Define the Goal
Set task boundaries and deliverables
Give organizational experiencethe ability to keep working.
F-ONEAn enterprise AI workforce is not a chatbot with a job title. It is an intelligent work system built around responsibilities, experience, processes, tools, permissions, and delivery standards.
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People Are the Most Mature Closed-Loop System
People continuously interact with the world through perception, decision, execution, feedback,and correction.
Starting from a goal, the AI workforce understands context, plans, invokes tools, executes work, validates results, requests human judgment at key points, and captures experience when the task ends.
The AI workforce loop contains six continuously coordinated steps.
Understand the Environment
Absorb context, rules, and constraints
Analyze and Decide
Break down the task and form an action plan
Use Tools
Connect systems and execute the task
Validate Results
Check quality, risk, and completeness
Capture Experience
Save outcomes and improve the next cycle
The Deliverable Is Completed Work, Not an Answer.
From understanding goals and gathering context to collaborative judgment, deliverable creation, follow-through, and learning, the AI workforce remains responsible for the entire work process.
01Understand the Goal
Read the goal, materials, boundaries, and delivery standards.
Goal, materials, boundaries
Delivery Standards
Track task progress
Coordinate critical decisions
Permissions
Historical Experience
Task Orchestration and Assignment
LEAD / WORKGROUPProduct GroupGoal breakdown · solution design
LEAD / WORKGROUPResearch GroupResearch gathering · issue discovery
LEAD / WORKGROUPGrowth GroupBusiness analysis · action recommendations
LEAD / WORKGROUPEngineering GroupData processing · deliverable creation
Consolidate OutcomesOUTCOME / Results and EvidenceComplete a Project Operating Review EXPERIENCE / Work Records · Skills and MemoryBuild the next task on accumulated experience
- Project operating review report
- Key issues and decision evidence
- Follow-up actions with clear owners
- Task traces and collaboration records
- Human corrections and actual outcomes
- Reusable decision and execution experience
Human Review and FeedbackReturn to enterprise context and organizational memory
The More It Works, the Better It Understands the Organization.
F-OneConnect role experience, enterprise context, autonomous execution, human–AI collaboration, and reusable capabilities so an AI worker can grow from a one-off executor into a sustainable organizational member.
02
Models Provide Intelligence; Memory Provides Tenure.
The AI workforce understands policies and remembers task progress, historical decisions, human corrections, and actual outcomes, so every new task builds on the organization's accumulated experience.
Seven-layer organizational memory, current layer: Conversation / Task Memory
Conversation / Task Memory
Remember current progress
Task ProgressCurrent Decisions
Personal Memory
Remember how to work better with this person
Communication HabitsFeedback Preferences
Project / Case Memory
Remember how events unfolded and were resolved
Historical DecisionsActual Outcomes
Team Memory
Remember how the team normally collaborates
Collaboration PatternsTeam Conventions
Department / Domain Memory
Remember how this domain handles work
Business RulesDomain Methods
Enterprise Memory
Remember how the enterprise consistently acts and decides
Organizational DecisionsExperience Assets
External Ecosystem / Regulatory Memory
Remember changes in the external environment
Industry ChangesRegulatory Requirements
03
Start With the Goal and Own the Deliverable.
The AI workforce understands the task, organizes the required steps, operates business systems, validates data, and delivers work that can be used directly. When information is insufficient or risk is high, it asks a domain expert to decide.
Generate a Quarterly Management Review Deck
04
Give Repetitive Execution to AI; Keep Critical Judgment With Experts.
At high-risk, low-confidence, or policy-conflict points, the AI workforce requests confirmation. Human acceptance, edits, and rejection become feedback for continuous improvement.
05
Turn One Expert Operation Into a Reusable Skill.
Record the actual operations, tool calls, and checks an expert performs. Select the structured operation record, send it to AI, extract the skill structure, confirm it, and archive it in the enterprise skill library.
RECORDING FILEStructured operation records, not video files
Let AI workers onboard, serve, and grow like formal employees—and be paused or offboarded when needed.
Enterprises can manage AI workers through probation, confirmation, promotion, and offboarding, gradually adjusting permissions and autonomy based on quality, efficiency, safety, and real performance.
Position Open
NO. ————
Role Description
Waiting for an AI worker…
00Materials
00Skills
00SOP
Lifecycle
- Onboard
- Probation
- Confirmed
- Promote
- Offboard
Kleiber Is Always Available
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Let People Focus on More Valuable Work.
The AI workforce takes on repetitive, tedious, and easily missed work while carrying human experience forward,so teams can spend more time on judgment, communication, and creation.
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