Artificial intelligence is only useful here if it improves judgment. A terminal does not become intelligent because you bolt a chat box onto it.
For a product like Lurk, the system has to get better at identifying what matters, what is fragile, what is misaligned, and what deserves action first.
Where the intelligence should live
Prediction markets are structured, time-sensitive, rule-heavy systems. That makes them a bad fit for pure prompt theater and a much better fit for structured reasoning, deterministic checks, targeted models, and strong evaluation.
The proprietary value should live in the internal market representation, the scoring logic, the recommendation layer, and the feedback loop that improves all of it over time.
What language models are for
Language models are useful for translation, summarization, and handling messy user requests. They are not where the core market judgment should originate.
Users do not need eloquent nonsense. They need the system to rank better, filter better, and explain clearly why something deserves attention.
The actual stack
So when we talk about AI in Lurk, we are talking about a stack of engines: structured inputs, symbolic checks, narrow learned components where they are useful, and a clean interface layer on top.
That is how you get less noise, better prioritization, better personalization, and a product that compounds instead of pretending.