Roles That Only Execute Rules Are Quietly Becoming Unstable
The prediction that AI will replace repetitive labor is gradually becoming reality.
If any of you readers work as project assistants or specialize in data aggregation, you’ve likely sensed a subtle chill recently.
Over the past few years leading an editing team, I’ve witnessed countless rises and falls among entry-level roles. When training newcomers back then, the first lesson was always: fill out templates, extract key meeting takeaways, and manually track progress. These tasks were, at their core, about “executing rules.” As long as the rules were rigidly defined, people could function like precision gears—fitting seamlessly into place.
But now, this entire approach is beginning to grind to a halt.
While you’re still transcribing meeting minutes word-for-word from playback, other teams have already integrated third-party AI assistants. The moment a video meeting ends, their intelligent work agents have already distilled core conclusions and action items with crystal clarity. While you’re shouting reminders across multiple group chats to chase progress, Lark’s calendar and instant messaging features have long since automated collaboration flows flawlessly.
The barrier to executing rules is being lowered infinitely by technology. Machines never tire, never miss messages in group chats, and certainly won’t derail an entire project because of a single misfilled cell. Roles that rely solely on rote execution—and lack intuitive business awareness—are bound to become unstable, sooner rather than later.
Yet this isn’t the end of the world.
After thoroughly experimenting with various AI-powered office tools, I’ve reached a firm conclusion: AI takes over “execution,” while humans must retreat to “decision-making.” Judging whether a project harbors hidden pitfalls, deciding where to allocate resources—these judgment calls rooted in business intuition are beyond machines’ reach.
Systems handle process execution; humans evaluate quality and outcomes.
As repetitive, labor-intensive tasks are taken over by Lark and its ecosystem of intelligent tools, human judgment is rapidly transforming into an increasingly valuable and scarce asset.
When Meeting Minutes and Progress Tracking No Longer Depend on Manual Handoffs
What do teams dread most after wrapping up a meeting?
When I led editing teams, my biggest post-meeting fear was the chaotic aftermath of review sessions. A two-hour topic brainstorming session would leave everyone fired up—but afterward, staring at messy, incomplete minutes would trigger collective despair. Who owned which thread? When was the rough cut due? Everything relied entirely on manual note-taking, manual distribution, and manual follow-ups.
This “manual handoff” burns through hidden management costs.
My habits have changed. Now, when my team holds video meetings on Lark, I simply activate a third-party AI assistant from the ecosystem. The moment the meeting concludes, core conclusions appear quietly and neatly inside a Lark Doc.
No need to replay recordings line-by-line—or hammer away at your keyboard until sparks fly.
With this ready-made document in hand, I instantly convert key delivery milestones into Lark Calendar events. For details requiring deep focus, I directly assign action items via Lark Instant Message to the relevant editor.
The whole sequence flows smoothly—no gaps, no friction.
This is the tangible impact of generational advancement in office infrastructure. You don’t need to understand how AI recognizes speech or interprets semantics—only that it can consolidate fragmented meeting information for you. And Lark’s foundational capabilities—Docs, Calendar, and Instant Message—function like reliable, standardized power sockets, seamlessly accepting and integrating these distilled insights.
Progress tracking is no longer a daily ritual of anxious @-mentions across group chats—it becomes a clearly visible timeline within the system.
When meeting minutes and progress tracking no longer depend on manual handoffs, what we save goes far beyond time—it’s mental energy—the exhausting fatigue caused by constant entanglement in trivial procedural loops.
Hand processes over to systems; reserve your energy for the content itself. This is what team collaboration should truly look like.
Extracting a Clear Data Skeleton from Complex Business Flows
If meeting minutes and progress tracking represent the shallow waters of collaboration, then handling disorganized business feedback plunges us straight into the deep end.
In earlier user research projects, incoming feedback was nothing short of catastrophic—hundreds of lengthy, emotionally charged, typo-ridden, and logically incoherent rants.
How did we tackle this before? We’d assign several people to manually tag and categorize each piece of feedback, one by one.
This is analogous to motion capture in film production. During motion capture, you strip away facial features, clothing, and background—retaining only the purest skeletal motion.
Processing business data works the same way. You must filter out users’ emotions and superfluous commentary—extracting only the core business metrics.
Now, this grueling “skeleton extraction” work can be delegated to machines.
I experimented with connecting a third-party intelligent work agent to Lark’s Multi-dimensional Table. Through AI-powered filtering, those scattered unstructured inputs are cleaned and neatly slotted into structured fields within the table.
For instance, when a user complains “the feature is too hard to find,” the agent automatically tags it as “deep interaction hierarchy”; complaints like “loading freezes” get categorized under “performance issues.”
Throughout this process, Lark’s Multi-dimensional Table demonstrates exceptional capacity as a data foundation. It functions like a tightly woven net—steadily catching and holding every distilled data skeleton.
You don’t need to concern yourself with the intricate logic behind the cleaning steps.
Once dirty data is filtered into clean, actionable metrics, the underlying structure of the business flow becomes unmistakably clear.
Humans shouldn’t mine for gold in information swamps—they should stand safely on shore, examining the refined gold they’ve extracted. This isn’t just about efficiency gains; it’s a fundamental shift in where our work focus lies.
Systems Handle Process Execution; Humans Evaluate Quality and Outcomes
Once Lark’s Multi-dimensional Table, Calendar, and Instant Messaging are seamlessly connected via third-party AI assistants, I noticed an intriguing phenomenon.
Team members who previously served as “process accelerators” suddenly found themselves with spare time.
Before, project managers spent every day individually @-mentioning people in group chats to chase status updates, manually updating statuses in spreadsheets, and repeatedly rescheduling meetings on calendars.
Now, these basic coordination tasks run automatically—following pre-defined logic built into the system.
That doesn’t mean humans have nothing left to do. Quite the opposite—the invisible expectations placed upon them have risen significantly.
During team retrospectives, we arrived at this conclusion: systems tell you “what happened,” but only humans can decide “what to do next.”
For example, if a critical metric suddenly turns red in the Multi-dimensional Table, the intelligent work agent can instantly post an alert message in the group chat.
But does that alert merely warrant a verbal reminder—or does it demand an immediate video call for an in-depth retrospective?
Or consider another case: the Calendar shows a delay in delivering a key milestone, and the system automatically logs the deviation.
Yet determining whether this delay warrants escalation to leadership still requires human judgment—grounded in holistic understanding of the business context.
The more automated the tools become, the scarcer those inherently unquantifiable qualities grow.
What’s unquantifiable? Your intuitive grasp of business temperature, your aesthetic sense of team collaboration rhythm, and your instinctive ability to make decisive calls amid complex situations.
Executing rules can be exhaustively codified—but making decisions remains fundamentally dependent on human cognition.
As Lark and its ecosystem of AI-powered office tools fully assume mechanical, repetitive workflows, we finally gain the bandwidth to return to the essence of work.
To observe deeply, to decide thoughtfully, to shoulder responsibility for those decisions.
In this era, computing power grows steadily cheaper—but human judgment grows ever more valuable.
AI Has Become the New Generation of Office Infrastructure
When the film industry transitioned from analog film to digital, what truly shifted wasn’t camera technology—it was the entire operational logic of film crews.
Today, watching my team collaborate seamlessly between Lark and various third-party AI assistants evokes a similar sense of disorientation.
Many worry AI will steal jobs from execution-level staff. But after months of hands-on experimentation with my team, my strongest impression is this: AI isn’t replacing people—it’s reconstructing our production relationships.
Lark provides foundational, widely understood collaboration capabilities—Instant Messaging, Docs, Multi-dimensional Tables, Calendar, Video Meetings, and Approvals. Meanwhile, intelligent work agents from the ecosystem function like tireless production assistants—firmly embedded atop this foundation.
Information flows through Docs, progress is tracked in Multi-dimensional Tables, and decisions are finalized during Video Meetings.
AI doesn’t aim to replace humans—it aims to take over those mechanical, unavoidable actions we “have to do.”
When systems handle process execution, humans finally gain the freedom to step back and evaluate quality and outcomes.
At its core, this represents a paradigm shift in production methodology.
Just as tape recorders and movie cameras once redefined the boundaries of cinematic creation, today’s integration of AI and collaborative tools is emerging as the new generation of office infrastructure.
It lifts teams out of the mire of tedious procedural work—and propels them toward a new coordinate system—one that places greater value on insight, aesthetic sensibility, and decisive judgment.
Don’t resist the trend—start experimenting.
A new era is unfolding, slowly but surely.
And new opportunities lie just around the corner.