@levelsio Voice gives 2.5x more data by volume than text forms (Höhne 2024, N=1001)—add physical queues and official stats end up measuring reporting friction, not real crime.
@Suryanshti777 Voice context hits 1,616 chars vs 163 in text, but raw meeting memory gets noisy fast. Do you index raw transcripts or extract into a structured schema first?
To founders evaluating early startup ideas:
How do you set a decision threshold before building?
Do you define explicit criteria to pass or fail?
Or do you rely on qualitative founder intuition?
@Suryanshti777 How do you filter casual chatter from actual commitments? We extract 13 of 14 structured fields from live conversations, but passive multi-source tracking usually gets noisy fast.
Everyone assumes synthetic focus groups are generic AI prompts.
We build target personas on posts from 11 platforms.
Single-prompt personas produce shallow validation.
Reliable feedback requires multi-source behavioral data.
@dannypostma Are you running WebGL or WebGPU for these? We hit frame budget bottlenecks when syncing audio streams with custom avatar shaders in production.
@simonw Cheap models hallucinate heavily on raw web fetches. We split research into 6 execution phases rather than a single pass—do you handle URL parsing in one prompt or chain specialized stages?