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Memory profilers, call graphs, exception reports, and telemetry
How giving AI coding assistants access to system-wide context—from memory profiles to error reports—transforms their debugging capabilities.
but rather, it does mean developers spend more time helping AI understand the full picture—manually bridging the gap between code and the several information sources that make up the complex system it lives within. Call graphs generated from production trace data Memory profiler outputs revealing resource bottlenecks Exception reports from monitoring systems Telemetry information showing actual usage patterns However, when we added the source file to the context, Aider provided significantly deeper analysis, identifying the specific recursive SQL queries likely causing the timeout and explaining how their 50,000-row limits interact with complex citation networks.
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