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Duration 7 hours
Course Outline
Module 1: Manus for Finance Professionals
- Understanding general AI agents: planning, acting, and delivering versus simply answering.
- Comparing Chat mode and Agent mode: determining the appropriate use case for each.
- Explaining the credit system, typical task costs, and managing the team's shared credit pool.
- Overview of the current interface: tasks, Projects, files, connectors, Skills, and Automations.
- Identifying where Manus integrates into finance, forensic, and corporate finance workflows, and where it does not apply.
- Exercise: Execute a small task in both modes and compare the results and credit expenditure.
Module 2: Briefing, Steering, and Review
- Writing actionable briefs: defining goals, inputs, output formats, and constraints.
- Monitoring agent activity, intervening mid-task, and managing browser and login steps.
- Evaluating outputs: verification steps, requesting sources, and criteria for re-execution.
- Exercise: Conducting company background and regulatory research on a target entity.
- Exercise: Using Wide Research to compare a list of companies against defined criteria.
Module 3: Working with Financial Data
- Uploading various file types: spreadsheets, PDF statements, and finance system exports.
- Cleaning and standardizing ledgers, and constructing formulas and summaries in Excel-style outputs.
- Extracting figures from PDF financial statements into structured tables.
- Performing reconciliations and anomaly checks (duplicates, round-number tests, Benford's-law screening).
- Exercise (Forensic): Flagging anomalies in a synthetic transaction ledger and documenting the methodology.
- Exercise (Corporate Finance): Building a comparables table from provided statements.
Module 4: Final Outputs 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: Setting up scheduled or event-triggered tasks, such as weekly market summaries.
- Exercise: Packaging Module 3 analysis into a memo and slides, then saving the method as a Skill.
Module 5: Risk, Governance, and Credit Discipline
- Data protocols: Determining what data can and cannot be input into Manus, considering firm policy, client confidentiality, and regulatory requirements.
- Provider context: Understanding Manus's 2025–26 ownership changes and the August 2026 data deletion policy, and their impact on data decisions.
- Output verification: Identifying hallucinated figures, outdated sources, and calculation errors; emphasizing citation and spot-checks.
- 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
- Participants build one workflow tailored to their own job functions.
- Brief group demonstration with feedback from the instructor and peers.
- Personal 30-day usage plan: Identify two tasks to migrate to Manus and one Skill to build.
- Handout: Prompt patterns, review checklist, and credit guide.
Requirements
- Basic proficiency with web applications is recommended; prior AI experience is not required.
- Participants must log in to their individual Manus licenses on work laptops using Chrome or Edge. As Manus is a cloud-based service, no virtual machine is necessary.
- Verify Manus plan status and credit balances prior to the course. Scheduling early in the billing cycle is advised, as intensive hands-on work may consume a significant portion of monthly credits.
- Coordinate with IT to confirm approved connectors (e.g., Gmail, Google Drive, Notion) to ensure demonstrations align with post-course capabilities.
- The instructor utilizes a separate paid Manus account for preparation and live demonstrations.
- All exercise data is synthetic and provided by the instructor; participants must not use client data.
- Complete the pre-course survey (approx. 10 minutes) by submitting one or two repetitive tasks from your current workflow 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
