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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 when to use each.
- Explaining credit mechanics, typical task costs, and the team’s shared credit pool.
- An overview of the current interface: tasks, Projects, files, connectors, Skills, and Automations.
- Identifying where Manus fits within finance, forensic, or corporate finance workflows, and where it does not.
- Exercise: Execute a small task in both modes and compare the outcomes and credit costs.
Module 2: Briefing, steering, and reviewing
- Crafting briefs that Manus can execute: defining goals, inputs, output formats, and constraints.
- Monitoring the agent’s progress, intervening mid-task, and handling browser and login steps.
- Reviewing outputs: key checkpoints, requesting sources, and determining when to re-run tasks.
- Exercise: Conduct company background and regulatory research on a target entity.
- Exercise: Use Wide Research to compare a list of companies against consistent criteria.
Module 3: Working with financial data
- Uploading files: spreadsheets, PDF statements, and exports from financial systems.
- Cleaning and standardizing ledgers; constructing formulas and summaries in Excel-style output.
- Extracting data from PDF financial statements into structured tables.
- Performing reconciliations and anomaly checks (duplicates, round-number tests, Benford’s-law screening).
- Exercise (Forensic): Identify anomalies in a synthetic transaction ledger and document the methodology.
- Exercise (Corporate Finance): Construct a comparables table using provided financial statements.
Module 4: Finished outputs and repeatable work
- Generating a memo, slide deck, and interactive dashboard from a single analysis.
- Projects: Consolidating files, instructions, and context for specific clients or engagements.
- Skills: Converting successful workflows (e.g., due-diligence checklists or valuation templates) into reusable steps.
- Automations: Setting up scheduled or event-triggered tasks, such as weekly market summaries.
- Exercise: Package the Module 3 analysis into a memo and slides, then save the methodology as a Skill.
Module 5: Risk, governance, and credit discipline
- Data governance: Determining what data is permissible for Manus based on 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 implications for data decisions.
- Verifying outputs: Identifying hallucinated figures, stale sources, and calculation errors; always citing sources and spot-checking results.
- 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 derived from their own job responsibilities.
- A brief demonstration to the group, with feedback from the instructor and peers.
- A personal 30-day usage plan: identifying two tasks to migrate to Manus and one Skill to develop.
- Handouts: Prompt patterns, review checklists, and a credit guide.
Requirements
- Basic proficiency with web applications; no prior experience with AI is necessary.
- Participants must sign in to their individual Manus license on their work laptop using Chrome or Edge. As Manus is a cloud-based service, a virtual machine is not required.
- Please verify your Manus plan status and credit balance before the session. Ideally, schedule the training early in the billing cycle, as a full day of hands-on work may consume a significant portion of the team’s monthly credits.
- Confirm with IT which connectors are approved for use (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 are advised not to bring confidential client data.
- A pre-course survey (approximately 10 minutes) requesting one or two repetitive tasks from current workflows, to 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
