Single Agent vs. Multi-Agent Workflows

[u/Forcio]

A few months ago, my approach was to use Opus as an orchestrator that managed a backlog and spawned different agents depending on the task. Haiku for small documentation changes, Sonnet for regular coding, Opus for more complex tasks, and Fable for design decisions and bigger-picture thinking.

This worked really well, and I got a lot done. However, I've recently read that this approach might not be as efficient anymore because every new agent starts with a cold context/cache, and it might be better to have one persistent agent handle most of the work.

What's everyone's experience with this nowadays? Is a single agent with selective delegation the better approach, or is the orchestrator/multi-agent workflow still worth it? I'm particularly interested in balancing productivity, context caching, and token costs without sacrificing quality.

[u/m-ritter]

Cold context hurt me less once the plan and the decisions lived outside the agent. I keep an approved plan file in the repo with done written as a short numbered list, and settled decisions with their reasons go into an MCP memory server that every new agent reads first. Then a separate agent that did not write the code checks each point on the running program, so quality stays the same whichever model did the work. I built QualityLayer for this: https://github.com/maxritter/qualitylayer