# Context Engineering

Tutorials for prompt engineering, prompt optimization, and context construction.

### [Automatic prompt engineering](https://www.union.ai/docs/v2/union/tutorials/context-engineering/auto_prompt_engineering/page.md)

Easily run prompt optimization with real-time observability, traceability, and automatic recovery.

### [Text-to-SQL](https://www.union.ai/docs/v2/union/tutorials/context-engineering/text_to_sql/page.md)

Learn how to turn natural language questions into SQL queries with Flyte and LlamaIndex, and explore prompt optimization in practice.

## Subpages

- [Text-to-SQL prompt optimization](https://www.union.ai/docs/v2/union/tutorials/context-engineering/text_to_sql/page.md)
  - Ingesting data
  - From question to SQL
  - Vector indexing
  - Table retrieval and context building
  - SQL generation and response synthesis
  - Building the QA dataset
  - Schema extraction and chunking
  - Question and SQL generation
  - Validation and quality control
  - Optimizing prompts
  - Evaluation pipeline
  - Iterative optimization
  - Run it
  - What we observed
  - The bigger lesson
- [Automatic prompt engineering](https://www.union.ai/docs/v2/union/tutorials/context-engineering/auto_prompt_engineering/page.md)
  - Set up the environment
  - Prepare the evaluation dataset
  - Define models
  - Evaluate prompts
  - Optimize prompts
  - Build the full pipeline
  - Run it
  - Why this matters
  - Next steps

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**Source**: https://github.com/unionai/unionai-docs/blob/main/content/tutorials/context-engineering/_index.md
**HTML**: https://www.union.ai/docs/v2/union/tutorials/context-engineering/