{
  "record_id": "19500161",
  "document_id": "19500161",
  "title": "Object-Bound Agentic Interfaces: Receiver-First Spatial Inventories for Post-Smartphone Computing",
  "pages": 8,
  "authors": [
    "Raynor Eissens"
  ],
  "doi_confirmed_in_pdf": "10.5281/zenodo.19500161",
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  "abstract_extracted": "This paper introduces Object-Bound Agentic Interfaces (OBAI): a post-smartphone interface paradigm in which physical objects function as primary interface anchors, activating spatially bound inventories that contain app shortcuts, dynamic state signals, and agent-generated outputs. In contrast to app-centric and chat-centric interaction models, OBAI operates under a receiver- first logic: object → receive → generate AI output is not immediately generated in abstract interfaces, but is instead triggered by interaction with a real-world object, and may be persistently placed back into that object’s spatial inventory. This paper argues that existing AR systems, object recognition tools, and spatial computing platforms provide partial precedents, but do not implement: • unified object-bound inventories • persistent, fading state layers • integration of apps and agent outputs • autonomous agentic “landing” of outputs into object-specific contexts OBAI defines a new interface primitive: the object as a living, persistent, spatial interface container ⸻ Canonical Definition Object-Bound Agen",
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  "source_pdf_filename": "19500161_Object-Bound Agentic Interfaces Receiver-First Spatial Inventories for Post-Smartphone Computing Raynor Eissens 2026.pdf",
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  "full_text": "=== PDF PAGE 1 ===\nObject-Bound Agentic Interfaces\n\nReceiver-First Spatial Inventories for Post-Smartphone Computing\n\nDOI: 10.5281/zenodo.19500161\n\nRaynor Eissens · Ambient Era Canon · 2026\n\n⸻\n\nAbstract\n\nThis paper introduces Object-Bound Agentic Interfaces (OBAI): a post-smartphone interface\n\nparadigm in which physical objects function as primary interface anchors, activating spatially\n\nbound inventories that contain app shortcuts, dynamic state signals, and agent-generated\n\noutputs.\n\nIn contrast to app-centric and chat-centric interaction models, OBAI operates under a receiver-\n\nfirst logic:\n\nobject → receive → generate\n\nAI output is not immediately generated in abstract interfaces, but is instead triggered by\n\ninteraction with a real-world object, and may be persistently placed back into that object’s\n\nspatial inventory.\n\nThis paper argues that existing AR systems, object recognition tools, and spatial computing\n\nplatforms provide partial precedents, but do not implement:\n\n•\nunified object-bound inventories\n\n•\npersistent, fading state layers\n\n•\nintegration of apps and agent outputs\n\n•\nautonomous agentic “landing” of outputs into object-specific contexts\n\nOBAI defines a new interface primitive:\n\nthe object as a living, persistent, spatial interface container\n\n⸻\n\n=== PDF PAGE 2 ===\nCanonical Definition\n\nObject-Bound Agentic Interfaces are spatial computing systems in which physical objects act as\n\npersistent interface anchors that activate object-specific inventories containing app shortcuts,\n\nchromatic state signals, and agent-generated outputs, with generation occurring only after\n\nobject-based reception.\n\n⸻\n\nCore Principle\n\nTraditional model:\n\ninput → generate → display\n\nObject-Bound model:\n\nobject → receive → contextualize → generate → land\n\nThe object is not the target of output.\n\nThe object is the condition for output.\n\n⸻\n\nProblem Statement\n\nContemporary AI and interface systems exhibit three dominant limitations:\n\n1.\nInterface detachment\n\nInteraction occurs in abstract containers (apps, chats, dashboards)\n\ndisconnected from physical context.\n\n2.\nImmediate generation bias\n\nAI generates output without environmental grounding, leading to\n\noverload, irrelevance, or instability.\n\n3.\nNon-persistent contextualization\n\nOutputs are ephemeral and not anchored to meaningful real-world\n\nstructures.\n\nExisting systems increase capability, but lack situated coherence.\n\nAs identified in prior work, intelligence without environmental support\n\nleads to pressure accumulation and instability  .\n\n⸻\n\n=== PDF PAGE 3 ===\nProposed Architecture\n\nOBAI introduces a three-layer system:\n\n1. Object Layer (Receiver Layer)\n\nPhysical objects act as:\n\n•\nentry points\n\n•\ncontextual anchors\n\n•\nidentity surfaces\n\nExamples:\n\n•\nPlayStation → gaming context\n\n•\nrefrigerator → consumption/logistics\n\n•\nplant → care/temporal cycle\n\n•\nbag → movement/preparation\n\n⸻\n\n2. Spatial Inventory Layer\n\nEach object activates a dedicated inventory interface containing:\n\n•\napp shortcuts (object-relevant utilities)\n\n•\nchromatic state markers (living signals, fading over time)\n\n•\ncontextual actions\n\n•\nagent-generated outputs\n\nThis inventory is:\n\n•\nspatially anchored\n\n•\npersistent\n\n•\ndynamically evolving\n\n⸻\n\n=== PDF PAGE 4 ===\n3. Agentic Layer\n\nAgents operate as:\n\n•\ndetectors (events, updates, signals)\n\n•\ninterpreters (context relevance)\n\n•\nproducers (outputs, suggestions, actions)\n\nCrucially:\n\nAgents do not output globally.\n\nThey land outputs into object-specific inventories.\n\n⸻\n\nInteraction Model\n\nMinimal loop:\n\nscan → reveal → select → generate → land → fade\n\nExpanded:\n\n1.\nUser observes or scans object\n\n2.\nObject activates spatial inventory\n\n3.\nUser selects or inspects chroma/app\n\n4.\nAI generates context-specific output\n\n5.\nOutput is placed back into inventory\n\n6.\nState decays over time (fade / afterfield)\n\nThis extends the ARC-1 logic of field-first interaction and afterfield\n\ndecay into a general interface paradigm  .\n\n⸻\n\n=== PDF PAGE 5 ===\nReceiver-First Logic\n\nThe defining inversion:\n\nGeneration is not primary.\n\nReception is primary.\n\nAI output is:\n\n•\ndelayed until context exists\n\n•\ngrounded in object presence\n\n•\nspatially returned to that context\n\nThis resolves:\n\n•\ninterface overload\n\n•\nnotification drift\n\n•\ncontext fragmentation\n\n⸻\n\nRelation to Prior Art\n\nClosest precedents include:\n\n•\nobject-centric AR interaction systems\n\n•\nspatial UI anchored to surfaces\n\n•\nmultimodal AI with contextual outputs\n\nHowever, no identified system combines:\n\n•\npersistent object-bound inventories\n\n•\napp + agent unification\n\n•\nautonomous output landing\n\n•\nreceiver-first generation logic\n\nThus:\n\nPartial prior art only.\n\nThe novelty lies in the integration and structural coupling of these elements.\n\n⸻\n\n=== PDF PAGE 6 ===\nSystem Properties\n\nOBAI systems exhibit:\n\n•\nsituated intelligence\n\n•\npersistent context memory\n\n•\nlow-symbolic signaling (chroma, fade, presence)\n\n•\nenvironmental UI distribution\n\n•\nnon-intrusive output delivery\n\n⸻\n\nConceptual Shift\n\nFrom:\n\n•\napp-centric computing\n\n•\nfeed-based interaction\n\n•\nnotification systems\n\n•\nchat-based AI\n\nTo:\n\n•\nobject-centric computing\n\n•\nenvironment-bound interaction\n\n•\nambient state signaling\n\n•\nagentic contextual landing\n\n⸻\n\nExample\n\nObject: PlayStation\n\nInventory contains:\n\n•\ngame shortcuts\n\n•\nfriend presence indicators\n\n•\nagent-generated recommendations\n\n•\ncall actions\n\n•\nlive chromatic states\n\nAgent detects new JRPG →\n\nlands result as chroma →\n\nuser opens →\n\n=== PDF PAGE 7 ===\ncontent generated on demand\n\nNo global notification required.\n\n⸻\n\nRelation to Reasoning Systems\n\nOBAI operates as an interface layer.\n\nIt may be supported by underlying reasoning systems such as structured routing architectures\n\n(e.g. operator-based reasoning stacks) that refine output prior to externalization  .\n\nHowever, OBAI itself defines:\n\nwhere output appears, not how reasoning is performed.\n\n⸻\n\nWhy It Matters\n\nAs AI becomes agentic, persistent, and ambient:\n\n•\noutput volume increases\n\n•\ncontext fragmentation increases\n\n•\nuser overload increases\n\nOBAI introduces:\n\nenvironment as interface\n\nobject as anchor\n\npresence as filter\n\nThis transforms AI from:\n\na system that produces outputs\n\ninto:\n\na system that places meaning where it belongs\n\n⸻\n\n=== PDF PAGE 8 ===\nConclusion\n\nObject-Bound Agentic Interfaces define a new interface primitive:\n\nthe physical object as a living, spatial, persistent interface\n\nThey resolve key limitations in current AI interaction models by:\n\n•\ngrounding output in context\n\n•\ndelaying generation until reception\n\n•\ndistributing interaction across the environment\n\nThe result is a system where:\n\ninterfaces are not opened\n\nbut\n\nrevealed in place\n\n⸻\n\nKeywords\n\nobject-bound interface, spatial computing, agentic AI, ambient interface, AR interaction,\n\nreceiver-first systems, contextual AI, chromatic interface, spatial inventory, post-smartphone UI,\n\nambient era\n\n⸻\n\nOne-Sentence Version\n\nPhysical objects become the primary interface, and AI outputs land where they are needed\n\ninstead of appearing everywhere."
}