Interview review on the Build Your Own AI Platform track. A platform interview wants registry, versioning, eval gates, auth, logs, cost, and rollback. Pick one model and walk the lifecycle.
This lesson assumes you already worked through Build versus buy.
The idea in practice
Draw the path from train job to prod pointer.
A concrete check
goal = {
'track': 'Build Your Own AI Platform',
'lesson': 'Interview review',
}
checks = [
'input available at decision time',
'score matches the real decision',
'failure case written down',
]
print(goal['lesson'])
for item in checks:
print('-', item)
Run the sketch locally if you have Python. The printout is a reminder of the checks, not a trained model. Replace the strings with the real inputs from your own example before you treat it as a design.
What usually goes wrong
A diagram that is only boxes labeled AI. When this happens, stop adding parameters or tools. Fix the check, the data, or the permission, then run the same example again.
What to write down
- The input you are allowed to use at decision time.
- The output and the score or pass rule.
- One failure you will test on purpose.
- What you will not claim the system can do.
Practice
Talk through that path in five steps.
Self-check
- Say Interview review in one sentence that mentions an input and an output.
- Name the failure mode in this lesson and the check that would catch it.
Done when: you can explain this lesson without the page open, and you have a written failure case.