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.…