You have a working single-agent prototype. The hard part isn't building it – it's knowing when it's actually ready to decompose, which architecture to decompose it into, and what breaks first when you do. This playbook walks AI developers and ML engineers through every critical decision point in the transition from single-agent proof-of-concept to production multi-agent system. Seven structured sections cover the full arc: auditing your prototype for decomposition readiness, selecting the right orchestration pattern for your task structure, designing a memory architecture that holds across an agent network, defining inter-agent communication contracts that survive real load, setting safety boundaries and human-in-the-loop triggers before an incident forces your hand, and running a pre-launch production readiness check across observability, cost controls, and rollback. A dedicated failure mode catalog gives you the diagnostic vocabulary to recognize and recover from the breakdowns that catch most teams off guard. If you're about to scale – or already scaling and hitting friction – this is the operational reference you build from.
What's included
- A Prototype Readiness Audit framework that walks you through the specific criteria for determining whether your single-agent system is actually ready to decompose – before you commit to a multi-agent architecture
- An Orchestration Pattern Selection guide that maps common task structures to the right multi-agent architecture, so you're choosing a pattern based on your system's actual shape rather than what's trending
- A Memory Architecture Design section covering how to choose and connect the right memory layers across an agent network – including what breaks when memory boundaries are drawn incorrectly
- Inter-Agent Communication Contracts covering schema design, failure signal definitions, and retry protocols built to hold under production load – not just in a clean demo environment
- A Safety Escalation Design framework for setting agent authority boundaries and human-in-the-loop triggers before you need them, with explicit guidance on where most teams draw those lines too late
- A Failure Mode Catalog that names, describes, and provides recovery paths for the most common multi-agent breakdowns – giving you a diagnostic reference for issues that are hard to Google your way out of
- A Production Readiness Checklist covering observability instrumentation, cost controls, and rollback procedures to work through before your multi-agent system goes live
