Generated: 2026-03-26 | Iteration: 3 | Quality Score: 3.50/5.0
15 items identified. 3 remediated. 3 resolved. 9 open.
| # | Flag Source | Flag Type | Severity | Status | Technique(s) | Evidence Focus |
|---|---|---|---|---|---|---|
| 1 | Layer 2 - 3a | Unstated premise impacting key judgment (revenue-as-proxy) | HIGH | REMEDIATED | kac |
Revenue-as-proxy limitation: retention, player welfare, cultural impact metrics |
| 2 | Layer 2 - 3b | Evidence imbalance >2:1 | MEDIUM | OPEN | ach |
Seek consumer welfare, regulatory, and indie developer sources |
| 3 | Layer 2 - 3d | Strong counter-argument (structural fragility) | HIGH | REMEDIATED | what-if, premortem |
Structural fragility: whale demographics, developer sustainability, design quality |
| 4 | Layer 2 - 3e | Missing perspectives (player/consumer) | MEDIUM | OPEN | narratives |
Consumer satisfaction surveys, spending regret data, engagement quality metrics |
| 5 | Layer 2 - 3e | Missing perspectives (regulatory) | MEDIUM | OPEN | narratives |
Government regulators on loot box legislation, gambling classification |
| 6 | Layer 2 - 3e | Missing perspectives (advertising/UA ecosystem) | HIGH | REMEDIATED | what-if, premortem |
UA cost trends, ATT/IDFA impact, privacy regulation effects |
| 7 | Layer 2 - 3g | Analytical bias -- anchoring | MEDIUM | OPEN | devils-advocacy |
Evidence countering growth-presuming framing; net negative effects by non-revenue metrics |
| 8 | Layer 2 - 3g | Analytical bias -- authority bias on academic studies | MEDIUM | OPEN | devils-advocacy |
Post-2023 academic research on mobile-console/PC relationships under contraction |
| 9 | Layer 2 - 3a | Revenue-as-proxy not operationalized post-diagnosis | HIGH | RESOLVED -- Iter 3 | ach, kac |
Re-run ACH with non-revenue evidence; construct parallel engagement-based assessment |
| 10 | Layer 2 - 3a | Compound ATT + DMA + whale erosion interaction not modeled | HIGH | RESOLVED -- Iter 3 | what-if, premortem |
Model as integrated reinforcing system; assess compound probability |
| 11 | Layer 2 - 3d | Counter-argument strengthened -- structural fragility thesis needs direct testing | HIGH | RESOLVED -- Iter 3 | what-if, premortem |
Developer ecosystem survival rates; whale demographic lifecycle modeling; design quality trends |
| 12 | Layer 2 - 3a | Engagement metrics may have compositional bias | HIGH | OPEN | kac, ach |
Test whether surviving games show improved retention; distinguish mix effects from genuine erosion |
| 13 | Layer 2 - 3a | Compound system dampening forces underweighted | HIGH | OPEN | what-if |
Model AI-assisted UA recovery, DMA fee reductions, web store adoption as dampening forces |
| 14 | Layer 2 - 3g | Confirmation bias in v3 evidence collection | HIGH | OPEN | (evidence collection only) | Search for mobile gaming innovation, successful launches, adaptation strategies in 2025-2026 |
| 15 | Layer 2 - 3e | Missing perspectives -- emerging market developers | MEDIUM | OPEN | narratives |
Developer economics in India, MENA, LATAM, Southeast Asia |
All six techniques used revenue as the primary metric for assessing mobile gaming's market impact, despite the Key Assumptions Check identifying revenue-as-proxy as a linchpin assumption with significant limitations.
- Technique:
kac - Evidence focus: Collect engagement metrics, player welfare studies, cultural impact assessments.
- Remediation note: Auto-remediated in cycle 2. Prior artifact archived at working/assumptions.v1.md. KAC v2 downgraded Linchpin 5 to Unsupported. Diagnosis operationalized in Iter 3 -- see item #9.
Evidence ratio shifted from ~2:1 favoring expansion (v1) to ~1:1.3 favoring structural concerns (v3). All 18 new items across v2+v3 challenged the conventional line. Imbalance has reversed direction but the asymmetry in new evidence collection suggests confirmation bias rather than genuine rebalancing.
- Technique:
ach - Evidence focus: Seek adaptation evidence, successful innovation cases, recovery indicators for mobile gaming.
The structural fragility counter-argument needed direct evidence testing.
- Technique:
what-if,premortem - Evidence focus: Whale demographic data, developer survival rates, design quality metrics.
- Remediation note: Auto-remediated in cycle 2. Further addressed in Iter 3 (item #11). Counter-argument upgraded to viable alternative thesis.
No independent consumer satisfaction surveys or engagement quality metrics collected. Peer-reviewed player welfare studies [E46, E47] partially address this gap but focus on harms rather than overall satisfaction.
- Technique:
narratives - Evidence focus: Independent consumer surveys on mobile gaming satisfaction, longitudinal spending behavior studies.
No evidence from government regulators on loot box legislation or enforcement intent. Peer-reviewed evidence [E46, E47] provides academic basis but regulatory timeline unknown.
- Technique:
narratives - Evidence focus: EU legislative proposals, UK/Australian gambling authority position papers.
No data on UA cost trends, ATT impact, or privacy regulation effects on the F2P funnel.
- Technique:
what-if,premortem - Evidence focus: CPI trends, ATT impact data, DMA distribution effects.
- Remediation note: Auto-remediated in cycle 2. Evidence collected: CPI data [E50, E52], ATT opt-in [E55], ATT CPI impact [E51], ATT research [E54], DMA [E53]. Iter 3 added ATT compound analysis [E58]. Remaining: ad network adaptation strategies.
Monotonically decreasing confidence trajectory (Moderate to Moderate-Low to Low) across three iterations warrants scrutiny as potential overcorrection rather than genuine analytical discovery.
- Technique:
devils-advocacy - Evidence focus: Evidence of net positive effects by non-revenue metrics; test whether overcorrection is occurring.
Academic studies E36 and E37 retain disproportionate weight. Both pre-date the 2023-2025 stagnation period and have not been tested under contraction conditions.
- Technique:
devils-advocacy - Evidence focus: Post-2023 academic research on mobile-console/PC relationships; industry analyses testing complementarity under contraction.
KAC v2 diagnosed revenue as Unsupported but all techniques still built on revenue-denominated evidence.
- Technique:
ach,kac - Evidence focus: Re-run ACH with non-revenue evidence; construct parallel engagement-based assessment.
- Resolved: Iteration 3 (2026-03-26). 7 new evidence items (E56-E62). KAC v3 constructed parallel non-revenue assessment across four lenses (engagement, market position, ecosystem, revenue). ACH v3 re-run with dual matrices showing H1 inversion under equal weighting. Revenue-as-proxy diagnosis now fully operationalized.
10. [RESOLVED -- Iter 3] Compound ATT + DMA + whale erosion interaction not modeled (Layer 2 - 3a) -- HIGH
Premortem v2 identified ATT, DMA, and whale erosion as causally linked but all techniques analyzed them as independent risk factors.
- Technique:
what-if,premortem - Evidence focus: Model compound scenario with reinforcing feedback loops; assess compound probability.
- Resolved: Iteration 3 (2026-03-26). 7 new evidence items (E56-E62). What-If v3 modeled the compound system as a single reinforcing loop with system architecture diagram. Found 3 of 4 elements already active. Compound system is current state, not future risk.
11. [RESOLVED -- Iter 3] Counter-argument strengthened -- structural fragility thesis needs direct testing (Layer 2 - 3d) -- HIGH
Structural fragility counter-argument needed upgrading from "counter-argument" to "viable alternative thesis."
- Technique:
what-if,premortem - Evidence focus: Developer ecosystem survival rates; whale demographic lifecycle modeling; design quality trends.
- Resolved: Iteration 3 (2026-03-26). 7 new evidence items (E56-E62). Premortem v3 upgraded structural fragility to viable alternative thesis with two branches: collapse vs creative destruction. Both interpretations presented as primary forward-looking uncertainty in report.
Declining aggregate retention [E56] may partly reflect market cleaning (low-quality games exiting inflate the denominator) rather than genuine engagement erosion. KAC v3 and ACH v3 accepted decline at face value.
- Technique:
kac,ach - Evidence focus: Test whether surviving games show improved retention; obtain retention data segmented by game tier or longevity; distinguish mix effects from genuine erosion.
What-If v3 modeled the compound system as self-reinforcing without sufficient dampening analysis. Three dampening forces need explicit modeling: AI-assisted UA (restoring targeting), DMA fee reductions (improving margins), web stores (reducing platform dependency).
- Technique:
what-if - Evidence focus: AI-assisted contextual targeting effectiveness data; DMA marketplace adoption rates and developer margin impact; web store transaction volume and developer economics.
All 7 new evidence items [E56-E62] confirmed structural fragility. Search queries were targeted at structural problems. No systematic search for adaptation, innovation, or recovery evidence.
- Technique: (evidence collection only)
- Evidence focus: Mobile gaming innovation 2025-2026; successful new mobile game launches; developer adaptation strategies; AI-assisted game development; web store success cases.
No evidence on developer economics in India, Southeast Asia, MENA, or LATAM. The structural contraction may be geographically bounded. The mobile gaming ecosystem may be relocating rather than contracting.
- Technique:
narratives - Evidence focus: Developer economics in growth regions; emerging market studio formation rates; localization and market entry strategies.
/analyze --iterate 2026-03-26-mobile-gaming-marketplace-growth-impact kac ach what-if devils-advocacy narratives