Scaling Lessons From GLM-5 Coding Agents | dailyai.report
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Agents
120d ago
Scaling Lessons From GLM-5 Coding Agents
Debugging GLM-5 at scale revealed critical bottlenecks in how coding agents handle long-context state. The team identified specific memory leaks and latency spikes during complex repository traversal. These findings highlight the gap between prototype performance and production stability.
The Signal
Engineers must now optimize state management to prevent agent crashes during deep-code analysis.