The useful question about AI is often very ordinary: which recurring piece of work should be easier to complete next week?
For a supplier, that might be preparing a weekly item review. For a broker, it might be turning a client conversation into a clear action list. For a private-brand team, it might be finding the unresolved decisions across a launch plan.
I would start there. A reliable workflow needs an owner, usable inputs, a clear output, and a way to catch mistakes. Whether it eventually becomes an “agent” is a later implementation choice.
Choose a piece of work you can explain
Describe the current task without mentioning AI. Who does it? What decision does it support? What evidence is required? Where does the output go?
For example: “Before the client call, reconcile the permitted weekly extract to our agreed metric definitions, identify exceptions, and prepare questions for the account lead.”
That is specific enough to evaluate. “Automate retail insights” is not.
A useful first workflow has a stable owner and a bounded output. It should also have a manual version that the team understands. Automating a disputed definition usually makes the disagreement arrive faster.
Separate knowledge from account data
A maintained reference can explain a retailer process. An account extract can describe a client's business. A workflow may need both, but they are different inputs with different permissions.
For Walmart work, establish whether the client is a first-party supplier or a third-party Marketplace seller. Identify the retailer, banner, account role, and reporting entitlement. A Marketplace API does not provide universal access to first-party supplier workflows. A Scintilla Basic account does not have the same reporting and integration capabilities as a Charter account.
For an agency, being allowed to work with a client is also separate from being provisioned for a retailer's data service. Use the appropriate sponsored access and each person's own credentials. Do not design a process around borrowing a client's login.
Keep a simple input record:
- Source, extraction date, period, and data grain.
- Metric definitions, units, identifiers, and known exclusions.
- Who may use the information and for which purpose.
- The permitted destination, retention, and people who may receive the output.
An export is a possible input only when its use in the proposed system is permitted. A spreadsheet on a shared drive is not automatically suitable for an external AI service.
For the current division of operational systems, use Retail Reason's Supplier One and Retail Link guide. This article focuses on designing the team's workflow, rather than maintaining a second portal directory.
Start with a draft the owner can inspect
Here is a practical first version of the weekly-review example:
- An authorized person provides the permitted extract and the agreed definitions.
- Code checks required fields, duplicates, missing periods, and totals.
- The process returns an exception list if those checks fail.
- AI drafts a summary from the checked results and the context provided.
- The account lead reviews the calculations, explanations, and proposed next questions before sharing anything.
The system should distinguish a measured fact from an explanation it is proposing. “Sales fell in these items” can be supported by a table. “A competitor's promotion caused the decline” needs evidence the table may not contain.
Choose success measures for the whole task: preparation time, corrections required, review time, and whether the output helps the meeting. A faster draft that takes longer to verify is not necessarily an improvement.
Add automation where the boundary is understood
A scheduled workflow needs an actual trigger, accessible inputs, suitable permissions, and a supported integration. A prompt alone supplies none of those.
Before connecting a retailer system, verify that the specific operation exists, the account has the required entitlement, and the intended use is permitted. A documented read operation does not imply a write operation exists. An integration may require separate provisioning from ordinary portal access.
For a first implementation, a person pressing “run” can be entirely appropriate. Add scheduling when the input arrival, failure handling, and owner are predictable. Keep a record of which input and workflow version produced each output.
Feedback also needs a process. Recording a correction does not automatically retrain a model or update future runs. Someone must decide whether to change a definition, a prompt, a calculation, or the underlying reference, then check the revised behavior.
For partners, protect the client relationship in the design
A broker or advisor should be able to add capability without giving up ownership of the client conversation.
Agree on who receives drafts, who can see the underlying data, who approves communication, and what carries the partner's branding. Separate client workspaces, files, credentials, and output destinations. Review the boundary with an actual multi-client example before rolling it out.
White-label work should start with a defined workflow and a written scope: the audience, the data it may use, the responsibility for upkeep, and what happens when it cannot answer. The branding comes after those decisions.
Retail Reason's broker and agency offering addresses maintained retail guidance for client work. Its published limitations remain explicit: the product does not open retailer portals or retrieve client data. Custom analytics or integrations are separate work and should be described that way.
Decide what deserves a second iteration
Review several representative cases, including incomplete inputs and an answer that should be withheld. Include more than the easiest example. Ask the person who owns the work whether the output was useful and what they had to correct.
Expand only when you can explain why the workflow is dependable within its scope. Sometimes the right result is a better template and a human review step. Sometimes it is a supported integration. Both can create value when they make the actual work easier to finish.
If your team needs help choosing that first workflow, talk with Startup Success Lab.