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Duration 7 hours
Course Outline
Module 1: Introduction to Manus for Finance Professionals
- Defining the general AI agent: planning, acting, and delivering versus simple answering.
- Comparing Chat mode and Agent mode: determining appropriate use cases.
- Understanding credit mechanics, typical task costs, and managing the team’s shared credit pool.
- Interface tour: exploring tasks, Projects, files, connectors, Skills, and Automations.
- Positioning Manus within finance, forensic, and corporate finance workflows, including its limitations.
- Exercise: Execute a small task in each mode and compare outcomes and credit costs.
Module 2: Briefing, Steering, and Review
- Crafting actionable briefs for Manus: defining goals, inputs, output formats, and constraints.
- Monitoring agent activity, intervening mid-task, and managing browser and login interactions.
- Evaluating outputs: checking accuracy, requesting sources, and deciding when to re-run.
- Exercise: Conduct company background and regulatory research on a target entity.
- Exercise: Utilize Wide Research to compare a list of companies against unified criteria.
Module 3: Handling Financial Data
- Uploading various file types: spreadsheets, PDF statements, and exports from finance systems.
- Cleaning and standardizing ledgers; constructing formulas and summaries in Excel-style outputs.
- Extracting key figures from PDF financial statements into structured tables.
- Performing reconciliations and anomaly checks, including duplicate detection, round-number tests, and Benford’s-law screening.
- Exercise (Forensic): Identify anomalies in a synthetic transaction ledger and document the methodology.
- Exercise (Corporate Finance): Create a comparables table from provided financial statements.
Module 4: Final Deliverables and Repeatable Workflows
- Generating memos, slide decks, and interactive dashboards from a single analysis.
- Projects: Organizing files, instructions, and context for specific clients or engagements.
- Skills: Converting successful workflows (e.g., due-diligence checklists, valuation templates) into reusable steps.
- Automations: Implementing scheduled or event-triggered tasks, such as weekly market summaries.
- Exercise: Package the Module 3 analysis into a memo and slides, then save the method as a Skill.
Module 5: Risk, Governance, and Credit Discipline
- Defining data boundaries for Manus: firm policies, client confidentiality, and regulatory requirements.
- Provider context: Understanding Manus’s 2025–2026 ownership changes and the August 2026 data deletion policy, and their impact on data decisions.
- Output verification: Identifying hallucinated figures, stale sources, and calculation errors; emphasizing citation and spot-checking.
- Audit trails: Saving task histories, exporting outputs, and documenting agent actions.
- Credit discipline: Sizing tasks appropriately, using Chat mode for simple queries, and preventing runaway tasks.
- Discussion: Developing a one-page team usage policy.
Module 6: Capstone and Next Steps
- Each participant builds a workflow based on their own job functions.
- Short group demo with feedback from the trainer and peers.
- Personal 30-day usage plan: Identify two tasks to migrate to Manus and one Skill to build.
- Handout: Prompt patterns, review checklists, and credit guides.
Requirements
- Basic familiarity with web applications is assumed; no prior AI knowledge is necessary.
- Participants must sign in to their individual Manus licenses using a work laptop equipped with Chrome or Edge. As a cloud-based service, Manus does not require virtual machine setup.
- It is essential to verify the Manus plan tier and credit balance prior to the course. Ideally, schedule the session early in the billing cycle, as a full day of hands-on work may significantly impact the team’s monthly credit allowance.
- Coordinate with IT to confirm which connectors are approved (e.g., Gmail, Google Drive, Notion) to ensure demonstrations align with post-course capabilities.
- 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 advised not to bring client data.
- Pre-course survey (approximately 10 minutes): Identify one or two repetitive tasks from current duties and submit them at least one week before the session.
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
