# Market Thesis Research Bundle

Question: Given the push toward grid-flexible compute, will a major U.S. grid operator or capacity-market rule AI data-center load as dispatchable demand response or otherwise award it flexibility value rather than treating it as fixed peak demand?

What this bundle is: a reasoning and monitoring scaffold. It organizes public evidence into observations, claims, uncertainty branches, thresholds, and a watch plan.

What this bundle is not: primary evidence, live market data, trade advice, or a substitute for official, live, or current web sources.

Core tension: The assessment turns on unresolved evidence and live-source refresh.

Current inference to verify: {'verdict': 'partial_yes', 'summary': 'Major U.S. grid operators already have rule structures that can pay flexible load for curtailment and include demand resources in capacity constructs, but there is no universal AI-data-center-specific reclassification as of the cutoff. The direction of travel is toward conditional flexibility value, not automatic fixed-peak treatment and not automatic dispatchable status for every data center.', 'confidence': 0.84, 'reasoning': ['PJM already compensates voluntary demand response and places demand resources inside its capacity market structure.', 'CAISO is actively proposing metering and framework changes that would better capture behind-the-meter demand response capabilities.', 'The primary evidence is program and stakeholder-rule evidence, not final AI-specific tariff language.']} Treat this as a hypothesis that must be refreshed against live official sources, not as a signal.

How to use: read `source_priority.json` first, refresh sources in `live_verification_plan.json`, then use `fact_inference_split.json`, `thresholds.json`, and `watch_schedule.json` to decide what changed. Do not infer buy/sell/hold, position sizing, execution, or asset-price direction from this artifact.