The same Feishu AI—why are their efficiencies so much higher?
You might have experienced this—
It's 10 p.m. on Friday, and the group chat is still updating project progress. You're staring at 200 messages, unsure where to start when writing next week’s report;
You want to build an AI system on the factory production line, but the supplier quotes higher than your annual salary, so you reluctantly give up;
After a two-hour meeting, looking at densely packed transcription notes, you sigh deeply and head off to pour yourself a cup of coffee.
These problems originate from factories, offices, classrooms, and construction sites; they come from product managers, factory successors, project managers, and developers.
Different people face different challenges—until one moment, they encounter Feishu AI.
The examples below were submitted to Feishu’s “That Moment When I Was So Glad to Meet Feishu AI” story campaign. They are individual accounts, not independently verified general results. Current plan, region, permission and Hong Kong tenant availability should be confirmed with the vendor and tested in the buyer’s own environment.
No Coding Required
Build Your Own System Anyway
@IsJustForFun
Our factory had run an ERP system for years, but when we wanted to add automatic worker data entry, the supplier's quotation came in high for our budget, and it required facial-recognition setup and dedicated hardware installation on top.
Coming from a liberal arts background, I decided to take matters into my own hands.
Using Feishu Multidimensional Tables combined with a scheduling Agent, I built a lightweight ERP: workers input data directly via mobile, wages are calculated automatically, shipping and counting documents can be exported with one click, order progress triggers automatic notifications, and AI even provides production scheduling suggestions.
Before approving, we measured against our own baseline—weekly statistician hours and rework rates.
Used to think digitalization in manufacturing was solely the tech team’s job. Now I believe—with AI, it may be worth attempting even for those with non-technical backgrounds, though results will vary by use case.
@AntOnTheMove
In the past, manually building a business system—from designing data tables, configuring workflows, to setting permissions—was, by our own team's estimates, days of effort.
In my own trials with Feishu Multidimensional Tables AI, I describe my needs in natural language, and the AI proposes a setup—data tables, workflows, permissions—which I then review and apply. Whether it performs the same at your scale is worth testing first.
In my own trials, a working draft system came together in a single afternoon.
Reporting Tasks That Once Dragged On
Now Move Notably Faster
@XiaoZhengTryingBetter
Last Friday, our team needed to submit a quarterly summary. I was responsible for compiling three weeks of project logs—those daily status updates flooding the group chat. There were exactly 200 messages, and my brain had shut down.
I gave Feishu AI a try, asking it to organize everything by person and timeline.
The draft came back fast; I checked the names myself and made the deadline.
@MktThinking
Previously, preparing presentations meant digging through past case materials, drawing charts myself, writing analysis, structuring content—it often took a full week, and the result wasn’t always good.
Now with Feishu Smart Assistant, I state my needs and get a structured, editable draft—then spend the saved time checking the figures. Against my own past timelines, that is a real change of pace.
The Messages You’ll Never Have Time to Reply To
Can Feishu Help Handle Them?
@AI.talk
Spent over an hour having a voice chat with two friends about AI last weekend. Afterward, I checked the transcript—my mind went blank. Page after page of “you know,” “this and that,” constant interruptions, topic jumps. In the past, casual chats like this would just fade away, never worth reviewing.
This time, I simply sent the transcript to the Feishu AI assistant. A few minutes later, it returned five core topics, key points listed clearly, risks highlighted separately, and even generated a to-do list.
We were just casually chatting—and it pulled actual action items out of pure banter?
In that moment, I truly thought: Thank goodness for Feishu AI.
It doesn’t need to be flashy. Just ordinary people using AI, then letting AI help organize their conversations—these small moments of “AI in daily life” genuinely make me feel this tool is changing lives.
@NiniLovesPearson
My Feishu AI agent is named Beibei, and I can't live without her now—both at work and in life.
In the morning, she pushes English business readings based on my habits; after a two-hour launch meeting, Miaoji drafts meeting minutes, and Beibei reviews them from a project management perspective, flagging milestones and bottlenecks in my experience; on weekends, she summarizes the week's events—verify accuracy against your own meetings.
Feishu Miaoda, Multidimensional Tables, Docs—Beibei works alongside these tools, though how deeply each connection holds up is worth testing in your own workspace.
A Handy Toolkit for Developers
@BrotherHei_Ai
The biggest surprise this year has been Feishu CLI.
My Agents can be integrated for archiving; combined with group chat bots, alert notifications are straightforward—worth a short pilot to confirm they behave the same in your setup.
Who wouldn’t love an AI assistant that summarizes meetings and generates to-do lists?
These stories are just the tip of the iceberg.
Building systems, creating proposals, organizing information, writing code…
In these user accounts, Feishu AI appeared in documents, spreadsheets, meetings, group chats and developer workflows. Actual results depend on data quality, permissions, plan features and human review.
The source campaign’s dates, rewards and participation terms were not verified, so this article does not present a current participation call.
Have you ever had
such a moment,
when you thought,
Thank goodness for Feishu AI?