WorkBuddy's real efficiency isn't autonomous execution, but templates keeping quiet

What really saves the hassle with WorkBuddy is shutting up the template.

I increasingly feel that the biggest pitfall for office Agents is being too smart. I came across an article on a 2026 AI tools guide mentioning that current AIs can autonomously call tools, plan steps, and execute tasks over long periods. Sounds impressive. After using WorkBuddy for about a month, my conclusion is quite plain: the key to stable operation is preventing it from planning wildly.

Last Wednesday, I asked WorkBuddy to merge a bunch of expense reimbursement xlsx files into a weekly summary. The first time, I just said, "Read all reimbursement sheets, merge by date, amount, and category, and output a table." It did exactly that, but also casually scanned contracts, resumes, and screenshots into the context. Result: three different date formats, amounts mixing "yuan" text with pure numbers, and categories where it invented its own like "dining," "eating," and "travel." Usable, but unnecessary. Later I realized the problem was that I gave it boundaries that were too loose.

Now my approach is rigid. Open WorkBuddy, find the "Tasks" entry on the left, click "New Template," and select "Table Processing" in the popup. Name it "Weekly Expense Summary v2." In the field editor, allow only five fields: Date, Amount, Category, Source File, and Notes. Fix the date format as YYYY-MM-DD, require Amount to be numeric, and limit Category to only Travel, Dining, Office, and Other. Select xlsx for output. Beginners might find this step tedious, but once the template is fixed, you don't need to re-explain fields every day. Think of the template as pre-hardcoded fields and rules, preventing it from improvising on the spot.

Before running, I place the files to be summarized separately into the workbuddy_inbox folder, not the entire Downloads folder. This folder contains only the current week's reimbursement sheets—no contracts, screenshots, or chat logs. Back in the WorkBuddy task page, select the template, choose "Read Only" for the data scope (meaning it can view but not modify original files), set the output path to workbuddy_out, and hit Run. The log on the right shows how many files were read and generates summary.xlsx. My tests show results in about ten minutes. Not bad.

This step is crucial. I previously fell into a trap by giving the Agent a large directory directly; it read too much context, became more confident the more it read, and ended up looking like it was holding a meeting. Later, when I narrowed the scope to just the current week's reimbursement sheets, the results became much more stable.

For collaboration, I haven't complicated things either. Colleagues drop files into the inbox subdirectory, and my WorkBuddy task only reads inbox/2026-09, not personal desktops. Finance views the result tables with View-only permissions, no Edit access. I keep one copy of the original files and save another copy of the summary results. In Feishu Docs, I put a one-page explanation clearly listing template fields and submission formats; only I have edit permissions, others are view-only. This prevents accidental operations. Backend systems fear unlogged online configurations most, and office Agents are the same.

Daily maintenance is also fixed. I run it once every Friday afternoon. Before running, I check file naming: YYYYMMDD_Reimbursement_Name.xlsx. If naming is non-compliant, WorkBuddy won't guess; it flags anomalies according to template rules. Anomalous fields get red notes, which I fix manually. Each time the template changes, I bump the version number; if v2 fails, I roll back to v1. If the total amounts don't match, I use Excel Pivot Tables or VLOOKUP for spot checks. VLOOKUP is a lookup function in spreadsheets that finds values in another table based on a column, similar to a backend join. VLOOKUP is an old function, sufficient to judge whether WorkBuddy merged fields incorrectly.

I think the trend is the same. General-purpose models will certainly get stronger; ChatGPT, Gemini, and Claude can all chat, plan, and call tools. But in office scenarios, what truly lands is clear boundaries. Agent autonomy suits exploration, not reimbursement. Exploration can be wrong; finance cannot.

So if you're using WorkBuddy for the first time, don't ask if it can think through everything for you right away. First, create a template, fix the fields, restrict the directory, give read-only permissions, and run it for a week. Once it produces stable tables, then talk about automation. No need to overcomplicate. If you can write two fewer lines of validation code, do so.