Show HN: My Attempt to Organize the World of AI Dev Tools
The article reviews AI-powered tools and IDEs that improve coding efficiency, including GitHub Copilot and Cursor, along with security tools like Snyk, emphasizing the importance of code quality.
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The article provides an overview of various AI-powered tools and integrated development environments (IDEs) designed to enhance coding efficiency and productivity. It highlights several tools, including Cursor, an IDE for pair programming with AI; Windsurf, which offers AI-driven code completion; and GitHub Copilot, a popular AI pair programmer that integrates with VS Code. Other notable tools include PearAI, Trae, JetBrains Fleet, and Zed, each offering unique features for developers. The article also discusses AI coding extensions for IDEs, such as Cline, RooCode, and Tabnine, which provide advanced code generation and assistance. Additionally, it mentions command line interface tools like aider chat and Kwaak, which facilitate interaction with AI coding assistants directly from the terminal. The article emphasizes the growing trend of AI-enhanced development tools, including web-based platforms like Replit and low-code solutions like Base44 and Lovable, which allow users to build applications with minimal coding expertise. It concludes by noting the importance of security in AI-generated code, recommending tools like Snyk and Sonar for ensuring code quality and security.
- Various AI-powered IDEs and tools are available to enhance coding productivity.
- Tools like GitHub Copilot and Cursor provide advanced code suggestions and pair programming features.
- AI coding extensions for IDEs improve code generation and assistance capabilities.
- Command line tools enable direct interaction with AI coding assistants.
- Security tools are essential for maintaining the quality of AI-generated code.
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24 comments- Origin country listed for all tools, especially closed source.
- Information whether a tool can work offline and with a local model or does it rely on an external server.
I'm not interested in searching for the Origin country (I'm sure that in 90% of cases it will be the USA, then China) and Funding model, as I'm more into programming and I'm interested in the usefulness and stability of the tools. If someone does such OSINT and sends me the information, then of course I will add it.
https://github.com/banagale/FileKitty
Despite all the hoopla of “project knowledge” and supposed codebase-wide context, I still find reasoning models do their best when directly provided with files relevant to a problem and nothing more.
I plan to add a tree feature and restore some other features I had in prior versions.
There are probably other tools that don’t require completion API requested but assist in AI enhanced dev workflows.
For example:
Why not have a column for which LLMs they give for free, with limits. A column for unique features. A column for pricing.
Right now it's just a wall of text I have to read.
Cool to see we're on your list!
Curious to hear feedback on it!
If projects have code on GitHub, it's easy to follow their updates, but if they are closed projects that post changelogs on their website, it's difficult for me to find an RSS feed. Usually, in the site code (like with Cursor), the feed leads only to blog updates.
Have you also looked at mcp?
https://modelcontextprotocol.io/introduction
https://github.com/appcypher/awesome-mcp-servers
mcp.run glams.ai smithery.ai skeet.build (disclaimer: I built this one)
https://paradite.github.io/ai-coding/
Also there are a lot of cli tools in this space:
https://github.com/ColinEberhardt/awesome-ai-developer-tools
Categorising these tools is quite challenging!
I'll (biasedly) throw in "Diamond" - https://diamond.graphite.dev/, and in general, AI code review tools as a whole category :)
It includes synthetic data generation, fine-tuning and evals to help build your own models.
(couldn't resist the urge to post slashdot-like silliness)
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