Meta-Insight

The framework reads MI-31 demand chain stress test as the diagnostic discipline applied to companies whose revenue depends on specific customer concentration or industry positioning that could face structural stress under specific scenarios. The pattern is closely related to but distinct from customer concentration risk (V.03) — MI-31 specifically addresses circular capital exposure where customers' revenue depends on the same broader demand cycle that supports the company's revenue. AI infrastructure stack exposures with multi-tier circular capital relationships demonstrate the pattern at concerning magnitude per recent extraction work.

The framework reads circular capital as the structural condition where revenue flows return through the supply chain to support continued spending by upstream entities. AI infrastructure stack relationships demonstrate elements of this — chip companies sell to hyperscaler customers whose AI services revenue funds further chip purchases, with model providers funded through similar dynamics. The pattern is concerning when the circular relationships represent material percentages of revenue at multiple tiers without independent demand support. The framework's recent extraction work identified AI infrastructure stack as the worst MI-31 score domain with 3+ tier circular capital relationships.

The framework applies MI-31 demand chain stress test on every extraction as a paired evaluation gate alongside other meta-insight diagnostics. The discipline distinguishes companies whose revenue base reflects independent demand from companies whose revenue depends on circular capital relationships that could face structural stress under specific scenarios. The pattern fires bearish when circular relationships represent material revenue percentages at multiple tiers, the relationships lack independent demand support, and the broader cycle dynamics could compress demand across the circular chain concurrently.

The framework's recent Run #6 v2 work identified AI infrastructure stack as the worst MI-31 score domain across the v1.5 framework. The finding reflects 3+ tier circular capital relationships where chip company revenue depends on hyperscaler customers whose revenue depends on AI service demand that depends on AI infrastructure investment. The circular nature concentrates risk if any tier of the chain faces compression. The framework's discipline applies MI-31 reads on AI infrastructure exposures alongside individual operational composite reads to surface composite firing risk.

The framework's diagnostic conditions track circular capital exposure through customer concentration analysis combined with customer revenue source analysis. Companies serving customers with diversified revenue sources face limited circular capital exposure. Companies serving customers whose revenue depends on the same broader cycle face circular capital exposure at varying magnitudes. The framework reads each exposure through specific diagnostic conditions identifying which face circular capital risk versus which face independent demand support. Free registration shows per-ticker reads on companies firing MI-31 patterns at moderate or strong magnitude.