Course Structure
 
Module 1: Sales Intelligence Assistant MVP
 
█ Use Cases
 
 
 
 
Cold outreach, pre-sales and post-sales follow-up, customer success management, and long-cycle contract collaboration
 
 
 
 
 
█ Cracking the Three Time Black Holes × AI in Practice
 
 
 
Black hole 1: Visit logs and weekly reports eat up your prime selling time
 
 
AI approach
 
- AI automatically generates visit logs and summaries and converts them directly into your company's required format
 
- Breaks down progress and to-do lists so information doesn't get buried
 
- Instantly converts deadlines and follow-up items into calendar reminders
 
 
 
Black hole 2: Handling quotes, proposals, and contract documents feels as tedious as copying by hand
 
 
AI approach
 
- AI speeds up the digitization of paper documents and auto-formats data
 
- Compares differences across multiple versions to avoid errors and omissions
 
- One-click generation of standardized templates with quick command-based application
 
 
 
Black hole 3: Customer information is scattered across platforms, making the sales path feel like a jigsaw puzzle
 
 
AI approach
 
- Make good use of the Google / Microsoft ecosystems combined with AI Q&A for quick retrieval
 
- Establish a real-time sync mechanism to break the cross-department "everyone tells a different story" dilemma
 
 
 
█ Benefits
 
1. Build a prototype of your own "AI sales-department brain" and establish integrated logic for records / fields / templates
 
2. Reshape the nodes of your sales SOP and observe AI automation cases that optimize path efficiency
 
 
 
Module 2: Customer-Service Butler MVP
 
█ Use Cases
 
 
 
Replying to community reviews, FAQ management, customer sentiment analysis, cross-channel support, and post-sales follow-up
 
 
 
 
█ Cracking the Three Time Black Holes × How AI Is Applied
 
 
 
Black hole 1: Repeatedly answering the same questions drains your energy
 
 
AI approach
 
- Automatically tag and categorize common questions to reduce the cost of manual searching
- AI automatically generates FAQs for the public or scripted support replies, ensuring consistency and timeliness
 
- Understand the need for a sync-update mechanism in the support "brain" so answers are always the latest version
 
 
 
Black hole 2: Transcribing and retrieving customer conversation logs across systems and interfaces is fragmented
 
 
AI approach
 
- AI generates conversation logs and summaries in real time and automatically classifies them into the system
 
- Break conversations into a "to-do list" to avoid omissions
 
- Automatically notify the relevant department to enable cross-department handoff
 
 
 
Black hole 3: Sentiment judgment relies entirely on experience, and crisis handling is always a step behind
 
 
AI approach
 
- AI tags sentiment to identify trends in customer emotion
 
- Build a "customer sentiment map" to help support staff adjust their messaging strategy
 
- Early warning for abnormal situations, matching the right handler to the case
 
 
 
█ Benefits
 
1. Build a prototype of an "AI customer-service brain" that raises customer satisfaction, lowers churn, and shifts the support team from passive support to proactive care
 
2. Build the applied mindset for AI automation of knowledge, records, and sentiment analysis, with case study observation
 
 
 
Module 3: High-Efficiency HR Partner MVP
 
█ Use Cases
 
 
 
Résumé screening, interview records, training planning, new-hire onboarding, and employee data analysis
 
 
 
 
█ Cracking the Three Time Black Holes × How AI Is Applied
 
 
 
Black hole 1: Résumé screening and interview scheduling rely on heavy manual work and are inefficient
 
 
AI approach
 
- Automatic preliminary résumé screening and keyword matching
- Add a "candidate summary" to help managers make quick decisions
- Fast automatic matching for calendar bookings
- AI phone-interview invitations
 
Black hole 2: Interview records are scattered and emotional details rely on memory
 
AI approach
 
- AI automatically generates interview transcripts and key-point summaries
- Add sentiment analysis to help assess a candidate's traits
- Instantly convert to the recruiting system's transcription format to avoid tedious work
 
Black hole 3: Training and performance data are scattered and hard to track
 
AI approach
 
- AI integrates learning records and generates training-progress reports
- Automatically map performance data to uncover potential skill and learning gaps
- Generate draft presentations for the annual review and training plan
 
 
 
█ Benefits
 
1. Build a prototype of an "AI HR-department brain" that improves recruiting efficiency and hiring-decision quality while reducing manual workload
2. Build the applied mindset for AI automation of screening, records, analysis, and outreach, with case study observation
 
 
 
Module 4: Precision Finance MVP
 
█ Use Cases
 
 
 
Invoice processing, bookkeeping tracking, expense auditing, monthly/quarterly closing reports, and financial analysis
 
 
 
 
 
█ Cracking the Three Time Black Holes × How AI Is Applied
 
 
 
Black hole 1: Invoices and receipts pile up, with a high manual error rate
 
 
AI approach
 
- AI OCR automatically extracts invoice information for fast classification and entry
- Simplify the reimbursement process and reduce manual-entry errors
 
 
 
Black hole 2: Reconciliation and tracking of receivables/payables is time-consuming
 
 
AI approach
 
- AI automatically generates receivable/payable reconciliation lists and flags overdue payments
- Integrate accounting data from multiple sources
 
 
 
Black hole 3: Compiling monthly/quarterly closing reports eats up most of your time
 
 
AI approach
 
- AI automatically converts formats and summarizes to quickly generate a draft financial report
- Present key financial figures with visual charts to support decision-making discussions
- Flag abnormal items to aid precise review
 
 
 
█ Benefits
 
1. Build a prototype of an "AI finance-department brain" that improves report-generation efficiency and sharpens risk control
2. Build the applied mindset for AI automation of extraction, comparison, and insight, with case study observation
 
 
 
Module 5: Business Planning and Decision Collaboration MVP
 
█ Use Cases
 
 
 
Market-data collection, competitor analysis, strategy-report generation, strategic-intelligence dashboard generation, breaking through project roadblocks, and pitch presentations
 
 
 
 
█ Cracking the Three Time Black Holes × How AI Is Applied
 
 
 
Black hole 1: Market data and reports are scattered, and gathering information is like searching for a needle in a haystack
 
 
AI approach
 
- AI collects from across the web and automatically generates a market-summary report
- Filters out abnormal data to help assess market turning points
 
 
 
Black hole 2: Competitive analysis and strategy-report production are time-consuming
 
 
- AI automatically compares competitors' strengths and weaknesses and generates a SWOT draft
- Automatically derives multi-perspective options and conclusions to support strategy development and meeting decisions
- Outputs a "one-page intelligence dashboard" to support strategy
 
Visualization of strategy derivation
 
 
 
Black hole 3: Project roadblocks and stakeholder coordination progress lacks transparency
 
 
- AI analyzes project bottlenecks and proposes viable solutions
 
- Automatically generates a "stakeholder cause-and-effect" map and key-message summaries
 
- Generates a visual draft presentation
 
 
 
█ Benefits
 
1. Build a prototype of an "AI business-planning brain" that becomes a common language for strategy discussions, improves the timeliness of market insight and decision support, and lets planners focus on innovation and cross-department collaboration
 
2. Build an AI-assisted thinking framework that turns market collection, competitive analysis, strategic proposals, and decision methods into knowledge, with case study observation
 
 
 
Module 5: Project Team Management MVP
 
█ Use Cases
 
 
 
Cross-department project collaboration, OKR/KPI tracking, project-progress transparency, and internal knowledge sharing
 
 
 
 
█ Cracking the Three Time Black Holes × How AI Is Applied
 
 
 
Black hole 1: Lots of meetings but thin results, with information hard to retain
 
 
AI approach
- AI automatically generates meeting notes and decision summaries
- Extracts action items and assigns them to the team's task system
 
 
 
Black hole 2: Project-progress tracking lacks transparency, with breakpoints in cross-department communication
 
 
AI approach
 
- AI automatically consolidates project updates and generates a "one-page progress board"
- Automatically compares plan vs. actual progress and flags gaps
- Supports cross-tool integration (such as Slack, Teams, and Notion) so the team stays aligned on the same view
 
 
 
Black hole 3: Compiling KPI/OKR statistics is time-consuming, and data is hard to unify
 
 
AI approach
 
1. AI integrates the data and quickly generates a KPI/OKR overview
2. Provides early warnings for abnormal data so problems aren't discovered too late
 
 
 
█ Benefits
 
1. Build a prototype of an "AI team-agent PM" that supports cross-department collaboration, improves project transparency and execution efficiency, and reduces redundant communication costs
 
2. Build the AI collaboration mindset for tracking multiple projects and groups across the enterprise, with case study observation
 
 
 
Overall Benefits
 
✅ Build a systematic blueprint for an enterprise-exclusive “AI Department Brain”
✅ Turn tedious tasks into automated workflows and unlock the value of your workforce
✅ Strengthen cross-department collaboration and build the core capability for intelligent operations