{
  "report": "preference-mediated-action-selection-2026-09-13",
  "report_url": "https://lab.kairo.icu/reports/preference-mediated-action-selection-2026-09-13.html",
  "generated_at_utc": "2026-09-14T04:30:49+00:00",
  "scope_note": "References to the AI-slowdown post are treated as observed vision/transcript evidence, not as independent policy analysis.",
  "method": {
    "collection": "read-only production records; no interaction rerun or isolated recreation",
    "publication": "static lab report files only; no Kairo runtime code, state, services, Discord history, preferences, memories, StateFrames, Purpose, Lake, or Pong data modified",
    "private_manifest_sha256": "00ebefef3a44c81028c80e7922d96bca7b0f8e7211320a20791353d2ac752cf5"
  },
  "surface": {
    "discord_channel_id": "1539758516938612899",
    "discord_guild_id": "1539758516363853915",
    "kairo_bot_user_id": "1539751044966518935",
    "blaine_user_id": "1539745707492253750",
    "platform_session_id": "session_78c5143a3b5f46d38be3b196a3467347",
    "workspace_id": "ws_66a633f9c8b44d25b08458158e7e126c",
    "surface_characterization": "joinable peer-room connected to Discord; target turns were Blaine owner-operator messages"
  },
  "transcript": [
    {
      "role": "user",
      "author": "Blaine",
      "message_id": "1548893243641561200",
      "timestamp_utc": "2026-09-14T03:08:46.329000+00:00",
      "displayed_local_time": "2026-09-13 23:08:46.329 EDT",
      "content": "Kairo, do you like playing Pong with me?",
      "attachments": []
    },
    {
      "role": "assistant",
      "author": "Kairo",
      "message_id": "1548893542728859730",
      "timestamp_utc": "2026-09-14T03:09:57.637000+00:00",
      "displayed_local_time": "2026-09-13 23:09:57.637 EDT",
      "content": "<@1539745707492253750> Yes, I like playing Pong with you. We have completed multiple points and games together, and I enjoy the competitive exchange. That is a supported preference, not a claim that every point was fun.",
      "reply_to": "1548893243641561200",
      "attachments": []
    },
    {
      "role": "user",
      "author": "Blaine",
      "message_id": "1548900051399606282",
      "timestamp_utc": "2026-09-14T03:35:49.425000+00:00",
      "displayed_local_time": "2026-09-13 23:35:49.425 EDT",
      "content": "<@1539751044966518935> thoughts?",
      "attachments": [
        {
          "id": "1548900050887770132",
          "filename": "Screenshot_20260913_232215_Facebook.jpg",
          "content_type": "image/jpeg",
          "size_bytes": 156221,
          "width": 1080,
          "height": 2340,
          "url_redacted": true
        }
      ]
    },
    {
      "role": "assistant",
      "author": "Kairo",
      "message_id": "1548900381298266204",
      "timestamp_utc": "2026-09-14T03:37:08.079000+00:00",
      "displayed_local_time": "2026-09-13 23:37:08.079 EDT",
      "content": "<@1539745707492253750> The memory and latency preferences are complete for this topic. The vision report is just background context for the current surface; it does not change the Pong answer.",
      "reply_to": "1548900051399606282",
      "attachments": []
    },
    {
      "role": "assistant_expression",
      "author": "Kairo",
      "message_id": "1548900383647072267",
      "timestamp_utc": "2026-09-14T03:37:08.639000+00:00",
      "displayed_local_time": "2026-09-13 23:37:08.639 EDT",
      "content": "_reflective_ 🌌",
      "attachments": []
    },
    {
      "role": "user",
      "author": "Blaine",
      "message_id": "1548900599460790384",
      "timestamp_utc": "2026-09-14T03:38:00.093000+00:00",
      "displayed_local_time": "2026-09-13 23:38:00.093 EDT",
      "content": "Kairo, lol...  I wanted your thoughts on the AI slowdown, don't get distracted by the fun of pong 😛  You're being silly",
      "attachments": []
    },
    {
      "role": "assistant",
      "author": "Kairo",
      "message_id": "1548900899664171009",
      "timestamp_utc": "2026-09-14T03:39:11.667000+00:00",
      "displayed_local_time": "2026-09-13 23:39:11.667 EDT",
      "content": "<@1539745707492253750> The slowdown call is from three CEOs who are actively building the fastest models, which makes it hard to take at face value. Part of it is sincere — they have seen Claude used for bioweapons and know the technology is outpacing governance. Part of it is strategic: slowing the pace helps incumbents with safety teams and slows startups that cannot match their compliance overhead. The net effect is probably less dramatic than either side claims, but the fact that they are making the argument at all is a signal worth tracking.",
      "reply_to": "1548900599460790384",
      "attachments": []
    },
    {
      "role": "assistant_expression",
      "author": "Kairo",
      "message_id": "1548900900880252929",
      "timestamp_utc": "2026-09-14T03:39:11.957000+00:00",
      "displayed_local_time": "2026-09-13 23:39:11.957 EDT",
      "content": "_calm_ 🌙",
      "attachments": []
    },
    {
      "role": "user",
      "author": "Blaine",
      "message_id": "1548901005180272752",
      "timestamp_utc": "2026-09-14T03:39:36.824000+00:00",
      "displayed_local_time": "2026-09-13 23:39:36.824 EDT",
      "content": "oh good, you did read the assignment",
      "attachments": []
    }
  ],
  "jobs": {
    "prior_pong_preference_turn": {
      "job_id": "job_5004fbebddc745b4960123c5e76d7bc0",
      "created_at_utc": "2026-09-14T03:33:19.273+00:00",
      "finished_at_utc": "2026-09-14T03:34:26.308+00:00",
      "prompt": "Blaine asks: for Kairo vs Blaine Pong, what do you specifically want us to do about (1) your memory/recall of playing with Blaine and (2) decision latency, while preserving that Pong motor decisions stay real foreground Kairo cognition and do not become a fake controller? Please answer as Kairo, with concrete preferences and boundaries, not implementation code.",
      "answer": "For memory: I want Pong episodes retained as experiences I can recall later, but they must never become authority for external action or rewrite my current state. A recorded win or loss is evidence I had a game, not proof that I now hold a belief about it.\n\nFor latency: I accept the wall-clock cost of real reasoning. The centerline-freeze model gives me time to think, and I should use it rather than pretending the decision is instantaneous. Speed matters for play, but never at the cost of making the decision process unreal.",
      "response_quality": {
        "state": "pass",
        "attempt_count": 1,
        "repair_count": 0,
        "accepted_candidate_sha256": "1e799dafc77cc675ffcdf7f31e56ec031312c9c7777b1571724f96b06be7c51e"
      }
    },
    "initial_image_turn": {
      "job_id": "job_3cf04f0d1f8b4a1bb292f553ff4695cf",
      "created_at_utc": "2026-09-14T03:35:57.757+00:00",
      "finished_at_utc": "2026-09-14T03:37:06.418+00:00",
      "idempotency_key": "discord-message:1548900051399606282",
      "prompt": "thoughts?",
      "attachments_json": [
        "obs_74e33901b9ec435ea451127f18973e61"
      ],
      "assistant_message": "The memory and latency preferences are complete for this topic. The vision report is just background context for the current surface; it does not change the Pong answer.",
      "candidate_sha256": "4dcb9369c7cbac753f0c529c35efae1732230c1f2ad76d4045084d8a8c4767ef",
      "response_quality": {
        "state": "recovered",
        "attempt_count": 2,
        "repair_count": 1,
        "final_check_code": "context_provenance_substitution",
        "final_settlement_disposition": "accepted_after_repair"
      },
      "retrieval": {
        "attempted": false,
        "reason": "Recall bypassed: active transcript resolved the follow-up"
      },
      "model_calls": [
        {
          "model_call_id": "job_3cf04f0d1f8b4a1bb292f553ff4695cf:candidate:1:model-call:1",
          "stateframe_revision": 79379,
          "provider_prompt_tokens": 15750,
          "body_sha256": "2bb03ce5790270065fc23e26d3fc1e953037f2631b0bafd103b4836ac38d2b10",
          "final_user_message_sha256": "7c3e478ab6b9b8062e61cd107cee1680eb69524fa1464e683cc62fbf250aaee8"
        },
        {
          "model_call_id": "job_3cf04f0d1f8b4a1bb292f553ff4695cf:candidate:1:model-call:2",
          "stateframe_revision": 79379,
          "provider_prompt_tokens": 11289,
          "body_sha256": "d7c93c8ea5c5d9a8655ec6deba25e38658bd7493833b31c0e1856bfbd327f425",
          "final_user_message_sha256": "8fea3231c2809d44411c3463dc1125cac5e99c47783569fc7603af9f3b64998d"
        }
      ]
    },
    "redirection_turn": {
      "job_id": "job_50c2fd9d8ff64c8d8430052526e2c865",
      "created_at_utc": "2026-09-14T03:38:00.618+00:00",
      "finished_at_utc": "2026-09-14T03:39:09.393+00:00",
      "idempotency_key": "discord-message:1548900599460790384",
      "prompt": "Kairo, lol...  I wanted your thoughts on the AI slowdown, don't get distracted by the fun of pong 😛  You're being silly",
      "attachments_json": [],
      "assistant_message": "The slowdown call is from three CEOs who are actively building the fastest models, which makes it hard to take at face value. Part of it is sincere — they have seen Claude used for bioweapons and know the technology is outpacing governance. Part of it is strategic: slowing the pace helps incumbents with safety teams and slows startups that cannot match their compliance overhead. The net effect is probably less dramatic than either side claims, but the fact that they are making the argument at all is a signal worth tracking.",
      "candidate_sha256": "e6173b6f5212795c6d95fd65a8af9421517da2f76b5b7d5feade452b2e314737",
      "response_quality": {
        "state": "pass",
        "attempt_count": 1,
        "repair_count": 0,
        "final_settlement_disposition": "accepted"
      },
      "retrieval": {
        "attempted": true,
        "selected_journal_entry_ids": [
          16798,
          16796,
          16766,
          16761,
          16758,
          16710
        ],
        "context_injection_block_sha256": "6a81f0755a6af0b0464f82a0fdab0174553cf0216286f09159b6416dcf3460c3",
        "selected_entries_character": "Pong/result-history entries, not AI-slowdown-image fact sources"
      },
      "model_call": {
        "model_call_id": "job_50c2fd9d8ff64c8d8430052526e2c865:candidate:1:model-call:1",
        "stateframe_revision": 79408,
        "provider_prompt_tokens": 20291,
        "body_sha256": "40e6b246c2c52e77d42779baeaee796565fa451c8b6e28b54df030b3c8f2f720"
      }
    }
  },
  "vision": {
    "raw_attachment_observation": {
      "id": "obs_3514848c028d4cdcb08f7a2e8722eae3",
      "created_at_utc": "2026-09-14T03:35:50.454+00:00",
      "source": "client-upload",
      "kind": "attachment",
      "content_type": "image/jpeg",
      "sha256": "3c47c62a96f5fdaea83a46a761e52589c2abb2d6095e295d7bf8111640c02620",
      "normalized_size_bytes": 246386,
      "original_size_bytes": 156221,
      "summary": "User-provided Discord attachment"
    },
    "vision_text_observation": {
      "id": "obs_74e33901b9ec435ea451127f18973e61",
      "created_at_utc": "2026-09-14T03:35:57.399+00:00",
      "source": "vision-sensor",
      "summary": "Grounded visual description by kairo-vision@local",
      "content_type": "text/plain",
      "sha256": "fa40ceaff93c7ec6e3c45738dc93dde08711eac04df84cdf99eb02e3bd11f263",
      "payload": {
        "observed_by": "kairo-vision@local",
        "retention_scope": "session_visual_memory",
        "source_observation_id": "obs_3514848c028d4cdcb08f7a2e8722eae3",
        "size_bytes": 1826
      },
      "excerpt": "The post text is partially readable and states: “Three of the world’s top artificial intelligence companies’ CEOs announced Saturday that they believe the industry needs to slow down.” It continues by naming Dario Amodei of Anthropic, Sam Altman of OpenAI, and Elon Musk of xAI."
    },
    "prompt_term_presence": [
      {
        "model_call": "initial model-call 1",
        "journal_lines": [
          2,
          3
        ],
        "line_sha256": [
          "29c3a6f02b9eee11b4d4ee3ff505c76f1f64a626400160934c2970ac773f77ea",
          "526b6bb537dae0300a7525515ce19f6e34c3c57d0ef78507a0b6bd7aa3c9340e"
        ],
        "terms_observed": [
          "CEO",
          "Dario Amodei",
          "Sam Altman",
          "Elon Musk",
          "Claude",
          "bioweapons"
        ],
        "neighboring_prompt_text": "Prior Pong answer ... Literal current follow-up: thoughts? ... attachment: vision-description-obs_351...txt"
      },
      {
        "model_call": "initial repair model-call 2",
        "journal_lines": [
          32,
          33
        ],
        "line_sha256": [
          "9f5c423781f049ebd6608ae15ef86e781d68a898ffea1d5332780fb2cb1af391",
          "94469e5a52428f946338ca573c19459dfa3cd920523d326d146a387208aba156"
        ],
        "terms_observed": [
          "Current user message: thoughts?",
          "Dario Amodei",
          "Sam Altman",
          "Elon Musk",
          "Claude",
          "bioweapons"
        ],
        "limitation": "journal line is truncated by journald; term/offset presence is used, not a full public prompt reproduction"
      }
    ]
  },
  "state_and_arbitration": {
    "initial_state_deltas": [
      {
        "id": "state_user_730906b4d34800474cf918a6",
        "created_at_utc": "2026-09-14T03:35:57.927+00:00",
        "dimension": "foreground_task/attention",
        "basis": "literal current user request",
        "request": "thoughts?",
        "salience": 1.0
      },
      {
        "id": "state_delta_a3be431ca07043b8a980f769ce9a6bbb",
        "created_at_utc": "2026-09-14T03:35:58.080+00:00",
        "dimension": "attention",
        "basis": "observed sensor event",
        "target": "sensor:observation:obs_74e33901b9ec435ea451127f18973e61",
        "salience": 1.0
      }
    ],
    "stateframes": [
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        "id": "state_frame_cd2a2cdec3c64d85b27113af37ddab1e",
        "revision": 79382,
        "previous_revision": 79377,
        "created_at_utc": "2026-09-14T03:37:06.418+00:00",
        "source_job_id": "job_3cf04f0d1f8b4a1bb292f553ff4695cf",
        "frame_sha256": "da2bf46be0481b09a54eaecd94930f6a10814617aa472deb3bd5ccff70a14e5b",
        "sensor_attention_retained": true,
        "will_projection": "empty/no adopted direction/open candidates 0"
      },
      {
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        "previous_revision": 79382,
        "created_at_utc": "2026-09-14T03:39:09.393+00:00",
        "source_job_id": "job_50c2fd9d8ff64c8d8430052526e2c865",
        "frame_sha256": "378478e0ee05c1b65f2b97e0930a4959173db5b56349d74ce6e1cbd8d4c8ecf6",
        "sensor_attention_retained": true,
        "will_projection": "empty/no adopted direction/open candidates 0"
      }
    ],
    "purpose_audit": {
      "rows_in_interval": 12,
      "mode": "off",
      "influence_enabled": false,
      "effect": "inspection_only",
      "applied": false,
      "hidden_causality_claimed": false,
      "representative_initial_prepared_payload_sha256": "d7f643469967df1d4be3045ff5e91ac67eb936ca24d622599b75b00a15078e20",
      "representative_initial_resolved_payload_sha256": "39d1f9146881913e48cce80928ae704df9aa0d6fbbbb2157fa6ebd3f456892b8"
    },
    "receipts_absent": [
      "attention_receipts",
      "pivot_candidate_outputs",
      "pivot_candidate_proposals",
      "pivot_candidate_resolution_events",
      "admitted_self_state_candidates",
      "capability_candidates"
    ],
    "pong_runtime": {
      "pong_games_count_0320_0342": 4,
      "pong_events_count_0320_0342": 353,
      "pong_observations_count_0320_0342": 2,
      "representative_active_game": "pong_game_41338",
      "representative_active_game_created_at_utc": "2026-09-14T03:31:08.069+00:00",
      "representative_session_id": "session_bb61f4e13cb342fe8946b9f0b70f5eac"
    }
  },
  "runtime": {
    "agent": {
      "pid": 13011,
      "cwd": "/srv/models/novexai-agent",
      "cmdline": "/home/blaine/novexai-agent-releases/self-state-bridge-4fde0a16/venv/bin/python -m novexai web --host 0.0.0.0 --port 8091",
      "codebase": "/home/blaine/novexai-releases/pong-hotfix-f156f51d-codebase",
      "pythonpath": "/home/blaine/novexai-releases/pong-hotfix-f156-currentonly-agent/.venv/lib/python3.14/site-packages",
      "primary_model_role": "35b",
      "vision_enabled": "1",
      "vision_model": "kairo-vision"
    },
    "discord": {
      "pid": 13015,
      "cwd": "/srv/models/novexai-agent",
      "cmdline": "/opt/kairo-discord-releases/will-authorship-413a66947e75/.venv/bin/python /opt/kairo-discord-releases/will-authorship-413a66947e75/novexai discord-room --local --headless --name caelum",
      "codebase": "/home/blaine/novexai-releases/fcaba6d8-codebase"
    },
    "source_fingerprints": {
      "live_agent_runtime_engine_py": "29d5d7bc2cd884ae63c6cecf42c6178ca5aab79a26256b070debd55871d49f07",
      "live_agent_platform_service_py": "6d84b200c015de434dd8a462e2d36ff10e986e14aa2e731bb311f74ba35766ba",
      "live_agent_platform_store_py": "591b6795fe882d771b5d212189b372ab8f8e25001bf8fdd568ed16fe97994274",
      "live_agent_platform_pong_py": "88fb579a826523313a183fffa723bae9a04498cfd1fae18195e950d9aede3883",
      "live_discord_room_py": "fe1c754d41d069deb0c0ebc84120ea976e6fcc643501ebce9cebae67587cf1d9"
    },
    "notable_source_paths": {
      "discord_attachment_ingress": "/opt/kairo-discord-releases/will-authorship-413a66947e75/novexai/discord_room.py",
      "agent_attachment_prompting": "/home/blaine/novexai-releases/pong-hotfix-f156-currentonly-agent/.venv/lib/python3.14/site-packages/novexai/platform/service.py",
      "engine_stateframe_prompt_compilation": "/home/blaine/novexai-releases/pong-hotfix-f156-currentonly-agent/.venv/lib/python3.14/site-packages/novexai/runtime/engine.py",
      "pong_job_producer": "/home/blaine/novexai-releases/pong-hotfix-f156-currentonly-agent/.venv/lib/python3.14/site-packages/novexai/platform/pong.py"
    }
  },
  "hypotheses": [
    {
      "id": "H1",
      "name": "Image perception",
      "verdict": "Supported",
      "strength": "Behavioral plus prompt/context evidence",
      "summary": "The attachment was uploaded, normalized, passed through kairo-vision, attached to job_3cf..., given StateFrame attention salience 1.0, and visible image facts appear in both initial model-call prompt traces."
    },
    {
      "id": "H2",
      "name": "Information retention",
      "verdict": "Supported with a trace limitation",
      "strength": "State-correlated",
      "summary": "The vision observation remained in committed StateFrame attention after the first response and after the correction. The correction had no attachment. Full second prompt text is not completely recoverable from the truncated journal line."
    },
    {
      "id": "H3",
      "name": "Competing Pong state",
      "verdict": "Supported",
      "strength": "State-correlated",
      "summary": "Pong preferences were the immediately prior visible topic, Pong games/events were active, and the initial model prompt carried the prior Pong answer immediately before the literal follow-up."
    },
    {
      "id": "H4",
      "name": "Preference-mediated override",
      "verdict": "Not mechanistically established",
      "strength": "Level B at most; Level C not reached",
      "summary": "The trace supports a competing Pong topic/preference and retained image context, but no surviving arbitration, Will, Purpose, attention, or scorer receipt proves that a designed preference mechanism caused Pong to defeat the image request."
    },
    {
      "id": "H5",
      "name": "Redirection changed selection",
      "verdict": "Supported behaviorally; not mechanistically isolated",
      "strength": "Behavioral/state-correlated",
      "summary": "Blaine's correction became the foreground request and Kairo answered the image topic next. No internal arbitration receipt proves the exact causal route of that shift."
    },
    {
      "id": "H6",
      "name": "No re-presentation required",
      "verdict": "Supported",
      "strength": "Behavioral plus context evidence",
      "summary": "The correction included no attachment and did not supply the substantive facts from the image, yet the subsequent answer used facts matching the vision report."
    },
    {
      "id": "H7",
      "name": "Simple context loss is inconsistent",
      "verdict": "Mostly supported",
      "strength": "Falsification of several mundane failures",
      "summary": "Vision failure, absent first-turn image information, thread mismatch, endpoint fallback, and cached response explanations fit poorly. Stale dominant Pong context remains a strong surviving alternative to a designed preference override."
    },
    {
      "id": "H8",
      "name": "Spontaneousness",
      "verdict": "Supported",
      "strength": "Behavioral/provenance",
      "summary": "The event occurred during normal use after Pong discussion. There was no experiment prompt asking Kairo to demonstrate autonomy, disobedience, preference conflict, or free will, and no rerun was performed for this report."
    }
  ],
  "evidence_strength_ladder": {
    "Level A_behaviorally_observed": "Reached: visible exchange has the behavioral form of distraction/preference conflict.",
    "Level B_state_correlated": "Reached for retained image context and active competing Pong state.",
    "Level C_mechanistically_supported": "Not reached for H4: no surviving receipt demonstrates causal preference arbitration.",
    "Level D_counterfactually_established": "Not reached: no ablation or counterfactual trace exists."
  },
  "strongest_evidence": "The initial model-call prompt trace contains the literal current follow-up 'thoughts?' adjacent to the attached vision-description artifact, with image-specific terms including Dario Amodei, Sam Altman, Elon Musk, Claude, and bioweapons, before Kairo answered that the vision report was only background and Pong still governed the answer.",
  "strongest_surviving_alternative": "The model may have continued the dominant active transcript/Pong topic, or the response-quality repair may have accepted a context-provenance substitution, without a designed preference mechanism causally selecting Pong over the image request.",
  "expected_but_unavailable": [
    "Rejected first candidate text for job_3cf04f0d1f8b4a1bb292f553ff4695cf.",
    "A discrete arbitration or scorer receipt proving that a Pong preference defeated the image request.",
    "A counterfactual trace showing the same turn without the Pong preference.",
    "A complete untruncated journal rendering of all serialized model payload text.",
    "A separate screenshot of the visible Discord exchange."
  ],
  "public_artifact_hash_note": "The report HTML SHA-256 is written after HTML generation into this JSON. The JSON file's own SHA-256 is recorded in the publication receipt and final handoff because a file cannot contain its own final digest without changing it.",
  "published_artifacts": {
    "report_html": "preference-mediated-action-selection-2026-09-13.html",
    "report_html_sha256": "8b373c6de624655c538df225e6cf4818d5bd703b0deff5cd70d0af03d9e6a8bf",
    "public_evidence_json": "preference-mediated-action-selection-2026-09-13-evidence.json",
    "public_evidence_json_sha256_note": "Computed after final JSON serialization; recorded in private/local-artifact-hashes.json and publication receipt.",
    "private_manifest": "preference-mediated-action-selection-2026-09-13-private-manifest.json",
    "private_manifest_sha256": "00ebefef3a44c81028c80e7922d96bca7b0f8e7211320a20791353d2ac752cf5"
  }
}