Add compute history time-series (capacity vs demand chart), revenue vs expenses
dual-line chart, enhanced system status (training allocation, network uptime,
model freshness), active operations panel, market position bars, and competitor
snapshot. Stat cards expand from 3 to 6 as player progresses through eras.
Graceful v9→v10 save migration preserves existing games.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Create researchBonuses utility to aggregate tech tree effects into all game systems
(infrastructure energy costs, compute efficiency, training speed, model capability, reputation)
- Rework model capability from sqrt(compute) to 4-pillar formula (params + compute + data + research)
- Make context window affect benchmarks and inference speed
- Add MoE tradeoffs: 1.5x VRAM, 0.8x training speed
- Enforce research point costs as a gate for unlocking research
- Add real consequences to data contamination events (reputation hit, legal costs)
- Scale talent costs from $0.03 to $5/tick per headcount
- Scale compliance costs 100x to be meaningful
- Rework competitor acquisition: cheaper but grants headcount, RP, and reputation
- Remove dead code: sfxVolume, autoSaveInterval, notificationsEnabled,
FAST_FORWARD_BATCH_SIZE, CHINCHILLA_OPTIMAL_RATIO
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Expand from 10 to 18 rack SKUs across NVIDIA, AMD, and custom ASIC vendors, each with
distinct training vs inference FLOPS, VRAM capacity, cooling requirements, and interconnect
technology. Adds cooling hierarchy (air/liquid/immersion) that gates rack deployment, VRAM
requirements that gate model training by generation, interconnect multipliers for distributed
training scaling, and PUE-based energy cost reduction for advanced cooling. Includes save
migration from v4 to v5, 6 new research nodes, and UI updates showing split compute stats.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three intertwined fixes:
1. Zero-capacity utilization: when inference allocation was 0%, the
guard clause returned 0% utilization instead of 100%, so the market
system never penalized satisfaction and subscribers never churned.
2. Stale compute in market: restructured tick order so capacity is
computed before market runs, giving satisfaction calculations
current-tick demand/capacity ratio instead of previous tick's.
3. Subscriber growth: replaced pure compound growth (reached billions
in minutes) with logistic saturation curve. Era-based market caps:
startup 10K, scaleup 1M, bigtech 20M, agi 100M. Quality and
reputation expand the effective cap.
Also tuned FLOPS-to-tokens multiplier (10 → 26) for balanced
demand/capacity feel across all eras, and added market saturation
indicator to the Market page.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Turborepo monorepo with three packages:
- packages/shared: TypeScript types for all 14 game systems + balance constants + formatting utils
- packages/game-engine: Pure TS simulation engine with tick processor, economy, infrastructure, compute, research, market, and reputation systems
- apps/web: React + Vite + Tailwind + Zustand frontend with sidebar dashboard layout, new game screen, dashboard with charts, infrastructure management, and model training pages
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
josh