Scaffold PIG and model the compute-GTM ontology
PIG is an agent-native CRM for two-sided AI-compute companies: businesses that buy GPU capacity from providers and resell it. Their business is the spread between two pipelines, which is precisely what a generic CRM cannot represent. The load-bearing decision is the `allocations` table, joining a capacity_commitment (what we bought, at a known cost) to a demand_deal (what we sold, at a known price). Margin, utilisation and idle capacity all fall out of that one join. Cost is charged against the full commitment rather than only the hours that sold, because unsold hours are already paid for and any other treatment flatters a block that is losing money. Domain decisions worth noting, each grounded in how this market operates: - Demand stages put `legal` second, not last. Customers do not hand workloads to an infrastructure provider before paper is executed. - Supply qualification splits technical from financial diligence, recorded attributably. Accepting capacity is a two-key decision. - Capacity carries a time SHAPE (intervals + quantities), not a window. Commitments ramp and step down; a rectangle reports availability that does not exist in the month someone wants it. - SLAs model three distinct shapes: none, a reliability tier plus credits policy, and a negotiated agreement. Aggregators generally cannot promise uptime on resold capacity, but negotiate heavyweight paper upstream. Remedies include fee abatement, which is materially better than a capped credit and is not expressible as one. - Export control is a predicate on the allocation edge, evaluated against the ULTIMATE parent's jurisdiction. Country of incorporation is not a valid key, so this cannot live as a flag on an account. - Agent-derived claims land in `facts` with a confidence band and evidence. Only verified claims self-apply; weaker ones await review. - The API never calls the agent. It writes to a leased queue, guarded by a partial unique index on unfinished work. Verified: typechecks clean, migration generates and applies to Postgres 16 (31 tables, 24 enums, 117 indexes). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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