From “Information Container” to “Action Hub”: A Paradigm Shift in Workplace Tools
Over the past decade, office software has visibly grown “heavier.” Real-time messaging, documents, calendars, approvals, video conferencing—features keep piling up, and systems grow increasingly bloated.
Yet as systems grow heavier, people grow more exhausted. The reason is simple: the “glue” connecting these siloed modules remains human.
You schedule a meeting in your calendar, then switch to chat to send a notification, then open a document to draft the agenda. After the meeting wraps up, you manually assign each follow-up task to colleagues. Tools remain mere containers for information; people become the process’s搬运 workers.
Over the past two years, the AI wave has swept across workplace scenarios, easily giving rise to a misconception in the industry: simply adding a chat interface—capable of drafting summaries or replying to emails—is enough to qualify as AI-powered work. But that’s still far off the mark.
True AI-powered work shouldn’t just be a clever chatbox—it must evolve into an action terminal equipped with “hands.”
This is precisely the paradigm shift Lark is actively exploring. It doesn’t aim merely to stitch together real-time messaging, multi-dimensional tables, documents, and calendars into a Frankenstein-like amalgamation. When a system can understand your intent, it ceases to be a passive blackboard for writing—it becomes an active personal assistant.
You simply state your goal; the system itself navigates seamlessly across foundational capabilities, smoothing out those tedious, cross-module workflows on your behalf.
From passive information hosting to active execution, workplace software has finally begun growing its own “hands.”
Breaking Down Module Silos: Enabling AI to Truly “Run Errands” Within Business Flows
In recent years, many of us have used too many AI tools that “only talk.”
Ask it about industry trends, and it churns out a thousand-word essay with flair—but ask it to “share the conclusions with the project team,” and it shrugs helplessly, citing inability to access internal systems. Capable only of answering questions—not performing tasks—this remains AI’s greatest weakness to date.
At its core, work is never about Q&A—it’s about flow. Information must continuously shuttle among people, documents, schedules, and tasks. If AI fails to break down module silos, it will forever remain a chat widget dangling at the system’s periphery.
Lark’s solution leverages an open ecosystem to give AI genuine hands and feet.
By integrating various third-party intelligent work agents, Lark weaves AI capabilities deep into the capillaries of business flows.
For instance, in a project group where discussions flood daily, you can invoke an integrated third-party intelligent work agent directly within real-time messaging, rapidly synthesize information based on context, and link to multi-dimensional tables for archiving—the action path is initiated by the user, while the system provides capability support.
Or consider just wrapping up a video meeting: you can invoke an ecosystem-integrated third-party intelligent work agent to help distill key takeaways—and instantly connect to Lark Calendar and Approval features to swiftly create follow-up items. People drive the rhythm; the system delivers cross-platform collaboration support.
It’s no longer a “navigator” forcing you to hop repeatedly between apps—it’s now the “delivery person” running the full errand for you.
In such scenarios, real-time messaging, documents, calendars, multi-dimensional tables, and approvals cease to be fragmented silos. Instead, they become digital organs that AI can flexibly call upon. The system evolves from a static display board into a dynamic action hub. Offload cumbersome workflows—and only then do you truly free your hands for creation.
The Screen Is Context: Seamless, WYSIWYG Interaction
Using AI used to make you feel like an awkward搬运 worker.
Copy a long text block, switch to the chat window, paste, wait for output; for complex formatting or data, you’d even need to screenshot and upload. These constant switches and interruptions relegated AI to an “add-on” external to your workflow—never fully integrating into daily routines.
In Lark, however, that layer of interaction has been punctured.
When reading a lengthy report in a Lark document—or analyzing data in a multi-dimensional table—you can instantly summon an integrated third-party intelligent work agent and pose questions or launch tasks anchored to the content you’re currently viewing—context is actively defined by the user, enabling sharper, more focused system responses.
No need to manually select text or switch applications. Summon an AI assistant from the ecosystem, and it can directly “understand” the page you’re looking at.
You might casually ask: “What implementation risks appear in Section 3 of this report?” Or: “Help me identify common root causes behind delayed progress in this multi-dimensional table.”
AI no longer requires manual “feeding” of data—it has grown eyes capable of perceiving its environment.
WYSIWYG means those tedious operational paths are obsolete.
When the screen itself becomes the largest input field, human-system dialogue finally returns to its most natural, intuitive form.
A System with “Memory” Deserves to Be Called a Personal Assistant
Every time you activate AI, it feels like onboarding a new intern with amnesia—this is likely a shared pain point for many professionals.
You must repeatedly explain project background, reiterate your boss’s aesthetic preferences—even demonstrate formatting conventions for reports step-by-step. An AI without memory remains merely a fast typist, never evolving into a collaborator who truly understands you.
A true personal assistant needs “long-term memory.”
Within the Lark ecosystem, intelligent work agents are quietly gaining memory. They’re no longer disposable chat windows—instead, they deeply interweave with your everyday Lark documents, calendars, and real-time messages. Of course, this occurs strictly within rigorously defined authorization and privacy boundaries.
Once authorized, integrated third-party intelligent work agents can leverage your Lark documents, calendars, real-time messages, and other sources to assist in organizing content, reusing standard structures, and boosting efficiency for repetitive tasks.
Come Friday afternoon, you won’t need to cobble together those long, unwieldy prompts.
Just say offhand: “Update this week’s industry briefing using last week’s format.”
It will precisely retrieve memorized templates and data sources—and deliver the finished work immediately.
Speaking less repetitively marks the first sign that AI truly understands you.
Once the system gains memory, human-machine interaction shifts from “instruction-driven” to “intuitive collaboration.” It no longer forces you to rebuild context from scratch every time—instead, it steps in directly, informed by its understanding of your workflow.
Only a system that remembers you can truly grow the brain needed to assist your thinking.
Redefining Human-Machine Division of Labor: Returning Time to “Creation”
Many people fall into a trap when measuring the value of AI-powered work: calculating how many words it generates.
But real transformation isn’t driven by volume—it’s measured by how many tedious execution paths it eliminates.
In the past, we hopped endlessly between real-time messaging, documents, calendars, and approvals—a literal “human interface” stitching modules together. Now, those mechanical, cross-system errands are being quietly taken over.
Within this new collaborative paradigm, the boundary between human and machine roles grows strikingly clear.
Lark provides a robust collaboration foundation—making information flow, schedule alignment, and data accumulation seamless infrastructure; meanwhile, third-party intelligent work agents integrated into the ecosystem become concrete actors, moving through business flows to get things done.
The system supplies capabilities; agents execute actions; humans focus solely on defining goals.
You no longer stare at progress bars waiting for results—instead, you redirect mental energy away from “how to do it,” and refocus on “what to do” and “why to do it.”
When workplace software grows “hands” and “memory,” it ceases to be a passive tool awaiting your keystrokes—and transforms into an action hub that knows you, runs for you.
Delegate the trivial to the system; return time to creation.
That may well be the ultimate purpose of collaboration tools’ evolution: letting machines handle the dirty, labor-intensive work they excel at—so humans can reclaim their rightful place at the heart of true creation.