs for [insert ai model] and it will just add it to your app. Impressed tbh.

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Riley Brown

31,043 просмотров • 1 год назад

Have you ever vibe coded 6 versions of same app at the same time using all of the best AI coding tools. Well I did it in this video: Tools used: Cursor Cursor Windsurf @windsurf Replit Replit ⠕ Bolt bolt.new Lovable v0 TimeStamps 00:00 - Introduction to AI Coding Tools 01:23 - First Prompts 05:56 - Final Adjustments and Comparisons 16:12 - Results / Rankings don't worry a cancelled my api keys

Have you ever vibe coded 6 versions of same app at the same time using all of the best AI coding tools. Well I did it in this video: Tools used: Cursor Cursor Windsurf @windsurf Replit Replit ⠕ Bolt bolt.new Lovable v0 TimeStamps 00:00 - Introduction to AI Coding Tools 01:23 - First Prompts 05:56 - Final Adjustments and Comparisons 16:12 - Results / Rankings don't worry a cancelled my api keys

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I've been playing with MiniMax M3 recently. The combination of coding, agent workflows, 1M context, and multimodal understanding made me curious enough to try something real. So I gave it one task: "Build me a Skill Hub to manage all my Claude Code skills."👇

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ares. 🎧

49,239 просмотров • 3 месяцев назад

Write 100x better code using AI (for free!) Install the Codacy extension (VSCode, Cursor, WindSurf). This will install an MCP Server locally on your computer. Your coding copilot will use this server with the Codacy CLI to check every line of code it generates. The way this works is pretty awesome (assuming you are using Cursor): 1. You ask Cursor to generate some code 2. Cursor writes the code 3. Cursor then calls Codacy's MCP Server to check it 4. The MCP Server will use the Codacy CLI to find any issues 5. Cursor will fix the issues and call the MCP server again 6. When the code passes all checks, you are done Level of effort on your side: literally zero! Code quality and security because of this: 100x better! Codacy has been doing this for a long, long time, and their Guardrails MCP Server checks for a lot of potential issues: • Security issues • Quality standards • Pattern violations • Linting issues You can see more information about the extension here: I recorded a quick video to show you how it works. Thanks to the Codacy team for helping me set up everything, answering my 1,000 questions, and collaborating with me on this post.

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Santiago

63,316 просмотров • 1 год назад

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.

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Akshay 🚀

30,865 просмотров • 1 год назад

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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Santiago

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101,068 просмотров • 2 лет назад

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sourcery

149,352 просмотров • 8 месяцев назад

Notion's Head of Product Max Schoening : "I actually don't care at all whether designers write code that lands in production. The reason I like designers thinking in code is that it forces you to consider the medium. I would much rather take a designer or PM who has a deep affinity for understanding how agent loops work than someone who can ship PRs. And the only way that you can actually get to understanding agent loops is by building them in the material that they're made of, which is currently code. That's why I care that designers 'code.' Not because of the utility of shipping to production, but because it forces you to really interrogate the material that you're designing with."

Notion's Head of Product Max Schoening : "I actually don't care at all whether designers write code that lands in production. The reason I like designers thinking in code is that it forces you to consider the medium. I would much rather take a designer or PM who has a deep affinity for understanding how agent loops work than someone who can ship PRs. And the only way that you can actually get to understanding agent loops is by building them in the material that they're made of, which is currently code. That's why I care that designers 'code.' Not because of the utility of shipping to production, but because it forces you to really interrogate the material that you're designing with."

Lenny Rachitsky

76,527 просмотров • 4 месяцев назад

I built an agent that answers machine-learning questions. It's autonomous, and the best part is that I built the whole thing without writing a single line of Python code. Here is what I did and how I did it: Over a year ago, a friend and I built a site that publishes multi-choice questions. You get a new one every day. I decided to have GPT-3.5 answer questions. Here is what I needed to build: 1. Connect to the site's API to retrieve today's question 2. Extract the question and the potential choices 3. Connect to OpenAI's API and ask GPT-3.5 to answer the question 4. Parse the answer from the model 5. Submit the answer back to the API to get the score Not difficult. Likely several hours of work. But I didn't have to write any code. I built the whole thing by dragging and dropping components using Vellum is a YC-backed platform for developers to build LLM applications. They are the only ones I've seen offering this functionality. They sponsored this post, and their team helped me with all my questions while I built this. I created a workflow. The platform supports several node types to build whatever you have in mind. I show how I put the whole thing together in the attached video. The only code I had to write was a few lines of Jinja to parse and transform the API and the LLM results. There are three lessons I want to share from this experience: First, the best possible code is the one you didn't write. I'm a big fan of no-code tools because they help me materialize my ideas fast. They help product people, designers, and no coders collaborate on the solution. Second, Large Language Models are sensitive to how you prompt them. Small changes to prompts can make a big difference in results. This is more pronounced when you are building a multi-step workflow. Third, automated testing and evaluation for prompts is critical. There aren't many companies thinking about this. They'll have a hard time moving from a demo phase. The attached video will show you what I did.

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Santiago

309,825 просмотров • 3 лет назад

This might be the best "AI Engineer" I've tried so far. I'm an old school developer who started 30 years ago. I feel very uncomfortable letting AI take control of my code, but for the sake of science, I spent two hours building an application that took me weeks to build a couple of years ago. I used Pythagora, a brand new tool backed by Y Combinator. They just released to the public. Keep in mind that I use AI every day to write code, but Pythagora is something different: it's a tool that leads, and uses you—the human—as the copilot. I go into more details in the video, but here is the TLDR; 1. Holy molly! We've made a ton of progress on this front! This is way better than Devin when I tested it a few months back. 2. Love the approach of generating a plan with sub-tasks before writing any code. 3. The tools never tries to do too much: it tackles every small task one at a time, and gives you instructions so you test everything. 4. It does exactly what you'd do when it gets stuck: writes a bunch of logs and uses those to correct itself. Pretty neat! 5. It's fast. It runs locally. It's an extension to Visual Studio Code. I'm impressed, but I don't think this tool is for me. I'm not the type of developer who's ready to relinquish control. I felt I had no connection with the code because I didn't write it. It was not my code. I know many people who don't care about this. I know many people who will get tremendous value out of Pythagora. I hope they keep pushing the limits, providing feedback, and helping this get to a point where old folks like me feel more comfortable using it. Don't take my word for it. The best thing you can do is to give it a try and see how you feel using it. Thanks to the team who built this, for all of the explanations and support, and especially, for sitting and listening to my dumb questions for 2 hours while I tested this.

Santiago

212,056 просмотров • 1 год назад