# Market Thesis Research Bundle

Question: Given the AI buildout, will utilities, EPC firms, or grid-equipment suppliers cite skilled labor shortages as a binding constraint on project delivery or commissioning by year-end 2026?

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: Given the AI buildout, will utilities, EPC firms, or grid-equipment suppliers cite skilled labor shortages as a binding constraint on project delivery or commissioning by year-end 2026?

Current inference to verify: {'status': 'current_inference_to_verify', 'answer': 'likely_yes', 'estimated_probability': 0.84, 'time_horizon': 'through year-end 2026', 'frame': 'This is a current inference from primary-source filings and commentary, not a prediction signal.', 'basis_summary': ['EPC firms are already explicitly describing qualified labor scarcity as a constraint on project execution.', 'Grid-equipment suppliers are already linking labor scarcity to field installation, commissioning, and infrastructure timing.', 'Utilities are somewhat less explicit on commissioning language, but at least some are already tying labor availability to capital-plan execution and the ability to construct and operate grid infrastructure.']} 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.