Platform spec on the Build Your Own AI Platform track. Write a spec for a platform that can train, register, evaluate, serve, and roll back one model for two tenants. Include the off switch and the log fields.
This lesson assumes you already worked through Interview review.
The idea in practice
Two to four pages. Name what you would buy instead of build.
A concrete check
goal = {
'track': 'Build Your Own AI Platform',
'lesson': 'Platform spec',
}
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 spec with no tenant boundary and no rollback. 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
Produce the outline and fill rollback plus tenant isolation.
Self-check
- Say Platform spec 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.