Context Engineering for Developers
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 36m | 74.3 MB
Instructor: Deepak Goyal
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 36m | 74.3 MB
Instructor: Deepak Goyal
This course introduces you to the emerging skill of Context Engineering in AI. Learn how to dynamically manage and deliver relevant data, tools, and workflows to large language models for accurate and reliable outcomes. Explore techniques like smart retrieval, summarization and context quarantine. Designed for AI practitioners and prompt engineers aiming to build better AI agents and RAG pipelines.
Learning objectives
- Define context engineering and explain how it differs from prompt engineering.
- Identify failure modes in AI systems due to poor context handling.
- Design RAG-based pipelines for dynamic context retrieval.
- Apply summarization and pruning techniques to manage large inputs.
- Analyze real-world use cases where context engineering improves AI performance.