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Back to the business caseAI coding tools · Implementation
From a refund request to tested code
The assistant retrieves the reference and generates a call. Documentation supplies the operation’s meaning, valid inputs, and recovery path; the sandbox establishes what the code actually does.
Follow the process- Business goal
- Build brand loyalty
- Business metric
- Integration activation rate
Build, test, and correct the request
Use a supported API version, a test payment, and sandbox access. Keep production credentials and payments outside this trial.
The task in this example
Write a function that refunds part of a payment with the Payments API.
- Step 1
Interpret the request
The assistant identifies a partial refund as the intended task.
ModelThe model interprets the prompt; ambiguous payment states may require a question.
- Step 2
Retrieve the reference
The assistant reaches the API docs through the site or MCP server.
SystemEngineering exposes current entries and their version context through a supported retrieval path.
- Step 3
Choose the operation
Select refunds rather than reversals or credit notes.
TaxonomyDefine the operations and their synonyms with examples of when each applies.
- Step 4
Construct the call
Generate code from the supported field definitions and example.
Content teamKeep required inputs, amount units, expected state, and version together.
- Step 5
Run the sandbox case
The developer executes and checks the result.
PeopleConfirm both response and payment/refund state; compilation alone is insufficient.
- Step 6
Recover from a documented error
The assistant proposes a correction using the returned code.
Content teamExplain causes and remedies beside each error.
ModelThe assistant must still choose and apply the right correction.
This framework provides a practical baseline shaped by experience. Every organization operates under distinct technical and operational realities that require tailored design and governance. While you can adapt these measures independently, we frequently partner with teams to customize governance, integrations, and rollout. Performance outcomes will naturally vary.
Why these content layers matter
Intelligent content
Maintain required fields, runnable examples, expected responses, and actionable errors with the endpoint version.
Taxonomy
Distinguish refunds, reversals, and credit notes, including the terms developers use, so retrieval selects the correct operation.
Verify the result and handle exceptions
Exercise a valid partial refund and representative invalid inputs. Check that the assistant retrieves current docs and that fixes preserve the intended payment and amount.
If the reference conflicts with the schema or observed sandbox behavior, return the discrepancy to engineering. Do not resolve it by inventing an undocumented field.
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Support for this implementation
Define ownership, version policy, and review standards for a reference that coding assistants can retrieve and developers can test.
- Content strategySet priorities, ownership, and a rollout your team can sustain.
- Information architectureStructure content for reliable retrieval and reuse.
- User experienceDesign and test the experience around real user tasks.
- Metadata and iiRDSDefine classification and delivery metadata, using iiRDS where it fits.
Where do generated API calls break down?
Intuitive Stack can help review endpoint structure, developer terminology, and the examples and error guidance a coding assistant needs to produce testable work.