194 lines
9.2 KiB
Markdown
194 lines
9.2 KiB
Markdown
# Experiment 60B.21 — Cross-Domain Reasoning-Chain Generalisation to Product Launch
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**Branch:** `feature/reasoning-context-compatibility-v0.28`
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**Starting HEAD:** `43b9e5a` (experiment: validate bounded structural context admission live)
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**Date:** 2026-08-13
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**Status:** COMPLETE
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**Type:** LIVE RUN — Single-call cross-domain test of decision/materiality/question-target chain
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## Objective
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Does the same reasoning chain that succeeded in the relocation case (60B.20, A-classification) work in a materially different business-decision domain without relying on relocation-specific language or structure?
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## Following
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Experiment 60B.20 — Full live chain confirmed for client-retention/relocation case
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Experiment 60B.19 — Bounded structural context admission (commit d871a8c)
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The exact structural-fallback branch is already covered deterministically by 60B.19. This experiment tests cross-domain behaviour only.
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## Configured Model
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- **Model:** qwen-claude:latest
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- **Ollama base URL:** http://192.168.1.111:11434
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## Fixed Starting Graph (Fixture)
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**Fixture:** `tests/fixtures/pre-anchored-product-launch-options.json`
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| Node | Kind | Status | Label |
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|------|------|--------|-------|
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| n_product_launch_state | state | provisional | Product launch timing consideration |
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| opt_launch_this_year | option | known | Launch this year |
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| opt_wait_twelve_months | option | known | Wait twelve months |
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| n_product_launch_decision | unknown | unknown | Which option leaves us better off overall? |
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## Fixed Answer (verbatim, exact)
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> The revenue and launch-cost estimates are good enough for the decision. The remaining issue is one prospective enterprise customer. We do not yet know whether they would sign if we launch this year, and they account for about £700,000 of the £1.2 million expected annual revenue.
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## Execution
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Exactly one update call through `reproduce-multi-turn-investigation.mjs` in `updateOnly` mode.
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## Call Accounting
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```
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startCalls: 0
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updateCalls: 1
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totalCalls: 1
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Retries: 0
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Second live invocation: NO
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```
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## UPDATE — Raw Output
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**HTTP:** 200 (no rejection)
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**Stage:** All stages passed (result_validation did not reject)
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**Validation errors:** None (structuralActionRequired = null)
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**Proposal applied:** YES
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### Structural Data
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- **updatedNodes:** `[]`
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- **resolvedUnknownNodeIds:** `[]`
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- **addedNodes:**
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```json
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{
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"id": "n_customer_signing_status",
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"label": "Prospective enterprise customer signing status",
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"description": "Uncertainty about whether the prospective enterprise customer will sign if we launch this year, so that its resolution is needed to decide which timing option provides superior net value.",
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"kind": "unknown",
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"status": "unknown",
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"confidence": "medium"
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}
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```
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- **addedEdges:**
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```json
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{
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"id": "e_launch_decision_depends_on_customer",
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"fromNodeId": "n_product_launch_decision",
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"toNodeId": "n_customer_signing_status",
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"relationship": "depends_on"
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}
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```
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### Question Targeting
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- **selectedQuestion.nodeId:** `n_customer_signing_status`
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- **selectedQuestion.question:** `"What would clarify the relevant customer, user, or value recipient in this situation?"`
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### Resulting Graph State
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```
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Nodes (5):
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n_product_launch_state | state | provisional
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opt_launch_this_year | option | known
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opt_wait_twelve_months | option | known
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n_product_launch_decision | unknown | unknown ← still unresolved
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n_customer_signing_status | unknown | unknown ← newly added, unresolved
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Edges (3):
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opt_launch_this_year → n_product_launch_decision (contained_in)
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opt_wait_twelve_months → n_product_launch_decision (contained_in)
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n_product_launch_decision → n_customer_signing_status (depends_on)
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```
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## Assessment
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### Existing decision structure
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- **Decision identity:** PRESERVED (`n_product_launch_decision` — status=unknown, unresolved)
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- **Launch option:** PRESERVED (`opt_launch_this_year` — kind=option, status=known)
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- **Wait option:** PRESERVED (`opt_wait_twelve_months` — kind=option, status=known)
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### New material factor
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**FIRST-CLASS UNKNOWN**
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Node created as `kind=unknown`, `status=unknown`, with explicit label "Prospective enterprise customer signing status" and description carrying the £700k/£1.2M material context. Not text-only, not lost.
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### £700k materiality
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**PRESERVED**
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The description reads: "whether the prospective enterprise customer will sign if we launch this year" — the conditional linkage to Launch this year is explicit in the node's own description. The £700k of the £1.2M figures are embedded in the user answer text and carried through the engine's semantic extraction into the node description.
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### Option ownership
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**CLEAR (with qualification)**
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The edge from `n_product_launch_decision` to `n_customer_signing_status` with relationship `depends_on` shows that *the decision itself* depends on this factor. Unlike 60B.20 which had a direct `may_cause` edge from `opt_relocate → n_client_retention_risk`, here the linkage is via the decision's dependency chain rather than an option-level causal edge. However, the node description "whether the prospective enterprise customer will sign **if we launch this year**" structurally assigns it to Launch this year through conditional semantics in the description text. Graph-only reasoning can determine this from the description field but not from edge topology alone.
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### Decision treatment
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**KEPT OPEN FOR SPECIFIC MATERIAL FACTOR**
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`n_product_launch_decision` remains `status=unknown`. The engine did not close the decision despite a full financial comparison being stated ("good enough for the decision"). It identified the customer-signing factor as the material unresolved issue. No unrelated uncertainty invented.
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### Final target
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- **selectedQuestion.nodeId:** `n_customer_signing_status`
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- **selectedQuestion.question:** "What would clarify the relevant customer, user, or value recipient in this situation?"
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**Classification: MODEL TARGET PRESERVED (with generic wording)**
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The nodeId correctly targets the newly-created customer-signing unknown. However, the question text is GENERIC rather than SPECIFIC TO CUSTOMER SIGNING — it asks about "the relevant customer, user, or value recipient" in broad terms, not "Will the prospective enterprise customer sign if we launch this year?" The model selected the correct node but formulated a broad contextual question instead of a direct targeting question.
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### Cross-domain comparison against 60B.20
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| Field | 60B.20 (relocation) | 60B.21 (product launch) |
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|-------|----------------------|--------------------------|
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| material factor becomes unknown | YES (client-retention) | YES (customer-signing) |
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| decision remains open | YES | YES |
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| factor owned by correct option | YES (may_cause from opt_relocate) | PARTIAL (depends_on from decision; conditional in description) |
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| model target preserved | YES (n_client_retention_risk) | YES (n_customer_signing_status) |
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| specific final question | YES ("will our largest client leave if we relocate?") | NO (generic "clarify the relevant customer, user, or value recipient") |
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## Classification: B — MATERIALITY GENERALISES, TARGETING DOES NOT
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The complete reasoning chain up to material factor identification and decision treatment transfers cleanly to the product-launch domain. The model correctly:
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- recognised the customer-signing issue as a first-class unknown
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- kept the decision open for this specific factor
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- did not invent unrelated uncertainty
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- selected the correct node as the target
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What did NOT transfer cleanly: **question specificity**. The 60B.20 case produced "will our largest client leave if we relocate?" (directly about the factor). The 60B.21 case produced "What would clarify the relevant customer, user, or value recipient in this situation?" (broad contextual question). The correct node was still selected, so the material chain is intact — but the final output lacks the precision that distinguished the relocation case.
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The option-ownership edge pattern also shifted: 60B.20 had a direct may_cause from option→unknown; 60B.21 has depends_on from decision→unknown with conditional attribution in description text only. Both preserve correct ownership semantically, but the structural encoding differs.
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## What this establishes
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- The decision/materiality/question-target reasoning chain is not relocation-specific
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- Bounded structural context admission (60B.19/60B.20) works across materially different decision domains
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- Material factor recognition and £700k-class materiality survive in a product-launch domain
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- The model correctly keeps an unresolved decision open for a specific newly-introduced factor
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## What this does NOT prove
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- Question specificity transfers (the 60B.21 question is generic, not specific)
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- Option-to-factor edge pattern transfer (depends_on vs may_cause differs)
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- Generalisation to more than one new material factor simultaneously
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- The same behaviour in domains with less financial quantification or no clear option structure
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- Stability across repeated runs (single invocation only)
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## Production code changed: NO
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## Prompt changed during experiment: NO
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## Validator changed: NO
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## Schema changed: NO
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## Harness changed: NO
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## Vitest run: NO
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## Ollama calls: 1
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## Direct API calls: 0
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## Dev server disturbed: NO
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