•1 min read•from InfoQ
How Slack Manages Context in Long-running Multi-agent Systems
Our take
In "How Slack Manages Context in Long-running Multi-agent Systems," Sergio De Simone explores innovative strategies that enhance productivity within complex environments. Slack engineers have shifted from traditional chat logs to a structured memory approach, emphasizing validation and distilled truth. This transition not only maintains coherence but also ensures the accuracy of interactions in multi-agent systems. By implementing these techniques, Slack effectively supports users in navigating lengthy conversations, enabling them to focus on meaningful tasks while improving overall efficiency and collaboration.
To sustain productivity in long-running agent systems, Slack engineers moved away from accumulating chat logs and started using structured memory, validation, and distilled truth to maintain coherence and accuracy of long-running agent systems.
By Sergio De SimoneRead on the original site
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