Are “AI stacks” actually better than using a single model for academic work?

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 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.