About This Directory

I'm Kaushik Rajan — founder, engineer, and computer scientist. I built this directory to help developers evaluate AI tools for software engineering with objective, evidence-based analysis rather than marketing claims.

This directory covers the full spectrum of AI-powered development tools: code editors like Cursor and Windsurf, IDE extensions like GitHub Copilot, conversational AI like ChatGPT and Claude Code, code review tools like Snyk Code, terminal assistants like Warp, and workflow orchestration platforms like Aviator Runbooks. Each category serves different stages of the development lifecycle.

Every tool is tested hands-on. I verify data monthly and update content as tools evolve. For more about my work and applications, visit kaushikrajan.me.

How I Build: AI-Assisted, Human-Directed

I believe in transparency about my development process. This directory is built using a team of AI agents with human-in-the-loop feedback.

What AI helps with:

• Research acceleration: AI agents help aggregate information from official sources, documentation, and user reviews—I verify and curate what's included.
• Content generation: AI assists with drafting comparison tables, feature lists, and structured content—I review, edit, and approve everything published.
• Code development: AI helps write and debug the site code—I architect the system and own the final implementation.

What stays human:

• Editorial judgment: I decide what tools to include, how to position them, and what methodology to use.
• Quality control: Every page is reviewed before publishing. Pricing is verified against official sources. Claims are checked.
• Hands-on testing: Every tool is tested hands-on. I verify data monthly and update content as tools evolve.

I own all the work and output. AI is a tool in my workflow—like a very capable research assistant—not a replacement for judgment, expertise, or accountability. The decisions, the mistakes, and the successes are mine.

Evaluation Methodology

I use a systematic 100-point scoring framework across four weighted categories:

• AI Capabilities (45%): Code generation quality, contextual awareness (single-file to project-wide), feature breadth including refactoring, test generation, security scanning (and specialized tools like Snyk Code), and debugging.
• Developer Experience & Integration (25%): IDE integration quality, performance, reliability, and language support.
• Usability & Support (15%): Ease of use, documentation quality, and customer support responsiveness.
• Pricing & Value (15%): Cost structure, pricing clarity, and overall value proposition.

The goal is to help developers choose tools based on demonstrated capabilities. For broader context on the AI coding landscape, explore the industry statistics covering market size, adoption, and productivity impact.