everyone keeps confusing "AI research agent" with ChatGPT for papers

Every time someone says "just use ChatGPT for your lit review" I lose a year off my lifespan. A summary is not research. A summary is what you do when you already know what you're looking for. Research is the opposite, you're staring at 200 papers across 4 subfields trying to figure out where the gap even is, let alone how to design an experiment around it. What an actual research agent needs to do is way more than Q&A. Take a vague research goal like "understand why method X underperforms on domain Y" and break it into sub-questions you can act on. Read 80 papers, map the citation network, tell me which 5 actually matter and why the rest are incremental. Compare proposed approaches, flag assumptions that don't hold, suggest baselines you'd forget. Take messy experimental results, run the right tests, catch that your sample size is underpowered before reviewer 2 does. ChatGPT does none of this. It gives you a paragraph. A well-formed paragraph, sure, but you still have to do all the connecting, planning, and debugging yourself. I've been trying out mira ai science and it's the first thing I've seen that actually attempts the full workflow instead of stopping at "here's a summary." It takes a research objective, decomposes it into subtasks, runs lit analysis across a corpus, and helps structure experiment design and data analysis. It's def not perfect though. The task decomposition can be too aggressive sometimes and hallucinate sub-questions that don't make sense for a specific domain. But at least the architecture is built for multi-step research execution, not single-turn answers. The point isn't that one tool beats another. It's that "AI research assistant" has become a meaningless label because everyone slaps it on a chatbot wrapper. If it can't hold a research goal across multiple steps and actually act on it, it's not a research agent. It's a search bar with extra steps.