Commit Graph

4 Commits

Author SHA1 Message Date
josh 102e05c8ba Add game-simulation package with multi-run balance testing, fix stalled-pipeline trap
Balance Check / balance-simulation (push) Failing after 11m32s
Balance Check / multi-run-balance (push) Failing after 23m46s
CI / build-and-push (push) Successful in 1m20s
Adds a full simulation harness (game-simulation package) with greedy/random strategies,
36-metric diagnostics, multi-run orchestration via child processes, and a statistical
interpreter. Includes 2.3x engine performance optimizations (research bonus caching,
per-DC dirty tracking, reduced allocations in tick pipeline, single-pass loops).

Fixes a critical balance bug where training pipelines stalled on insufficient VRAM would
permanently block training slots — the engine never re-checked stalled pipelines, and the
greedy strategy didn't pre-check VRAM requirements. This caused 20-25% of seeds to get
stuck in Scale-up era. All three fixes (engine un-stalling, strategy VRAM pre-check,
stalled pipeline cancellation) bring pass rate from 75% to 100% across 20 random seeds.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-26 06:11:26 -04:00
josh 09a5cb69a7 Overhaul market system with shared TAM competition, multi-tier pricing, enterprise pipeline, and developer ecosystem
CI / build-and-push (push) Successful in 42s
Replaces the simplified single-subscriber market with a full competitive simulation:
shared TAM with softmax market shares across 4 segments, multi-tier consumer
subscriptions (Free/Plus/Pro/Team) and API tiers (Free/PAYG/Scale/Enterprise),
enterprise sales pipeline (Lead→Qualification→POC→Negotiation→Active→Renewal)
with SLA tracking, developer ecosystem flywheel, technology obsolescence pressure,
seasonal demand cycles, and two new product lines (Code Assistant, AI Agents Platform).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-25 08:30:24 -04:00
josh 4c1c0e9ff2 Overhaul model system with multi-stage training, variants, benchmarks, and eval
CI / build-and-push (push) Successful in 32s
Replace the single-stage training + flat capability score with a realistic AI
development pipeline: pre-training with Chinchilla scaling laws, SFT with
specializations, alignment with safety/capability tradeoffs (RLHF/DPO/Constitutional),
model families with distillation/fine-tuning/quantization variants, named benchmark
suite with compute-costing eval jobs, and segment-specific market quality.

Phases 1-6 of the model rework plan: new types, engine rewrite, save migration,
training events/risk system, concurrent training, variant creation, benchmark
evaluation with leaderboard, and market integration.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-25 07:36:34 -04:00
josh 8c9555bc08 Add Week 2 depth systems: research, events, competitors, talent, data
Tech tree with 21 research nodes across 5 categories (infrastructure,
efficiency, generation, specialization, safety). Research page with
category-grouped cards, progress tracking, prerequisite gating.

Event engine with 34 events across industry/regulatory/PR/internal/market
categories, weighted random firing, cooldowns, expiry, and choice modal
with consequence preview. Events auto-expire with default choice.

Competitor system with 3 rival AI labs (Prometheus AI, Nexus Labs, Titan
Computing), personality-driven milestone progression, and comparison UI.

Talent page with department hiring, headcount management, and key hire
recruitment from a pool of 10 named characters with special abilities.

Data marketplace with 8 purchasable datasets, user data flywheel from
subscribers, and data system processing in tick loop.

Era transition system checks revenue/capability/reputation thresholds.
All new systems integrated into tick processor with notifications.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-24 17:30:24 -04:00