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Duration 7 hours
Course Outline
Module 1: Introduction to Manus for Finance Professionals
- Understanding general AI agents: the cycle of planning, acting, and delivering versus simple answering
- Comparing Chat mode and Agent mode: identifying appropriate use cases
- Overview of credit mechanics, typical task costs, and shared team credit pools
- Interface tour: exploring tasks, Projects, files, connectors, Skills, and Automations
- Positioning Manus within finance, forensic, and corporate finance workflows, and identifying its limitations
- Exercise: Executing a small task in both modes to compare outcomes and credit consumption
Module 2: Briefing, Steering, and Reviewing
- Crafting actionable briefs: defining goals, inputs, output formats, and constraints
- Monitoring agent activity, intervening mid-task, and managing browser and login interactions
- Output review: verification checkpoints, requesting sources, and deciding when to re-run tasks
- Exercise: Conducting company background and regulatory research on a target entity
- Exercise: Using Wide Research to compare multiple companies against consistent criteria
Module 3: Managing Financial Data
- Uploading various file types: spreadsheets, PDF statements, and finance system exports
- Cleaning and standardizing ledgers; creating formulas and summaries in Excel-style outputs
- Extracting numerical data from PDF financial statements into structured tables
- Performing reconciliations and anomaly checks (e.g., duplicates, round-number tests, Benford’s law screens)
- Exercise (Forensic): Identifying anomalies in a synthetic transaction ledger and documenting the methodology
- Exercise (Corporate Finance): Constructing a comparables table from provided statements
Module 4: Finalizing Outputs and Creating Repeatable Work
- Generating diverse deliverables—memos, slide decks, and interactive dashboards—from a single analysis
- Projects: Centralizing files, instructions, and context for specific clients or engagements
- Skills: Converting successful workflows (e.g., due-diligence checklists or valuation templates) into reusable components
- Automations: Setting up scheduled or event-triggered tasks, such as weekly market summaries
- Exercise: Packaging Module 3 analysis into a memo and slide deck, then saving the process as a Skill
Module 5: Risk, Governance, and Credit Discipline
- Data governance: Understanding firm policies, client confidentiality, and regulatory constraints on data input
- Provider context: Implications of Manus’s 2025–26 ownership changes and the August 2026 data deletion policy
- Verification protocols: Detecting hallucinated figures, outdated sources, and calculation errors through citation and spot-checks
- Audit trails: Preserving task histories, exporting outputs, and documenting agent actions
- Credit management: Optimizing task sizing, using Chat mode for simple queries, and preventing uncontrolled tasks
- Discussion: Drafting a one-page team usage policy
Module 6: Capstone and Future Steps
- Participants develop one complete workflow relevant to their current job functions
- Group presentation and feedback session with the trainer and peers
- Personal 30-day plan: Identifying two tasks to migrate to Manus and one Skill to build
- Takeaway materials: Prompt patterns, review checklists, and credit usage guides
Requirements
- Basic familiarity with web-based applications is required; no prior experience with AI is necessary.
- Participants must access their own Manus license on a work laptop using Chrome or Edge. As Manus is a cloud-based service, virtual machines are not required.
- It is essential to verify the Manus plan and credit balance prior to the course. Scheduling the session early in the billing cycle is recommended, as a full day of hands-on work can significantly impact monthly credit allocation.
- Collaborate with IT to confirm which connectors are approved (e.g., Gmail, Google Drive, Notion) to ensure demonstrations align with available post-course tools.
- The trainer utilizes a separate, paid Manus account for preparation and live demonstrations.
- All exercise data is synthetic and provided by the trainer; participants are strictly advised not to upload client data.
- A pre-course survey (approximately 10 minutes) requesting details on one or two repetitive tasks from their current workflow should be submitted at least one week in advance.
Target Audience
- Finance Associates
- Forensic Accountants
- Corporate Finance Professionals
Testimonials (4)
The difference between strategy and plan
Berat Rahmani - Wallee Group AG
Course - Leadership and Team Management for Managers
How to manage business financials
surprise mtileni - Hatima Holdings (Pty) ltd
Course - Learning Xero
Good communication, open for discussion, kept it interesting and engaging
Ahmet Keyman - Keytrade AG
Course - Management Accounting and Finance for Non-Finance Professionals
Experience of the trainer and his way of conveying the content
