The primary technical strain point for an image-based, real-time verification assistant lies in parsing highly ambiguous, dense, or non-standard workspace layouts. If you submit a cluttered IDE view to verify a coding block habit, or a complex terminal log stream to prove a deployment goal, Neo's parsing layer can experience contextual hallucinations—either misinterpreting the code execution state or stalling under high-resolution image payloads. The AI requires more transparent debugging logs within the review desk interface to explain why a submission failed verification, rather than outputting a flat rejection. Additionally, because the points ledger utilizes rigid ledger balance mechanics, correcting an invalid penalty or resolving an unfair squad peer-review dispute requires an awkward manual adjustment workflow that can feel overly punitive during active crunches.
