Overview
What this challenge is about.
Design a JSON prompt with schema and few-shot examples to extract invoice fields, then evaluate accuracy. Earn a verifiable certificate.
The scenario
The startup (Series A, around 40 staff, processes about 80,000 invoices per month for paying customers) has SLAs that promise sub-2 percent extraction failure; the current 12 percent rate is its top customer-success ticket source.
The Brief
What you'll do, and what you'll demonstrate.
Redesign an invoice-extraction prompt with JSON-mode + Schema + targeted few-shot examples to meet a sub-2 percent failure SLA.
Earning criteria — what you'll demonstrate
- Use JSON-mode and JSON Schema to enforce structured LLM outputs
- Mine real failure logs to curate few-shot examples that target known failure modes
- Design an evaluation harness for extraction quality with multiple metrics
- Iterate prompt design under a production SLA
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Prompt Engineering
Master · Generative Ai
Strong alignment
This challenge maps to Prompt Engineering at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Structured Output
Apply structured output to solve real industry problems and demonstrate production-level capability.
- Json Schema
Apply json schema to solve real industry problems and demonstrate production-level capability.
- Few Shot Prompting
Apply few shot prompting to solve real industry problems and demonstrate production-level capability.
- Prompt Evaluation
Apply prompt evaluation to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Failure Analysis
Apply failure analysis to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Prompt Engineer
Designing a structured-output prompt that meets a production SLA on real customer data is the day-one job of a prompt engineer at any AI product startup.
This challenge sharpens
- structured-output
- json-schema
- few-shot-prompting
AI Engineer
Building the prompt-plus-eval-harness boundary between the model and the product is the AI-engineer skillset hiring managers screen for.
This challenge sharpens
- prompt-evaluation
- python
- failure-analysis
NLP Engineer
Information extraction with field-level accuracy and structured outputs is core NLP-engineer work in B2B AI.
This challenge sharpens
- structured-output
- prompt-evaluation
- failure-analysis