WorkBuddy in Practice: Turning LLM Landscape Maps into Reusable Local Tables

Just saw the "2026 Mainstream Large Model Architecture × Performance Comparison Panorama." It lists models like GPT-5.6Sol, Claude Fable 5.1, Kimi K2.5, along with parameters, context windows, API prices, etc. Many people's first reaction is to ask a chat model to summarize it. My judgment is that these charts update quickly, fields are messy, and the main hassle appears in weekly maintenance.

Panoramas are good for indexing, not for drawing direct conclusions. Running a round through WorkBuddy to uniformly extract screenshots, web copies, and PDF fragments into tables is more stable than asking the model every time. I almost switched away from it due to resource usage, but now I feel it's steadier for this kind of dirty work. Below is the workflow I organized after using WorkBuddy for four weeks. My environment is Windows, which may not apply to everyone.

After opening WorkBuddy, first create a new document/table organization task in the left-side task list, naming it 2026-09-03 LLM Panorama Organization. Beginners shouldn't select automated workflows right away; it's easy to get lost. When putting materials into the input area, I suggest starting with three items: a screenshot of the panorama, a copied text segment from a webpage, and a PDF description. The input area displays file names and types. Don't put materials in OneDrive sync directories; I got stuck once during export.

Then click Craft mode above the input box. Think of Craft mode as WorkBuddy's structured instruction entry point; it turns fields into table columns. Paste this instruction: Read all files in the input area, extract only explicitly appearing fields: model, vendor, release date, context, key architecture, API price, source, credibility. Write 'Undisclosed' if not disclosed; do not fill in based on common sense. Put unconfirmed content in a 'To Verify' column and output a separate 'To Verify' checklist.

Click Preview before clicking Run. Check field mapping in the preview; normally it generates columns like Model, Vendor, Context, To Verify, etc. If it splits Key Architecture into three columns, go back to the instructions and add: Keep Key Architecture as a single column, separated by semicolons. Testing shows this step is crucial; WorkBuddy hates field splitting in complex tables the most.

Ran it, and after a few minutes, the output area generated Model_Panorama_Table.md and To_Verify_Checklist.md. Unified table format is an advantage. Blurry screenshots cause missing rows, requiring manual patching—that's a disadvantage.

Once the task runs successfully, click Save as Template in the top-right corner of the task, checking 'Keep field mapping' and 'Confirm before each run.' From then on, weekly you just need to create a new task, select this template, and drop in new screenshots. A more efficient approach is to solidify a path that works once, avoiding reconfiguration every week. The core of this configuration is breaking it down into single operations: extract first, then merge, then export. Don't let it summarize, analyze, and write conclusions all at once.

For collaboration, I suggest dividing into three roles. Material entry personnel only put files into 00_Raw_Materials and cannot modify templates. Template maintainers are responsible for modifying instructions, adding fields, and checking run logs. Regular viewers have read-only access to 01_Output, preventing accidental clicks on 'Run' that overwrite results. In WorkBuddy, click Collaborate in the top-right corner of the task, add members, and assign upload, edit template, and read-only permissions respectively. If there's no clear owner in the group, the template will inevitably get messier with every change.

Daily ops are simple too: run once a week, move old tables from 01_Output to 99_Archive, and clear cache monthly. I use Resource Monitor to check WorkBuddy's usage during exports and notice CPU spikes briefly. If tables exceed dozens of rows, suggest letting it process in batches; add to the instruction: Process 20 rows at a time, merge at the end.

Approach	Pros	Cons
Ask chat model directly	Fast, good for quick looks	Inconsistent sources, prone to hallucination/filling gaps
Use WorkBuddy templates	Reusable, clear fields	Initial setup is troublesome, bad screenshots cause misses
Manual copy-paste	Most accurate	Slow, unsuitable for weekly maintenance

At least for me, organizing LLM panoramas is something I no longer want to force through a chat window.