From Prompt to Pipeline
Turning a clever prompt into a system you can operate
A book by Alpesh Nakrani
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- Pages
- 98
- Chapters
- 12
- Format
- PDF · 20.0 MB
What's in the book
Every AI feature starts as a prompt that worked once. This manual is the unglamorous middle: versioning prompts, handling the long tail of inputs, building the observability that turns a clever result into a system someone can run on call.
A prompt that works in the playground is not a product. The path from a good result to a system that holds at 3am.
Table of contents
PDF page- INTIntroduction: When a Demo Prompt Started Acting Like a Product9
- 01The Long Tail Waiting Behind the Demo15
- 02A Prompt Registry Gives the String an Owner21
- 03Input Policy: What You Accept Before the Model Sees It27
- 04Output Contracts: What You Accept Before the Customer Sees It34
- 05Fixtures and the Regression Suite a Prompt Needs40
- 06Review Is Not Optional for a Customer-Facing Prompt46
- 07Rollback and the Release Note Nobody Wrote52
- 08Observability for a System Made of Sentences58
- 09The Model Upgrade You Did Not Choose65
- 10Where a Prompt Chain Becomes a Pipeline71
- 11Ownership and the On-Call Rotation for a Prompt77
- 12The Day an Experiment Becomes a Workflow83
- ENDConclusion: Prompts Are Operational Assets, Not Lucky Strings89
The full chapters, illustrations, and reference material are included in the downloadable PDF.
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