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Sample Data and Resetting an App

An empty datastore hides problems. Sample data fills one with realistic rows so you can see how it actually behaves.

Where to find it

Architect Panel → Data:

  • Sample Data — the generator, and the reset that undoes it
  • AI Builder — where a new structure is usually created

Why generate data at all

Layout, validation and performance problems are invisible on an empty form and obvious with fifty rows in it:

  • Columns too narrow for real values.
  • A browse view that looks fine with three rows and unusable with three hundred.
  • Dropdowns that should have been searchable.
  • A dashboard block that takes four seconds once there is history behind it.

Building against an empty system and discovering these after go-live is the normal way a rollout goes badly.

Generating

The generator creates plausible values for the field types it finds — names, addresses, dates, numbers, selections — so the result looks like data rather than "test1, test2, test3". That matters: realistic values expose layout problems that placeholder text does not.

Resetting

The reset removes application data and returns the app to an empty state. That is what makes generating freely safe — you can fill it, look at it, adjust, refill.

Understand precisely what the reset clears before running it. It is designed for a development or pre-launch instance. On anything holding real data it is exactly as destructive as it sounds.

Never generate into production

Generated records are indistinguishable from real ones to everybody except the person who generated them. Once mixed into live data they are very hard to remove reliably, and they will appear in reports, counts and returns.

Worked example

A team builds a new inspections datastore. Before rolling it out they generate 200 sample inspections, which immediately shows that the browse view needs a date filter and the notes column is far too narrow. Both are fixed, the data is reset, and the real rollout starts on a form that has already been used in anger.

Recommendations

  • Generate before you demonstrate. A demo on empty screens shows nothing.
  • Never generate on production.
  • Read what the reset clears before you run it, every time.
  • Generate enough to be realistic — twenty rows will not reveal a performance problem.