Preserve open-world training ambitions

docs/architecture/sequential-agent-runtime.md

@@ -4,10 +4,14 @@ Ghostlight's near-term target is not a general-purpose life simulator.
 
 The near-term product target is procedural interactive dialogue: set up a scene,
 let characters choose believable responses, expose player-facing choices, and
-propagate consequences into state, memory, and social perception. Later, the
-same machinery can help generate longer storylines, but that is not license to
-build an everything-simulator right now. The little goblin will ask for a crown.
-Do not give it one.
+propagate consequences into state, memory, and social perception.
+
+The long-term target is broader. The same classifiers, appraisers, and
+projection models should eventually operate inside a simulated game world with
+open-world contexts, iterated decisions, economic behavior, and major-faction
+decision-making. Do not train a tiny dialogue-only creature that panics the
+first time someone buys medicine, defects from a faction, or reacts to a
+shortage. Also do not build the whole economy today. Both cliffs are stupid.
 
 The runtime target for now is scene-local: choose which character is acting,
 give that character local awareness, let them act, apply consequences, mutate
@@ -42,7 +46,10 @@ For game use, the loop should be able to emit:
 - unresolved hooks for later scenes
 
 If a feature does not help produce those artifacts, it belongs in the parking
-lot until the smaller machine works.
+lot until the smaller machine works. If a field or label preserves information
+needed for later open-world behavior, consumer choice, faction pressure, or
+iterated decisions, keep it visible in the training artifact even if the first
+prototype does not simulate it.
 
 ## Local Awareness
 
@@ -195,7 +202,8 @@ already learned human interpretation from twelve examples and a strong coffee.
 
 ## Scope Boundary
 
-Build only what interactive dialogue generation needs first.
+Build interactive dialogue generation first, but shape the data for later
+open-world use.
 
 In scope now:
 
@@ -206,18 +214,35 @@ In scope now:
 - manual reviewed appraisals
 - memory, belief, relationship, and activation deltas
 - branch consequences that can be carried into later scenes
+- action intent and listener interpretation labels
+- resource, price, scarcity, obligation, reputation, and faction-pressure tags
+  when they affect the decision
+- reviewed examples of consumer-like choices and institution/faction pressure,
+  even when the prototype only records them as scene state
 
-Out of scope for now:
+Training-data obligations now:
+
+- Preserve why an agent chose, bought, refused, hoarded, traded, complied,
+  defected, concealed, punished, or helped.
+- Preserve what the agent believed the cost, risk, status effect, and social
+  consequence would be.
+- Preserve faction and institution pressures as perceived by the agent, not
+  only as objective setting lore.
+- Preserve iterated-decision context: promises, debts, prior betrayals,
+  reputation, memory, scarcity, and expected future contact.
+
+Out of implementation scope for now:
 
 - full autonomous world simulation
-- economy simulation
+- economy simulation loops
 - city-scale scheduling
 - long-horizon plot invention without author scaffolding
-- autonomous factions moving offscreen
+- autonomous factions moving offscreen as full actors
 - physical simulation beyond scene affordances
 - automatic social appraisal rules pretending to be trained classifiers
 
-The eventual storyline generator should grow out of reliable scene machinery,
+The eventual storyline generator, economic behavior model, and faction decision
+model should grow out of reliable scene machinery and reviewed decision data,
 not the other way around.
 
 ## Projection's Narrower Job

notes/fresh-workspace-handoff.md

@@ -141,8 +141,13 @@ Remaining projection path:
   awareness, produce branchable dialogue or action, and mutate only the state it
   has authority to affect
 - keep the near-term product target to interactive dialogue trees and
-  scene-local consequences; defer world-scale simulation and autonomous
-  long-horizon plot machinery
+  scene-local consequences
+- preserve training-data hooks for future open-world behavior, iterated
+  decisions, psychologically grounded consumer choices, scarcity/reputation
+  pressure, and major faction or institution decision-making
+- defer implementing world-scale simulation loops, autonomous offscreen
+  factions, economy loops, and long-horizon plot machinery until the scene-local
+  machine works
 - use a frontier teacher model to generate/audit projection artifacts
 - train a smaller student projector only after the artifact schema, input
   slicer, and evaluator stabilize

notes/ghostlight-current-system-map.md

@@ -48,7 +48,8 @@ state and re-entry discipline.
 - `docs/architecture/sequential-agent-runtime.md`
   - scene-local dialogue/runtime loop where agents act from local awareness,
     generated actions become event proposals, and bounded state mutation drives
-    branchable dialogue consequences
+    branchable dialogue consequences while preserving training hooks for later
+    open-world, economic, and faction decision models
 - `docs/experiments/cold-wake-story-lab.md`
   - four-scene Cold Wake writing experiment using Ghostlight projection as a
     story-generation crutch and training-data source

notes/ghostlight-implementation-plan.md

@@ -41,6 +41,9 @@
    - Keep the product target narrow: procedural interactive dialogue trees for
      games first, then scene-local character action with consequence
      propagation, then longer procedural storyline generation later.
+   - Do not make the training data dialogue-only. Preserve labels and state
+     hooks for open-world contexts, iterated decisions, consumer behavior,
+     scarcity, reputation, faction pressure, and institution decision-making.
    - Build local awareness from scene state, agent state, relationships,
      memories, resources, affordances, and known constraints.
    - Keep action primitives concrete: speech, silence, movement, gesture,
@@ -62,9 +65,13 @@
    - Emit game-useful artifacts: scene transcript, candidate player choices,
      NPC response branches, state/memory/social-perception deltas, and
      unresolved hooks.
-   - Keep out of scope for now: world-scale simulation, economy, city-scale
-     scheduling, autonomous offscreen factions, and long-horizon plot invention
-     without author scaffolding.
+   - Keep out of implementation scope for now: world-scale simulation loops,
+     economy simulation loops, city-scale scheduling, autonomous offscreen
+     factions as full actors, and long-horizon plot invention without author
+     scaffolding.
+   - Still record why agents buy, refuse, trade, hoard, comply, defect, conceal,
+     punish, or help when those decisions appear in scenes; those reviewed
+     decisions are seed data for later consumer-behavior and faction models.
    - First prototype: rerun one Cold Wake story-lab beat through a deterministic
      local-awareness/projection-control renderer, then apply one conservative
      state mutation and validate the resulting fixture.

state/evidence.jsonl

@@ -31,3 +31,4 @@
 {"ts": "2026-05-01T21:59:49+00:00", "type": "design", "status": "accepted", "note": "Reframed Ghostlight target from specific dialogue projection toward sequential character agents: each acting agent gets local awareness, options, objectives, and mutation authority; generated action becomes an event proposal resolved into bounded state changes. Single-turn projection remains a debug/training seam, not the procedural-generation endpoint."}
 {"ts": "2026-05-01T22:18:59+00:00", "type": "design", "status": "accepted", "note": "Sequential runtime prototype should keep fuzzy interpretation manual at first. Action tools should be concrete primitives; ask/refuse/offer/reveal/conceal/request are intended communicative functions on actions, while listener appraisal may misread them. Manual appraisal and mutation review becomes training data for future classifiers."}
 {"ts": "2026-05-01T22:31:04+00:00", "type": "design", "status": "accepted", "note": "Tightened Ghostlight runtime scope: near-term goal is procedural interactive dialogue trees and scene-local consequence propagation into state, memory, and social perception. Sequential agent machinery should serve branchable game dialogue first; world-scale simulation, autonomous offscreen factions, economy, and long-horizon plot generation stay deferred."}
+{"ts": "2026-05-01T22:36:38+00:00", "type": "design", "status": "accepted", "note": "Adjusted scope boundary: implement scene-local interactive dialogue first, but shape training data for later open-world agents, iterated decisions, psychologically grounded consumer behavior, scarcity/reputation pressure, and major faction or institution decision-making. Defer full simulation loops, not the labels and state hooks those future models will need."}

state/map.yaml

@@ -12,7 +12,8 @@ objective:
     Turn Ghostlight into a legible machine for persistent socially aware
     characters that can generate interactive dialogue trees for games, propagate
     scene consequences into state and memory, and eventually support procedural
-    storyline generation without collapsing into prompt soup.
+    storyline generation, psychologically grounded consumer behavior, and major
+    faction decision-making without collapsing into prompt soup.
   current: >
     Move from hand-authored single-turn projection artifacts toward the first
     scene-local sequential dialogue tick: local awareness, action or dialogue
@@ -103,7 +104,8 @@ accepted_design:
   - Generated action should become an event proposal resolved by mutation authority, not direct unrestricted edits to world or other-agent private state.
   - Sequential runtime action primitives should stay concrete; ask, refuse, offer, reveal, conceal, and request are communicative intentions carried by actions, while listener interpretation remains separate and may be wrong.
   - Early fuzzy social updates should be manual reviewed training data, not brittle rule-based appraisals pretending to understand relationships before the corpus exists.
-  - Scope boundary: generate interactive dialogue trees and scene-local consequences first; defer world-scale simulation, autonomous offscreen factions, economy, and long-horizon plot invention until the smaller machine works.
+  - Scope boundary: implement interactive dialogue trees and scene-local consequences first, but preserve training data hooks for open-world contexts, iterated decisions, economic behavior, scarcity, reputation, faction pressure, and institution decision-making.
+  - Do not train dialogue-only models that will be useless for later game-world simulation; reviewed scene data should preserve why agents buy, refuse, trade, hoard, comply, defect, conceal, punish, or help when those decisions appear.
 
 current_status:
   summary: Ghostlight now has the Epiphany-style persistence spine, the first architecture payload, the v0 canonical agent-state schema seam, prompt projection docs, immediate schema fixes from evaluation, first reviewed Cat/Oz projection examples, a revised Aetheria lore-grounding architecture, a lore grounding digest schema, the first draft Cold Wake historical grounding digest, a Cold Wake story-lab fixture, projection controls, validated Qwen capture receipts, and a complete Cold Wake short story assembled from accepted projection outputs.