Connect tasks, people, tools, and review so work moves forward.
What you’ll buildDesign and test one small business workflow.
A workflow is a sequence of steps that takes work from a request to a result. Think about a customer inquiry. Someone receives it, checks what is needed, prepares information, reviews it, and replies. If the steps are unclear, software can make the confusion move faster.
Start by drawing the current process. Name the input, the expected result, and the person responsible at each step. Then identify repeated work. AI might draft a summary, sort requests, or prepare a checklist. A fixed rule might be enough for a simpler task.
An agent is a system that can take steps and use tools within its allowed limits. Its ability to do something is not the same as permission to do it. Keep review points visible. Try incomplete and unusual cases before trusting a process with important actions.
An AI workflow drafts customer replies but sends them before anyone checks the customer record.
Pause and choose your first action. Explain why it would help before opening the example response.
Separate preparation from authority to send. Map the steps, require the responsible person’s review, and test a missing-information case before turning on automation.
Start with plain words, a useful question, and one worked example.
Hear a perspective, notice a choice, and pause to think.
Try a small task. Use feedback to make the next attempt better.
Make something you can use, test it, and reflect on the result.
These six modules outline the full course we are building. Planned topics are not yet full lessons. Start with the published foundation lesson below; available deeper lessons are linked in their relevant modules. No other course is required.
This introductory lesson is ready to use. The six-module curriculum below shows the larger course being developed. Take any course independently.
A workflow takes an input through steps to a result. Begin with the current process, including handoffs and delays. Name what arrives, who checks it, what information is needed, and what should be produced. A customer inquiry may need classification, a record lookup, a draft reply, review, and sending. Drawing those steps exposes missing responsibilities. Automating an unclear process usually moves the confusion faster rather than solving it.
A fixed rule works well for a clear, repeatable condition. AI may help with language, summaries, or varied input, but its outputs need suitable checks. An agent can take steps using tools within its design; capability is not permission. Define what it may read, prepare, change, or send. Give the least access needed for the task. Important decisions need a named reviewer and a visible way to handle missing information or an exception.
A successful ordinary case does not prove a workflow is reliable. Test incomplete requests, duplicates, unusual language, unavailable tools, and conflicting records. Record the input, result, reviewer decision, and errors. Keep a fallback so someone can finish the work manually. Judge the pilot by accuracy, useful time saved, and rework. Expand access only after the process performs acceptably under the cases that matter.
A team wants faster customer replies. They first build a flow that reads an approved request, checks the order record, and drafts a response. A person must approve sending. A test request contains no order number, so the flow asks for missing information instead of inventing a record. A duplicate request is flagged. The pilot saves drafting time while keeping the decision boundary clear.
Draw a five-step workflow. Label inputs, outputs, owner, review point, and exception path. Test one normal case and two boundary cases with fictional information. Record what a person must approve before any external action.
Ask someone to try your result when practical. Use their experience to revise one choice. The three questions check understanding; the project checks what you can actually do.
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Original InAct explanation and illustrative examples. These primary sources support further study; platform terms should be checked again before use. References use an APA-style organization, date, and title. Sources without a verified publication date are marked n.d.
The written lesson stands on its own. These optional videos offer another example or perspective. Read the focus, watch if you choose, and try the idea yourself. If a video is unavailable, continue with the explanation and practice on this page.
Ethan Mollick · The Wharton School
Start at 00:00. Separate demonstrations from claims about every workplace. Sketch a small task where you could compare your work with an AI-assisted draft. This talk is from 2023.
Watch on YouTube at 00:00 ↗The Wharton School. (n.d.). Generative AI & the Disruption of Work [Video]. YouTube. Original publisher link above. Video and availability remain controlled by the publisher.
Andrew Ng · Stanford Online
Start at 00:00. Use the talk as a foundation. Write down one task, one possible use of AI, and one result you would need to check. Product examples are from 2023.
Watch on YouTube at 00:00 ↗Stanford Online. (n.d.). Opportunities in AI, 2023 [Video]. YouTube. Original publisher link above. Video and availability remain controlled by the publisher.
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