CoolDeep AI Digest

The article provides a comprehensive guide to utilizing 'Claude Cowork,' a desktop application that distinguishes itself from Claude Chat (the browser version) and Claude Code (a developer-centric terminal tool). Unlike the chat interface, Cowork connects directly to a user's local files, allowing the AI to read and write documents within a designated workspace. This eliminates the repetitive manual process of providing context and copy-pasting data, which the author estimates can save users several hours of productivity per month by treating the AI as a persistent employee with a dedicated 'desk' and memory of ongoing projects. To optimize the experience, the author shares five strategic tips. First, they recommend using Obsidian as a Markdown translator to make the raw .md files used by Cowork readable and easy to edit. Second, they emphasize keeping the main instruction file (CLAUDE.md) under 300 lines to reduce token consumption and latency, suggesting a structured approach with sections for memory, preferences, rules, and a 'routing map' to trigger specific workstations. Third, the author advises streamlining the memory file (MEMORY.md) by limiting entries to two sentences and capping the file at 150 lines, utilizing an ARCHIVE.md file for long-term storage to maintain efficiency. Fourth, the guide explains how to migrate from Claude Projects to Cowork to gain more direct control over instructions and knowledge files, transforming project memories into structured workstation files. Finally, the author begins to distinguish between 'Workstations'—used for processes requiring human judgment—and 'Skills,' though the text cuts off before fully detailing the latter. Overall, the article positions Cowork as a powerful tool for non-technical business users to build a sophisticated, automated system around their professional workflows, shifting the AI interaction from a series of isolated tasks to a continuous, integrated partnership.