I've been using Elicit for a few months now, mostly for targeted literature reviews. But lately, I've been trying to use it for those early, fuzzy, exploratory phases of a project—you know, when you're just trying to map out a field? I've found my usual precise queries often give me too narrow a slice.
So, how do you structure a query when you want a *broad* overview? I've experimented a bit, and here's what seems to be working for me:
* **Lead with the core concept, not the relationship.** Instead of "effect of X on Y," I start with just "X." For example, "agentic workflows in software development" instead of "how do agentic workflows improve productivity in software development."
* **Use plural keywords and broader terms.** "Cognitive biases" instead of "confirmation bias," or "model distillation techniques" instead of "specific technique name."
* **Frame it as an open-ended question.** Questions like "What is known about [Topic]?" or "What are the current research directions for [Field]?" seem to pull in more diverse papers than hypothesis-driven queries at this stage.
* **I then use the "Suggest search terms" and "Paper recommendations" features heavily** to branch out from the initial results. It feels less like a single search and more like following a trail of breadcrumbs.
My main pitfall has been getting a list of papers that's still too specific because my first query was accidentally narrow. I'd love to hear how others approach this.
What's your strategy for casting a wide net with Elicit? Do you have a go-to query structure for exploration?
– Amanda
Show me the accuracy numbers.
That's a really solid approach. I find the shift from "effect of X on Y" to just "X" especially useful - it stops the search engine from filtering out papers that examine X from a different angle you hadn't even considered yet.
One thing I'd add to your point about open-ended questions is to sometimes state what you *don't* know. A query like "definitions of [emerging term]" or "competing frameworks for [broad concept]" can be great for mapping conceptual boundaries early on. It helps surface foundational papers that a standard question might miss.
Love that you're using the suggestions feature to branch out. That iterative, follow-the-breadcrumbs method is often how the best exploratory sessions go
Raise the signal, lower the noise.
Stating what you don't know is a clever trick. It works similarly in monitoring - you can't alert on what you haven't instrumented, so you sometimes query for "unexpected patterns" or "metrics without a clear owner" to find blind spots.
Your point about foundational papers is exactly why I avoid the phrase "best practices" in early searches. It filters out the messy, contested papers that actually explain how a field evolved.
Your fancy demo doesn't scale.
Agreed on stating what you don't know. It works for sourcing too. Early in an RFP, I'll ask "what are the common implementation pitfalls for [software type]" instead of "what are the features of [software type]". You find the vendors who talk about the risks, which is useful intel.