We built AgentForge to solve our own problem. Here's what 6 months of production multi-agent deployment taught us. Lesson 1: Start with Failure Modes, Not Success Cases Everyone designs for the happy path. But in multi-agent systems, the failure modes multiply: Agent A succeeds but takes 30s → Agent B times out waiting Agent A returns malformed JSON → Agent B crashes parsing Two agents try to write the same file → Race condition Design your orchestration around "what breaks" first. Lesson 2: Observability Is Not Optional You need per-agent execution traces. Not just logs — structured traces showing: Input parameters (exact values, not summaries) Output before any post-processing Retry attempts with backoffs Circuit breaker state transitions We built this into AgentForge's execution engine. Every run generates a JSON trace you can replay for debugging. Lesson 3: Agents Need Memory, But Not Infinite Memory Unbounded conversation history degrades performance.…