6d • General discussion
One agent can get you started.
Multi-agent architecture helps you scale.
The real difference is not hype — it is responsibility.
A single agent is fast to prototype and useful for simple workflows, but once you add too many tools, logic, and decisions, it becomes difficult to inspect, debug, and improve.
Multi-agent systems work better when each agent has a clear role:
Research agent
SQL/data agent
RAG agent
Evaluation agent
Recommendation agent
Orchestration layer
The key design principle:
Split by responsibility, not by hype.
This is where agentic AI becomes practical for real business use cases.
What are you building today: one powerful agent or a team of specialist agents?
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One agent can get you started.
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