The New Skill in AI is Not Prompting, Itās Context Engineering
Context Engineering is the new skill in AI. It is about providing the right information and tools, in the right format, at the right time.
Research Resource Collection
Summary
The Awesome-Context-Engineering repository curates a comprehensive collection of papers, frameworks, and implementation guides on context engineering for large language models (LLMs) and AI agents, spanning from prompt design to productionāgrade systems.
Highlights
- Curated list of hundreds of academic papers and openāsource projects related to context engineering, retrievalāaugmented generation, and memoryāaugmented LLMs.
- Covers formal definitions, system architectures, scaling strategies, and integration of structured data for dynamic prompting.
- Highlights practical challenges such as evaluation metrics, enterprise deployment, and agent communication protocols.
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Context
Audience
Researchers, machine learning engineers, and developers building or studying contextāaware LLM applications
DomainArtificial Intelligence / Large Language Models
Formatopenāsource repository (GitHub)
Accessfree online
Source Overview
The repository provides a comprehensive survey and resource collection on context engineering for large language models, covering its shift from static prompting to dynamic, context-oriented AI systems.
It details formal definitions, system architectures, scaling methods, structured data integration, and current challenges, including practical system evaluation and enterprise deployment. The included papers and frameworks address foundational memory systems, retrieval-augmented generation, and agent-based communication for production-grade AI applications.
Topics
Related
Prompt EngineeringRetrievalāAugmented GenerationLLM Memory SystemsAI Agent FrameworksProduction AI Infrastructure
