Overhaul infrastructure: replace GPU model with rack-centric system
CI / build-and-push (push) Successful in 33s
CI / build-and-push (push) Successful in 33s
Replace flat GPU buying with a realistic data center + rack pipeline: - 4 DC tiers (small/medium/large/mega) with construction time, dual capacity constraints (rack slots + power budget kW), and era/research gating - 10 predefined rack SKUs from consumer GPUs through custom ASICs, each with unique FLOPS, power draw, cost, and pipeline timings - 6-stage procurement pipeline (order → mfg → receive → install → test → production) with Kanban UI, talent-influenced speed bonuses - Test failures (5-25% base rate) reduced by cooling, ops talent, and QA research; auto-repair with cost and re-test cycle - Production failures at low per-tick rate, racks sent to repair pipeline - Cooling and redundancy upgrades per DC (reduce failure rates) - 4 new tech tree nodes (DC Engineering II/III/IV, Quality Assurance) - Save version bump (1→2) with migration that resets old saves - Updated economy system to account for rack repair costs - Redesigned Infrastructure page with pipeline Kanban, capacity bars, rack ordering, and DC upgrade panels Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -6,6 +6,7 @@ export function processEconomy(
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state: GameState,
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market: MarketTickResult,
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infrastructure: InfrastructureState,
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extraCosts: number = 0,
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): EconomyState {
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const revenue = market.apiRevenue + market.subscriptionRevenue;
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@@ -20,7 +21,7 @@ export function processEconomy(
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const eraIdx = ['startup', 'scaleup', 'bigtech', 'agi'].indexOf(state.meta.currentEra);
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const complianceCost = bestCapability > 30 ? bestCapability * REGULATION_COMPLIANCE_PER_CAPABILITY * (1 + eraIdx * 0.5) / 100 : 0;
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const expenses = infraExpenses + talentExpenses + dataExpenses + complianceCost;
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const expenses = infraExpenses + talentExpenses + dataExpenses + complianceCost + extraCosts;
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const money = state.economy.money + revenue - expenses;
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