Deconstruct Your Monolithic Agent

1. 1
   Audit Your Monolith's Weakest Link

   Review your largest, most complex agent. Identify a single, self-contained function (e.g., 'summarize user history', 'generate SQL query') that is frequently a source of errors or requires constant prompt tweaking. This is your prime candidate for extraction.
2. 2
   Extract Your First Specialized Agent

   Create a new, single-purpose agent for the task identified in Step 1. Give it a highly-focused prompt and only the specific tools it needs. The goal is hyper-optimization, not general capability.
3. 3
   Implement a Simple Router

   Modify your original system to act as a router or orchestrator. Instead of handling the summarization task internally, it should now detect the user's intent and delegate the work by calling your new `SummarizationAgent`. This isolates the logic and creates a clear communication pathway.
4. 4
   Deploy and Measure the Impact

   Deploy your new specialized agent independently. Measure its task-specific success rate against the monolith's baseline and track your Mean Time to Recovery (MTTR) for any failures. Your goal is to see a 5-15% point increase in success and a reduction in recovery time from hours to minutes.
5. 5
   Build a Multi-Agent System from Scratch

   Now that you've extracted one agent, solidify your skills by building a complete multi-agent system. Our DIY package provides a hands-on lab to construct a composable system for a real-world use case, reinforcing the principles of routing, specialized agents, and independent deployment.

Identify one distinct, high-failure task within your largest agent's prompt. This could be data extraction, summarization, or tool usage.