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IBM

Designing and Building AI Assistant Workflows

IBM via Coursera

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Overview

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Many automation initiatives stall between analysis and implementation because practitioners lack the hands-on skills to configure a working AI assistant. This course, Designing and Building AI Assistant Workflows, closes that gap. You will study the anatomy of an AI assistant, including skills, tools, instructions, knowledge sources, and routing logic, and then build your first working assistant end-to-end in your own IBM watsonx Orchestrate free-trial instance for a realistic business scenario. You will also learn to connect assistants to enterprise data sources at a business-configuration level, write integration requirements that IT teams can act on without rework, and design conversational intake, triage, classification, and routing workflows with human-in-the-loop checkpoints and exception paths that fail gracefully. By course completion, you will have produced an End-to-End AI Assistant Build with a configured, working assistant, instructions documentation, integration specifications, and a complete intake-triage-routing flow evidenced by screenshots and a test report.

Syllabus

  • Anatomy of an AI Assistant
    • In this opening module of the build phase, you will take an AI assistant apart to see what it is actually made of. You will study skills, tools, instructions, knowledge sources, and the routing logic that ties them together, examine how an assistant decides what to do when a request is ambiguous, and set out the design principles that distinguish a useful assistant from a noisy or unreliable one. The lab has you dissect a pre-built reference assistant in watsonx Orchestrate and document its design choices.
  • Building Your First Assistant with watsonx Orchestrate
    • In this module, you will build, end to end, your first working AI assistant in a self-service watsonx Orchestrate free-trial environment. The build is scoped to a realistic business scenario — such as employee onboarding queries, supplier-invoice intake, or simple HR self-service — so the design choices stay business-led rather than technical. You will scope the assistant, write instructions and example dialogs that shape its behavior, wire in pre-built skills, and test and iterate against representative requests. The lab produces a complete working assistant with screenshots and a short reflection.
  • Connecting Enterprise Systems and Data
    • Real automation depends on real data. In this module, you will learn how AI assistants connect to enterprise systems and data sources, what a business analyst needs to specify versus what IT will deliver, and how to think about data quality, freshness, and access control. You will work with integration patterns across HR, CRM, ERP, ITSM, and knowledge bases. The lab has you connect your Module 2 assistant to two data sources in your free-trial instance and write integration requirements for a third.
  • Intake, Triage, Routing, and Human-in-the-Loop
    • In this module, you will bring everything together into one of the highest-value patterns in scope: assistants that handle intake, classify and triage incoming work, route it appropriately, and hand off to humans when warranted. You will design conversational intake that produces structured data, configure triage and classification logic, build routing rules, and implement explicit human-in-the-loop checkpoints and exception paths so the assistant fails gracefully. The lab extends your Module 2 assistant into a complete intake-triage-routing flow tested against a provided test pack.
  • Cumulative Project and Course Wrap-Up
    • In this final module, you will assemble everything from Modules 1 through 4 into a cumulative project: an End-to-End AI Assistant Build. The deliverable is a configured, working assistant in your watsonx Orchestrate free-trial instance, an instructions document with example dialogs, integration specifications for connected and pending data sources, and a complete intake-triage-routing flow with human-in-the-loop checkpoints and exception paths, evidenced by screenshots and a short test report. The module closes with a wrap-up featuring an SME interview, a day-in-the-life view of an Automation Designer, and a bridge into Course 3's deployment, governance, and scaling work.

Taught by

Starweaver

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