Simulation Environments

Create simulation environments for safe agent training

Core Design Principles

Good simulation environments share four critical properties. These aren't optional - without them, your simulation will be frustrating to use and ineffective at finding bugs.

Interactive: Principle Explorer

Learn what makes simulations effective:

👁️
Observability

See everything: agent thoughts, API calls, state changes, decisions. Record all interactions for debugging.

✅ Best Practice

Log every decision with reasoning. Trace full execution path. Replay scenarios exactly.

❌ Avoid This

Black box agent. No logs. Can't reproduce failures. Debug by guessing.

Interactive: Quality Impact Calculator

See how simulation quality affects testing effectiveness:

Simulation Quality50%
PoorExcellent
Bugs Found
260
pre-production
Test Speed
505
tests/hour
Confidence
62%
before deploy

Moderate simulation quality catches some bugs but misses edge cases. Still risky for production.

💡
Implementation Priority

Start with observability and determinism. These make debugging possible. Add easy reset next - you'll run thousands of tests. Finally optimize speed. A slow but observable simulation beats a fast black box. You can't fix bugs you can't reproduce or understand.

Environment Types