What makes AI features different to operate
On This Lesson 4 topics
This lesson is planned. The outline below lists the topics it will cover. The full lesson has not been published yet.
In this lesson
list how model-backed features differ from ordinary services.
Planned topics
- Outputs are non-deterministic and quality is a spectrum, not pass or fail.
- Latency is long and variable; cost scales with tokens, per call.
- The provider is an external dependency with quotas, rate limits, outages, and model changes.
- Quality can degrade silently when prompts, models, or data change.
Draft outline details
Demonstration
a comparison table of a normal REST dependency and an LLM call: latency, cost, determinism, failure modes.
Check your understanding
Why is "up" not enough for an AI feature?
Show answer
Answers can be wrong or slow while the service is technically up.
Practice
Apply this lesson with the module's lab, exercises and quiz.
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