Using WorkBuddy for Club Document Security After Reviewing AI Coding Tools

That article "From Strong to Weak: 2026 AI Programming Tool Landscape Review" said Codex aims to be a cross-device collaborative AI colleague, which is the right direction. It mainly solves engineering chains like code repos, terminals, and CI. My course project is messier: dozens of Feishu-exported PDFs, chat screenshots, Excel task sheets, teacher-annotated Word docs, and code READMEs all piled up in cloud storage. I've used WorkBuddy for about a month and last week did a real test with a club weekly report. It's better suited for locking office materials into a workspace that can view, manage, and assign tasks.

That day, I opened WorkBuddy, clicked Workspace in the top left, selected New Workspace, and named it 0916 Course Project. Think of the workspace as a local file cabinet; the AI can only read files you put in and authorize, without rummaging through your whole computer. Then I created three folders: 01 Raw Materials, 02 Organized Results, and 03 Exports, dragging files in by type. Beginners shouldn't dump everything into the root directory immediately. After files go in, click Import, select Documents, Spreadsheets, Screenshots, wait for the status to change from Parsing to Searchable, then start asking questions. Searchable means WorkBuddy has indexed these files and can find paragraphs and tables by content, not just by filename.

My task was specific: organize the Feishu PDFs, Excel task sheet, and chat screenshots in 01 Raw Materials into a weekly report base table with four columns: "Owner, Deadline, Status, Risk." In the input box, I wrote: Read only from 01 Raw Materials, output to 02 Organized Results, do not modify original files, do not merge private contact info from screenshots. Here's a key parameter: don't set the context scope too large at once. WorkBuddy's context is the file content it can currently remember and retrieve; if I exceed a dozen large files, it starts mixing things up. So I limited the context to 01 Raw Materials and enabled only Table Merge, Meeting Minutes Extraction, and Risk List skills. It took about ten minutes, the table came out, format was basically usable, and task rows from Feishu PDFs matched owners in the Excel sheet.

However, there are pitfalls. The first time, I dumped all files in and asked it to simultaneously handle the weekly report, PPT outline, and reimbursement summary. Result: it mixed the "Owner" and "Notes" columns and even treated teacher annotations as task sources. Later, I learned to make it do one thing at a time and start a new session after finishing. Another pitfall is screenshots. Chinese sentence breaks and table lines in chat screenshots are unstable; WorkBuddy might recognize "Student Wang" as "Wang Tongzi." The solution isn't complex: put screenshots in a separate folder, name files clearly like Screenshot-Meeting-0914, ask it to generate a List to Proofread first, then manually correct. Don't expect full automation in one go; the scariest thing in office materials is neatly organized incorrect information.

Permissions are why I think WorkBuddy is better than generic chat models for clubs. I clicked Collaboration and invited the leader, two members, and the advisor. I split permissions into three layers: Leader can edit 02 Organized Results; Members can only view and comment; Advisor has read-only access to 03 Exports; 01 Raw Materials is manageable by everyone but locked by default. Here, read-only means viewing, editable means changing results, and manageable means adding people, exporting, and deleting files. When exporting, I chose Summary Only Share, which outputs task statuses and risk warnings from the table as short summaries without sending out original chat screenshots. For clubs, this is more important than "Can AI write weekly reports?" The real time-saver lies in permission boundaries: which files cannot be read randomly, and which results cannot be sent randomly.

For daily maintenance, I set fixed actions. Every day after adding new files, go back to the workspace and click Rebuild Index so new PDFs are searchable. Every Friday night, clean up Sessions, archiving completed weekly reports to History Archive so old tasks don't pollute the context. I always keep Output to Separate Folder and Prohibit Overwriting Existing Files turned on. This setting seems basic, but it saves a lot of original material. My environment might not fit everyone. If you just want AI to write copy, WorkBuddy might feel heavy. But if you process documents, spreadsheets, screenshots, and meeting notes weekly, this workspace approach is steadier than copying files into a chat box.

Future office AI will likely split into two layers. Tools like Codex, Claude Code, and Cursor will continue competing on terminals, code repos, and automated testing. Tools like WorkBuddy will compete on file boundaries, permissions, collaboration, and auditability. What users ultimately care about is: Who can touch my files for this task? Who signs off on the results?