Building multi-agent systems is becoming easier, but coordinating their work within a real development team remains a challenge.
Frameworks like CrewAI make it possible to create agents with specific roles, assign tasks, and coordinate their execution. However, once these agents become part of a larger software development workflow, another question appears:
How do we coordinate human developers and AI agents without losing context or visibility?
From Multi-Agent Systems to Team Collaboration
Imagine a development team working on a new application:
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A human developer defines the requirements.
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A coding agent implements a feature.
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A testing agent checks the implementation.
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A review agent identifies potential issues.
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A human developer validates the final changes.
Each agent has a responsibility, but the team also needs a shared way to organize tasks, monitor progress, and manage execution.
Where Sharkly.ai Fits
Sharkly.ai approaches this problem from the development workspace perspective.
It provides a shared environment where teams can:
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Assign tasks to human teammates or AI agents.
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Coordinate multiple agents working on different tasks.
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Reuse agent configurations through shared Spaces.
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Follow execution progress and review results.
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Keep humans involved in important development decisions.
Rather than replacing frameworks such as CrewAI, Sharkly.ai focuses on organizing human-agent collaboration around development tasks.
Website: https://sharkly.ai/
Documentation: Agents - Sharkly Docs
An Interesting Question for Agent Builders
As multi-agent systems evolve, orchestration is only one part of the problem. Teams also need task ownership, shared context, execution visibility, and human oversight.
**How are you connecting your CrewAI agents to the rest of your development workflow? Are you using a separate workspace to coordinate human developers and AI agents?