After a Month with WorkBuddy, I Advise Against 'All-in-One' Agents

After reading today's AI agent cross-comparison, my first reaction was caution. It states the selection logic directly: choose tools that can operate the environment where your work resides. Look at Sai for desktop automation, Gemini for the Google ecosystem, and ChatGPT, Manus, or Genspark for cloud tasks. Sounds reasonable. But when applied to daily office flows, course archiving, or reimbursement attachments, my testing suggests the thing to avoid most is agents that claim to "click everything for me."

This post records my counter-intuitive conclusion on selecting all-in-one agents.

I'd prefer to give WorkBuddy a judgment first: it's currently better suited for office document flows. WorkBuddy is better for managing files before generating results; don't hand over the entire computer.

Comparing item by item for office scenarios, the results are as follows:

Dimension	WorkBuddy	Sai	Gemini Workspace Agent
Main Strengths	Documents, spreadsheets, emails, PPTs, file organization, clear workspace boundaries	Operates desktop, GUI, and long multi-app chains like a human	Native actions flow smoothly in Gmail, Docs, Sheets, Drive
Local Files	Imports and processes within the workspace, strong sense of boundaries	Can access desktop, broader permissions, also more dangerous	News says it cannot control local file systems, relies mainly on cloud products
Suitable For	People frequently handling PDFs, screenshots, Excel, Word annotations	Those willing to configure approval rules, have budget, and need automation	Teams entirely within Google Workspace
Cost	I use it primarily as an office tool; haven't paid for a high-priced agent package just for doc organization	Starter approx $50/month	AI Pro approx $19.99/month
Risks	Too many skills can mix contexts, but file boundaries contain some of it	Misclicks, accidental deletions, accidental sends require strict approvals	Weak with external apps, falls apart outside Google

This table compares fit for office scenarios. If the goal is simply organizing batches of PDFs, screenshots, Excel sheets, Word annotations, and Feishu exports into reviewable results, WorkBuddy is more suitable than all-in-one agents like Sai or Gemini. If the goal is clicking across multiple desktop software and running long processes, Sai is more aggressive, acting more like an automation system. Gemini Workspace Agent thrives on the ecosystem; it's valuable if the whole team is in Google, but it may not handle a pile of Feishu chats, WeChat screenshots, or netdisk PDFs well.

Choose tools based on the platform where the work happens, not just based on the model.

I agree with this sentence. I'd add half a phrase: choose tools based on the error cost you can bear. In office scenarios, boundaries matter more than capabilities.

What makes me appreciate WorkBuddy as an office agent is that it knows what it shouldn't touch.

Over the past month, I put WorkBuddy, Feishu, Excel, WPS AI, Qianwen Office, Copilot, Perplexity, Gemini 3.1 Pro, Cursor, Claude Code, Trae, and Grok into my daily workflow to test them; Codex has been in use for a few days. I care more about who keeps the error cost where.

All-in-one agents are tempting—they click desktops, cross apps, and send notifications automatically. The real trouble in office flows is that they might read the wrong file, edit the wrong sheet, treat notes as conclusions, or drafts as finals. WorkBuddy's approach locks many capabilities outside the door.

I did a comparison with a batch of materials: Feishu-exported PDFs, chat screenshots, Excel task lists, Word annotations, and code READMEs. The first time, I was lazy, pulled very long context, and enabled file organization, code summarization, and meeting minutes skills. Result: it mixed the "notes" and "person in charge" columns together, and the PPT outline looked like a product launch. Later I admitted the problem was treating it like a wishing well.

After breaking it down, I trust it more to first create a fact list, then extract persons in charge, deadlines, and risk points, and finally write the body text based on the table. It produces a draft in about twenty minutes, saving significant effort compared to manual merging. This experience made me realize that in office scenarios, the first thing agents should learn is not to act recklessly.

WorkBuddy's usefulness mainly manifests in boundary management. Many tools can provide pretty talk. WorkBuddy's value lies in putting scattered office materials into a manageable boundary, defining which files can be read and which outputs can be exported. This point is very useful for material archiving, reimbursement attachments, and meeting material organization.

Don't hide its flaws either. When merging multiple files, complex tables with merged cells, handwritten fields, and notes in screenshots still suffer from recognition misses. Its PPT aesthetics lean towards engineering; content structure is okay, but don't expect much from layout. Cross-tool automation is weak; it can't log into a netdisk for you or click send in WeChat. It's more like an office document assistant, still far from being an agent that works for you.

Looking forward, what WorkBuddy needs to supplement most is auditability.

Today's news trends are clear: agents are moving from chatting to executing. Sai wants to operate the full desktop, Gemini wants to expand multi-step web tasks, and Genspark wants to build an integrated workspace. Sounds powerful, but when office scenarios land on individuals and small teams, the primary need is: what happens if it clicks the wrong thing?

If WorkBuddy continues moving toward the agent direction, I don't want it to first learn to auto-send Feishu messages or auto-edit netdisks. I'd rather it supplement auditability: which files were read each time, which fields came from which PDF, which conclusions came from model inference vs. original text, and whether there was manual confirmation before export. Permission logs are worth more than flashy buttons.

Back to daily projects, what really blocks people are documents, spreadsheets, chat histories, and permissions. Using WorkBuddy for a month didn't reduce how much I wrote, but it saved me from carrying the blame for "who changed this file."

This post only records WorkBuddy's boundaries, organization, generation, and export in the narrow scenario of office documents. If archiving, reimbursements, and project docs are handed to agents, I'll first check if it can manage file boundaries.