Most AI agents today are still designed like monoliths: one prompt, one model, one response.
That works for Q&A.
It fails for anything that looks like real work.
Tasks like competitive research, synthesis across sources, and self-verification expose the limits of solo agents very quickly.
What’s happening now mirrors classic software evolution:
- Monolithic apps → distributed services
- Single prompts → coordinated agent teams
We built a production research workflow using CrewAI to explore this shift end-to-end.
In our latest newsletter, we cover:
- The architectural reasons solo agents break down
- What production multi-agent systems actually look like
- How teams evaluate and catch failures before users do
Multi-agent systems aren’t an experiment anymore.
They’re how complex AI work gets done reliably.
📖 Read the full breakdown here -> https://shorturl.at/5PmDc
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