Why Single-Agent AI Harnesses Are Expensive (And How Delegation Fixes It)

Reddit r/AI_Agents News

Summary

A blog post explains why single-agent AI harnesses are expensive due to token costs and monolithic issues, advocating for task delegation using specialized agents and patterns like predefined, dynamic, local CLI, and remote agents.

I just published a blog post reviewing all the different kinds of AI subagents used in AI harnesses today. It's based on actually building these systems myself. Here's what I found: any AI harness that wants to scale must support task delegation. Why? Two main reasons: Delegating saves tokens. When your main agent tries to do everything, context grows with every tool call. Costs explode. But when you delegate to specialized agents, each one works with only the context it needs. Way cheaper. It lets you build distributed systems. You're not stuck with one monolithic agent anymore. You can have specialized agents running locally, on remote servers, even in the cloud. They all talk to each other through simple protocols (MCP, REST APIs). I wrote up four different delegation patterns: Predefined agents inside your harness Dynamic agents spun up on demand Local CLI agents Remote agents over the network Each one solves different problems. Most people don't realize how different they are. The full blog post link is in the comment. Have you tried delegating in your AI harness setup? Curious what patterns you're using.
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