TL;DR
Technical guide clarifying agent autonomy, tool definitions, and when to use workflows, single agents, or multi-agent systems to avoid overengineering.
Key Points
- Workflows for fixed, predictable steps; single agents when path varies based on discovery; multi-agent only for true parallelism or context overload
- Single agents handle best with fewer than 10-20 tools; beyond that threshold, tool selection degrades and multi-agent splitting becomes justified
- Real-world case: marketing platform ditched planned 12-agent system for single agent with specialized tools, reducing complexity and cost while maintaining capabilities
- Research + writing use case required multi-agent split due to exploratory research phase vs. constrained writing phase with different tool needs
Why It Matters
LLM application architects frequently overengineer with multi-agent systems when simpler architectures suffice. This framework provides concrete decision criteria—autonomy requirements, tool count thresholds, and context constraints—helping developers choose architectures that minimize token costs, latency, and debugging complexity while solving the actual problem.
Source: www.louisbouchard.ai