A useful AI-assisted coding project is more than a prompt and a promising demo. It is a traceable sequence: define what should work, plan the important decisions, build in small pieces, run the application, and record what passed or failed. A “case file” is a practical name for that record—not a prescribed industry template. The point is to make the workflow inspectable and improvable, rather than trusting generated code on appearance alone.
What vibe coding looks like in practice
Vibe coding is often described as building software through natural-language prompts, but the work is not simply one prompt followed by a finished product. A 2025 study by Advait Sarkar and Ian Drosos analyzed more than eight hours of curated video from extended sessions with think-aloud reflections. The authors observed cycles of prompting, quickly inspecting generated code, testing the application, and making manual edits. They describe debugging as a hybrid activity: the developer decides what context to provide, judges whether an output is sound, and chooses when to stop prompting and take direct control. The study describes observed sessions, not a population-wide productivity measure. Read the study on arXiv.
That pattern suggests a useful case-file principle: document the decisions and checks that make the result trustworthy, not every line of code or every prompt. The file should help someone answer what was intended, what changed, what was actually tested, and what remains uncertain.
Start the case file with an outcome, not a tool
Before asking an assistant to build, write down the intended user and the observable result. “Make a useful dashboard” is hard to verify. “A coordinator can add a case, assign an owner, and see its status on the case list” gives the project something concrete to build and test.
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- Goal: What task should the application help someone complete?
- User: Who performs that task, and what do they know or need?
- Success conditions: What visible or testable behavior would show that the task works?
- Boundaries: What is explicitly out of scope for this version?
- Open questions: Which decisions still need a human answer?
These notes become a reference point when generated features drift from the original need. Keep uncertain choices marked as uncertain rather than letting an assistant silently turn assumptions into requirements.
Turn the idea into a plan a person can review
A written plan can make implementation easier to inspect, but it does not replace judgment. In a practitioner account of rebuilding an RFP-responder application, the author asked an AI to create a main implementation document and supporting Markdown files for major sections, then reviewed the plan before execution. The author contrasts unstructured work, in which the AI makes decisions, with an agentic approach that leaves architecture decisions with the person. This is an example from one project, not proof that a particular document structure is best. Read the RFP-responder account.
For a case file, capture the decisions that affect behavior or make changes costly: major components, data boundaries, external services, and how changes will be checked. Sketches or mockups can clarify expected screens. The useful question is not whether the plan is elaborate, but whether a reviewer can identify the next work item and the assumptions behind it.
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Break implementation into bounded tasks
Once the plan is reviewed, divide work into small tasks with an expected output and a way to verify it. A task such as “build the whole application” gives both the person and the assistant too much room to lose context. A task such as “add a case form with required title and status fields; after saving, show the new case in the list” is easier to assess.
- Specify one change. State the behavior or interface element to implement, along with constraints that matter.
- Name the output. Identify the screen, component, or behavior that should exist when the task is complete.
- Define a check. Say what action a user or test should perform and what result should appear.
- Review before continuing. Inspect the change and its effect on adjacent work before assigning another task.
Vibe Voyager’s retrospective describes a project workflow using brainstorming, a design document, phased implementation, independent tasks, review checkpoints, commits, type-checking, and a build log. The project reports a core build of about 66 minutes, more than 14,400 TypeScript lines across 61 source files, 35-plus agent invocations, 26 commits, and zero type errors. Those are the project’s own figures, with no date stated on the page; they are not independently validated measures of quality or a forecast for another project. Read the Vibe Voyager retrospective.
Generate in cycles, then test the running application
For each bounded task, prompt, inspect the proposed change, and run the application or relevant checks. If the result is wrong, give the assistant a specific correction or make the change directly. Record what changed and what evidence supports calling it complete.
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Runtime checks matter because code that looks plausible—or even compiles—may still fail in use. In the RFP-responder account, the author ran the application and found buttons that did not work and an interface that differed from the mockups. The author then asked the assistant to fix and validate the problems using browser tools. That example makes a distinction worth keeping in the case file: a build or type check is evidence about a limited class of errors; it does not establish that a user workflow works or that a screen matches its intended design.
- Run the application and follow the intended user path from beginning to end.
- Check that controls perform the actions their labels imply.
- Compare important screens with the approved sketch or mockup.
- Note which checks were actually performed and their results; do not mark an untested behavior as verified.
Keep decisions, changes, and evidence traceable
A practical case file can be a short project log alongside the code, rather than a separate bureaucracy. Record the requirement or task, the relevant decision, the change made, the checks performed, and any unresolved issue. A Git history can help show how the project changed and make a known-good state easier to recover, while clear technical ownership remains important.
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A lightweight log entry might look like this:
- Task: Save a new case and show it in the list.
- Decision: New cases begin in “Open” status unless the user chooses another status.
- Change: Form and list behavior updated.
- Verification: Submitted a case with required fields and confirmed it appeared as Open.
- Unresolved: No duplicate-submission check yet.
The example separates completed work from an outstanding issue. That makes the log useful to the next person—or to the same person returning to the project later.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Review the workflow, not just the deliverable
After the main user path works, inspect the case file for recurring friction. Did tasks repeatedly exceed their boundaries? Did an assumption cause rework? Did a check catch a defect before the next feature depended on it? Use those observations to refine requirements, task instructions, or review points. Treat what you observed as evidence about this project, not as proof that the same process will produce the same result elsewhere.
Other accounts illustrate why reported outcomes need context. Humantyze describes a two-session agency buildathon in which teams made prototypes, mapped workflows, and designed agents with triggers, guardrails, and escalation rules. It reports “6–10 working tools and agents produced”; that is the provider’s reported outcome, not an audited result. Read Humantyze’s account.
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Across these examples, the defensible comparison between a loose prompt-driven attempt and a more deliberate workflow is qualitative: time to a first prototype, planning effort, human review and runtime verification, traceability and reversibility, and the later effort needed to maintain the result. The sources do not provide a controlled comparison or establish a universally best tool or process.
What the case file should make clear
- What was requested and for whom.
- Which architecture or workflow choices were made by a person, and which remain assumptions.
- What each implementation task was expected to produce.
- What was run, checked, or reviewed, with results distinguished from expectations.
- What changed, what can be recovered, and what still needs attention.
Vibe coding can reduce the effort of producing code, but the observed workflow still relies on context, evaluation, and deliberate verification. The most useful case file is the one that makes those human decisions and checks visible.
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