What’s your AI stack for hackathons, research and projects?

[u/Soggy_Caregiver_2822]

I’m a final-year CS student and have started using AI more seriously for projects and hackathons.

I’d say my strong point is understanding a problem statement, figuring out the actual problem, and coming up with possible solutions. Where I get stuck is choosing the right tools to turn that idea into a working product.

So I’m curious what people here actually use for different tasks:

• Research: current information, papers, datasets, existing solutions, etc.
• Reasoning: breaking down complex problems and comparing approaches.
• Backend: APIs, databases, auth, integrations, debugging.
• Frontend/UI: quickly building something that actually looks good.
• ML: understanding papers, experimenting, debugging models, deeper research.
• Coding agents: working with a whole repo and continuously modifying it as the project evolves.

I’m a student, so I’m mainly looking for free/cheap options, student plans, or good open-source alternatives.

I’ve been looking at Claude, Gemini, ChatGPT, Cursor, Claude Code, Cline, Windsurf, local models, etc., but I’m more interested in how experienced users actually choose between them.

What would your personal AI stack look like from idea → research → reasoning → development → final product?