Lamis Mukta - Learning while you sleep: Beyond memory to dreaming - AI Native DevCon June 2026

Context engineering transforms raw model intelligence into scalable, durable products by managing how agents access and update information. Initial approaches like simple markdown files and autonomous in-band memory tools provide foundational steering, but they struggle with context bloat and lack of cross-session visibility. To address these limitations in production environments, developers must implement robust engineering practices including versioning, concurrency controls, and strict permissioning. The "dreaming" paradigm further optimizes performance by using asynchronous, out-of-band processes to analyze interaction transcripts and refine memory stores. This approach identifies recurring failures and updates curricula, allowing agents to learn from collective experiences rather than isolated sessions. By treating memory as a managed file system and automating curation, developers can significantly improve agent accuracy, reduce latency, and achieve true continual learning across complex, multi-agent architectures.