AIHostingTycoon/docs/how-to-play.md

# How to Play

## Getting Started

When you start a new game, you name your AI company and begin in the **Startup era** with $50,000 in seed money. Your goal: build the world's leading AI company and eventually achieve AGI.

The game runs in real-time at 1 tick per second. Use the speed controls in the top bar to play at 1x, 2x, or 5x speed, or pause to plan your next moves.

## The Core Loop

The fundamental cycle of the game:

1. **Buy GPUs** — Purchase compute hardware in the Infrastructure page
2. **Allocate compute** — Split between training new models and serving inference
3. **Train a model** — Start a training run in the Models page
4. **Deploy** — Put your trained model into production
5. **Earn revenue** — Users pay for API access and subscriptions
6. **Reinvest** — Buy more GPUs, hire talent, fund research

Everything else in the game builds on or modifies this loop.

## Key Resources

### Money
Your primary resource. Earned from API revenue and consumer subscriptions. Spent on GPUs, talent, data, and energy. Shown in the top bar with income trend.

### Compute (FLOPS)
Total processing power from your GPU fleet. The main bottleneck — you never have enough. Split between training (building new models) and inference (serving users).

### Reputation (0-100)
Public trust in your company. Affects talent acquisition, user growth, investor confidence, and regulatory treatment. Composed of safety record, public perception, employee satisfaction, and regulatory standing.

### Talent
Headcount across four departments: Research, Engineering, Ops, and Sales. Each department has effectiveness and morale scores that affect their output.

### Data
Training data quality and quantity. Better data produces better models. Acquired through the data marketplace or generated passively from your user base.

### Research
Progress through the tech tree. Unlocks better GPU tiers, model architectures, efficiency improvements, and safety techniques.

## Game Systems

### Infrastructure

Your datacenters house GPU clusters. Seven global regions are available, each with tradeoffs:

- **US-West / US-East** — Balanced costs, good latency to North American users
- **EU-West / EU-North** — Higher energy costs, strict regulation, access to EU market
- **Asia-East / Asia-South** — Lower costs, emerging markets
- **Middle-East** — Cheap energy, political risk

Each datacenter has a size (GPU slots), cooling level, and redundancy level. Higher redundancy reduces GPU failure rates but costs more. GPUs can fail randomly — lost hardware means lost capacity until you replace them.

GPU types unlock through research. Early on you have basic GPUs; research unlocks progressively more powerful (and expensive) tiers.

### Research

The tech tree has two dimensions:

- **Generations**: Small → Medium → Large → Frontier → AGI-scale models
- **Specializations**: Reasoning, coding, creative, multimodal, agents

Research projects require researchers and time. Completing projects unlocks new capabilities:
- Better GPU tiers
- Training efficiency improvements (quantization, distillation)
- Safety techniques (alignment research, interpretability)
- New product capabilities

### Models

Training a model requires:
- **Compute**: How many FLOPS to dedicate to training
- **Data**: Training data tokens to use
- **Time**: Training runs take real time (boosted by researcher and engineer quality)

When training completes, your model gets capability scores across five dimensions: reasoning, coding, creative, multimodal, and agents. A composite benchmark score determines its market competitiveness.

#### Safety vs Capability

This is the game's central tension. Safety research improves your model's safety score but penalizes benchmark performance. Low safety scores risk:
- **Safety incidents**: PR disasters that damage reputation
- **Regulatory backlash**: Higher compliance costs

High safety scores mean:
- Lower benchmarks (competitors may outperform you)
- Better regulatory standing
- Protection from reputation-damaging incidents

There's no single right answer — it depends on your strategy.

#### Model Tuning

After deploying a model, you can tune its behavior:

- **Presets**: Quick settings (Helpful-Safe, Performance, Creative, Balanced)
- **Sliders**: Fine-grained control over safety, creativity, verbosity, and speed/quality tradeoff (unlocked after completing alignment research)

### Market

Revenue comes from two sources:

**Consumer Subscriptions**: Users pay a monthly fee for your chat product. Subscriber count grows based on model quality and shrinks from churn. Higher quality models and competitive pricing accelerate growth.

**B2B API**: Enterprise customers pay per token. Set your input/output token pricing to balance revenue against demand.

#### Overload Policy

When demand exceeds your inference capacity, you choose how to handle it:
- **Queue depth**: How many requests to buffer
- **Rate limits**: Max requests per user
- **Degrade quality**: Serve faster but lower-quality responses
- **Prioritize enterprise**: Give B2B customers priority over consumers

Each choice has tradeoffs. Degrading quality hurts satisfaction. Enterprise prioritization frustrates consumer users.

#### Open Source

You can open-source deployed models. This:
- Boosts reputation significantly
- Attracts more talent
- Reduces direct revenue from that model
- Increases subscriber growth (community effect)

### Talent

Four departments, each critical:

| Department | Effect |
|-----------|--------|
| Research | Speeds up R&D projects and improves model training quality |
| Engineering | Speeds up model training and infrastructure reliability |
| Ops | Reduces infrastructure costs and failure rates |
| Sales | Increases enterprise API demand |

Hire to increase headcount. Morale affects effectiveness — keep your teams happy by managing workload and company reputation.

### Competitors

Three rival AI labs compete with you. Each has a personality:

- Some prioritize safety, others move fast
- Some are big-tech giants with deep pockets, others are scrappy startups
- They release models, gain users, and react to your moves

In later eras (Big Tech and AGI), you can **acquire** competitors, absorbing their talent and technology.

### Events

Random and conditional events keep the game dynamic. Categories include:

- **Industry**: Breakthroughs, open-source releases, benchmarks
- **Regulatory**: Hearings, compliance requirements, AI bills
- **PR/Cultural**: Media coverage, safety debates, public opinion shifts
- **Internal**: Employee issues, technical problems
- **Market**: Demand spikes, pricing pressure
- **Geopolitical**: Export controls, energy crises, natural disasters

Most events present 2-3 choices with meaningful tradeoffs. Some trigger chain events with delayed consequences.

### Funding

Raise capital through VC rounds as you grow:

| Round | Amount | Dilution | Key Requirement |
|-------|--------|----------|----------------|
| Seed | $100K | 10% | $100/s revenue |
| Series A | $500K | 15% | 100 users, 20 reputation |
| Series B | $2M | 12% | 1,000 users, 30 reputation |
| Series C | $10M | 10% | 10,000 users, 40 reputation |
| Series D | $50M | 8% | 50,000 users, 50 reputation |
| IPO | $200M | 20% | 100,000 users, 60 reputation |

Each round permanently dilutes your founder equity. Time your raises carefully — you want enough runway to grow but minimum dilution.

## Era Progression

The game has four eras that unlock progressively. Transitions happen automatically when you meet thresholds:

### Startup → Scale-up
- Revenue: $10,000/s
- Best model capability: 15+
- Reputation: 30+

### Scale-up → Big Tech
- Revenue: $1,000,000/s
- Best model capability: 50+
- Reputation: 60+

### Big Tech → AGI
- Revenue: $100,000,000/s
- Best model capability: 90+
- Reputation: 70+

Each era unlocks new game systems and sidebar pages. Watch for the "NEW" badge on newly available pages.

## Strategies

### The Safety-First Path
Invest heavily in alignment and interpretability research. Your benchmarks will lag competitors initially, but you avoid safety incidents and build strong regulatory standing. Good for steady, sustainable growth.

### The Move-Fast Path
Minimize safety investment, maximize raw capability. You'll lead benchmarks and attract users quickly, but safety incidents can crater your reputation. High risk, high reward.

### The Open-Source Play
Open-source your models to build massive community goodwill and attract top talent. Revenue per model drops, but subscriber growth accelerates and reputation soars. Strong mid-game strategy.

### The Vertical Integrator
Invest in multiple specializations and diverse products. Spread your compute across reasoning, coding, creative, and multimodal capabilities. More resilient but slower to dominate any single benchmark.

## Tips

- **Don't neglect infrastructure redundancy.** GPU failures at scale can cripple your capacity.
- **Watch your burn rate.** It's easy to over-hire and run out of money before your models generate revenue.
- **Timing funding rounds matters.** Raise too early and you give up equity cheaply. Raise too late and you run out of runway.
- **Safety research compounds.** Each safety project improves all future models.
- **Check competitor activity.** If a rival just released a strong model, expect to lose some subscribers unless you respond.
- **Events have lasting consequences.** Read the options carefully — some choices trigger follow-up events.
- **The data flywheel is real.** More users generate more data, which trains better models, which attract more users.
- **Deploy your models.** A trained model sitting idle generates zero revenue.
- **Use speed controls.** Pause when making big decisions. Speed up during waiting periods.

## Saving

The game auto-saves to your browser's localStorage every 60 ticks. You can also:
- **Export** your save as a JSON file from the Settings page
- **Import** a previously exported save
- **Cloud save** by creating an account (requires the backend server)

Closing the browser tab is safe — when you return, an offline catch-up system simulates what happened while you were away (up to 24 hours).

## Achievements

15 achievements track your progression milestones, from training your first model to reaching AGI. Check the Achievements page to see what you've unlocked and what's still ahead.