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Accounting teams are being handed AI tools and asked to produce work that will survive an audit. This course teaches the discipline that makes that possible. Finance engineering is the practice of building repeatable AI workflows on top of accounting data you can actually trust, with the controls and evidence a reviewer and an external auditor will expect. It is written for accountants, controllers, accounting managers, and finance leaders who want to automate month-end close work without writing code.

The course runs across five modules. DATA covers the hygiene, lineage, and context practices that determine whether an AI answer can be relied on: vendor master cleanup, consistent general ledger coding, context inventories, and exception logs. BUILD covers how to turn a process you perform every month into a reusable AI Skill, how the Model Context Protocol connects an AI assistant to your ERP and close platform, and how to share, schedule, and set permissions on what you build. CONTROLS covers governance: inventorying every agent your team runs, tiering each by materiality and reliance, naming the human checkpoint, and producing the audit trail and evidence of review that Information Produced by the Entity requires. STACK covers build-versus-buy analysis, total cost of ownership, and why the connections between your systems determine what your technology stack can actually do. ACCT'G INTEL covers the shift from preparing to reviewing, including how to form an independent expectation before reading an agent's output, and the convergence of accounting and financial planning and analysis as AI absorbs the preparation work between them.

Participants finish able to identify where their own data will break an AI workflow, build and share a Skill for a recurring close task, govern that Skill in proportion to what it touches, defend it to an external auditor, and judge whether the next workflow should be built or bought. Each module includes review questions, and the course includes a glossary of the vocabulary this work now requires, from Skills and agents to orchestration, tiering, and defensibility. 

Course Key Concepts: AI for Accountants, Finance Engineering, Claude Skills, Model Context Protocol (MCP), AI Agents in Accounting, Month-end Close Automation, Internal Controls Over AI, Audit Readiness, Build Versus Buy, Data Quality for AI.