Instructor topics
12 short topics in Generative AI and LLM Applications. Each one is a single focused exercise with a clear piece of evidence at the end.
12 topics, one exercise each.
Work through them in order, or jump to the one you need.
These are draft topic outlines (draft; instructor review pending). Full lessons follow after review; ask Ajay if you need a topic sooner.
- 01
Output schema representation
Demonstrate output schema representation in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 02
Type and format constraints
Demonstrate type and format constraints in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 03
Prompt-schema alignment
Demonstrate prompt-schema alignment in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 04
Partial and streamed output handling
Demonstrate partial and streamed output handling in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 05
Parsing and validation
Demonstrate parsing and validation in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 06
Recovery from invalid output
Demonstrate recovery from invalid output in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 07
Nested and optional outputs
Demonstrate nested and optional outputs in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 08
Tool-output schema integration
Demonstrate tool-output schema integration in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 09
Provider capability boundaries
Demonstrate provider capability boundaries in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 10
Schema change compatibility
Demonstrate schema change compatibility in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 11
Constrained-output evaluation
Demonstrate constrained-output evaluation in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 12
Structured-output regression fixtures
Demonstrate structured-output regression fixtures in a focused Instructor example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course →
Learn the same ideas beyond Instructor.
These courses share topics with this one, so you can compare how each language or tool handles the same concept.
More in LLM agent and retrieval frameworks.
You have the curiosity.
Let’s turn it into capability.
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