Hey everyone,
I’ve been experimenting with different AI tools for university work, and I keep seeing people recommend using a “stack” (e.g., ChatGPT + Claude + Perplexity + NotebookLM), where each tool is used for a specific task.
However, I’m starting to wonder if this is actually more efficient, or just overcomplicating things.
From my experience, switching between tools can:
- Break workflow continuity
- Create inconsistencies in outputs
- Add friction when managing sources and drafts
At the same time, different models clearly excel at different things (reasoning, writing style, sourcing, etc.).
So I’m curious:
👉 Do you think using multiple AI tools is genuinely better for academic work, or is it mostly overkill?
👉 Has anyone tried sticking to a single model and optimizing around it instead?
Interested in hearing real experiences, especially from students or researchers.
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