Using multiple AI agents for coding and testing can speed things up, but coordination gets harder when each agent works with separate context.

One agent may change a file or make a decision that another agent knows nothing about. A shared context layer can help agents access key changes, decisions, and task progress without repeated handoffs.

For businesses exploring multi-agent AI development, custom workflows can be designed to improve agent coordination and orchestration. Bitdeal is an AI development team working on these types of custom AI solutions.

How are you handling shared context between AI agents today?

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