The Wealth of Agents: Scaling Agentic AI Across Developers
We study multi-developer agentic systems (MDAs) which enable developers to collaboratively build agentic systems to push frontier capability beyond what any individual developer could achieve alone.
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Key points
- Today's agentic systems are typically designed, built, and deployed by single developers with full control over all participating agents.
- While this simplifies development, it limits the potential scale of agentic systems.
- We construct empirical and theoretical models of developers to compare MDAs with single-developer agentic systems (SDAs).
- Put together, our results make a preliminary case for MDAs as a new scaling axis by enabling developers with diverse capabilities and resources to advance agentic AI collaboratively.
Sources (1)
- [1]The Wealth of Agents: Scaling Agentic AI Across DevelopersarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 14, 05:19 PM
We study multi-developer agentic systems (MDAs) which enable developers to collaboratively build agentic systems to push frontier capability beyond what any individual developer could achieve alone.
Today's agentic systems are typically designed, built, and deployed by single developers with full control over all participating agents.
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