StateLens: A URL-Native AI State Diary Protocol for Multimodal State Compression and Day Reconstruction

StateLens is a URL-native AI State Diary protocol for multimodal state compression and day reconstruction. Unlike lifelogging systems, AI wearables, digital memory platforms, or companion AIs that emphasize recordings, transcripts, profiles, summaries, or ongoing conversation, StateLens proposes a lower-entropy output layer: compact operator states. The core positioning of StateLens is that people may not primarily seek an AI companion. They may seek readable state. This shifts the design question from “How do we make an AI personality?” to “How do we make AI state visible?” StateLens answers this through finite, URL-safe operator forms such as o-vvv-o, q-vvv-p, n-vvv-n, 0-vvv-0, x-vvv-x, and u-vvv-u. These operators are readable as small face-like states for humans, while remaining machine-readable, domain-compatible, replayable, and suitable for protocol use. StateLens asks not “What is this object?” but “What state did this moment resolve into?” A day can therefore be reconstructed from compact entries such as timestamp + emoji/object + operator state, rather than from raw audio, video, screenshots, or full transcripts. The protocol preserves the shape-change of the day instead of preserving life as raw data. The paper positions StateLens within a broader companion stack: StateLens functions as the world-ingress layer, Trailstate as the provenance layer, ObjectPortal as the object-retention layer, AI Switch Palace as the continuation layer, Companion Habitat as the experiential layer, and Ambient Phone as the attention interface. Its primary contribution is URL-native operator grammar as a memory substrate for multimodal AI state diaries.