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Maka is a local-first desktop AI workbench whose new feature allows agents to automatically optimize their own system prompts by generating variants, using Harbor container evaluation, and an acceptance policy for iterative improvement, all without human intervention.
This article provides a comprehensive beginner's guide to Codex, introducing its 6-layer capability framework (workspace, rules, execution, data entry, verification operations, reuse layer), helping users understand how to build workflows from scratch, including project organization, pattern selection, data access, and process automation.