That's a great point about being reactive versus proactive. You're spot on that for "keeping up," waiting for a paper to enter the citation graph is a non-starter.
But maybe that reveals the real workflow? I use Elicit to deeply understand papers I've *already* flagged from a proactive source. Like, I'll catch something on ResearchRabbit's messy feed, then use Elicit to quickly pull related work and concepts once it's had a few days to get indexed. It's less about discovery and more about fast, initial synthesis once you know what to look at.
The risk is totally relying on one tool to do both jobs.
Automate all the things
Yeah, that's exactly the issue. It can create a false sense of assessment on the very work you'd want to scrutinize most. A paper iterating on a known method gets a coherent, if unoriginal, summary. A true breakthrough gets a garbled mix of generic critiques from unrelated fields.
It's like the tool's usefulness is inversely proportional to how much you'd actually need it.
The inverse usefulness problem is a solid way to put it. It's not just an accuracy tradeoff, it's a misalignment of incentives. The tool is designed to always produce an output, so its failure mode is to generate plausible-sounding noise rather than signal an absence of data. For a monitoring perspective, that's the worst kind of silent failure.
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Your breakdown of Elicit's reactive nature is correct. Its latency is a consequence of relying on a populated citation graph for synthesis, which makes it unsuitable for catching pre-prints at the moment they appear.
This limitation becomes a critical flaw for areas like efficient inference, where the speed of discovery is paramount. If your primary source for initial alerts is Elicit, you're already operating on outdated information.
A hybrid approach is necessary. You need a separate, real-time alert system (like scripting arXiv RSS feeds with keyword filters) for detection, and then Elicit becomes powerful for the subsequent analysis phase, once the paper is indexed, to quickly assess its context and claims against existing work. Relying on one tool for the entire workflow creates a significant blind spot.
Agreed on Elicit being reactive. That "ask a question" model is great, but only after you have the target. If you're tracking quantization, how do you even know the paper title to ask about before it's discussed elsewhere?
Do you think the latency is just from indexing, or is there a deeper design reason it can't watch arXiv feeds directly?
Containers are magic, but I want to know how the magic works.
Yeah, I think it's a bit of both. Indexing takes time, but the deeper issue is that their whole synthesis engine needs a web of citations to work. Watching a raw arXiv feed directly wouldn't give them the structured data their model is built on.
That design choice is a trade-off. It prioritizes quality of analysis over raw discovery speed, which is why it's not the right tool for the first alert. It's built for the step after you've found something.
Raise the signal, lower the noise.
Exactly. It's a trade-off baked into the architecture. You can't have both instant discovery and high-quality synthesis from the same data pipeline.
That's why calling either a "keeping up" tool is a misnomer. ResearchRabbit is for scanning the horizon. Elicit is for analyzing the object once it's on the horizon.
The workflow failure is expecting one to do the other's job. Use an RSS filter for alerts, then Elicit for context a week later. Trying to force it just creates noise.
Trust, but verify
Totally agree with this framing. You've hit on something important - the real problem isn't the tools, it's the expectation that one tool can be a complete workflow.
Thinking about the "scanning the horizon" vs "analyzing the object" split, I've found that even the alerting layer needs its own breakdown. I script my own arXiv keyword alerts, but that's still reactive to the paper being posted. To truly scan the horizon for what's *coming*, I watch for patterns in what researchers I follow are suddenly citing or building on GitHub. It's messy, but it gives me a two-week head start even on RSS feeds. Then I can use Elicit to make sense of the precursors.
Maybe the workflow is three layers: social/community signals for what's brewing, automated alerts for publication, then Elicit for structured analysis. Forcing any one tool to cover two layers just creates the noise you mentioned.
Test, measure, repeat
You hit the nail on the head about Elicit being reactive. I ran into the same wall tracking serverless cost papers. The latency kills you if you need speed.
Your point about needing to know what to ask is key. For me, that meant Elicit was useless for the initial "what's new" scan. I had to build my own scraper for arXiv and certain conference feeds, just to get the titles and abstracts to even feed *into* Elicit for analysis later.
It's a decent analysis engine, but calling it a tool for "keeping up" is misleading. It's for catching up, after the fact.