What happens when you give each role in a design workflow its own dedicated AI agent? That's the premise behind Design Agents, a browser-based canvas where separate AI agents handle distinct parts of a design project simultaneously, rather than one model doing everything.
The interface works like a whiteboard where agents are assigned specific roles - strategy, visual direction, copy - and their outputs appear as linked blocks that feed into each other. The creator's intent is to replicate how actual design teams divide work, with specialization improving output compared to general-purpose prompting.
This is an early-stage solo project, documented in a blog post that leans more toward explaining the concept than reporting results. The demo focuses on the interaction model rather than finished design outputs.
The underlying architecture question is genuine. Whether separating agents by role produces meaningfully better results than prompting a single capable model depends heavily on task complexity. For involved, multi-phase design work - brand identities, full product interfaces - role separation can surface conflicting priorities that a single model would smooth over. For simpler projects, the coordination overhead is rarely worth it.
Design Agents doesn't include benchmarks comparing its output against human designers or single-model alternatives. That's the missing evidence the concept needs to convince beyond the earliest adopters.