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Context Engineering: The Next Frontier Beyond Prompt Engineering

This article explores how designing the right informational environment is the key to building sophisticated, enterprise-ready AI application and agents in 2026.

By
The deepset Team
Long-Context LLMs and RAG
Context windows are growing. What does that mean for retrieval augmented generation (RAG)?
AI Trends
Building Product-Focused AI Development Teams
A blueprint for assembling and leading AI talent
AI Best Practices
GraphRAG: Using Knowledge Networks to Improve Retrieval and Generation
Let’s talk about the new graph-based approach to processing complex datasets for context-rich LLM responses
AI Trends
AI Architecture
Compound AI: Shifting from Models to Systems
Why composability and flexibility are the way forward in AI system design
AI Best Practices
AI Trends
Intelligent Document Processing with LLMs: Real-World Use Cases
LLM-powered IDP in action: Three real-world examples of intelligent automation of complex reports and portfolios
AI Architecture
Solutions
How to Fast-Track AI-Driven Innovation with Haystack Enterprise Platform
Discover why the Haystack Enterprise Platform is a scalable, accessible, and simple option for implementing applications with LLMs-and how it can benefit your product development lifecycle
Product
AI Earnings Call Analysis with RAG Systems
Learn how we set up a RAG system to extract insights from live earnings calls of the biggest companies in tech and financial services.
Solutions
Measuring LLM Groundedness in RAG Systems with Evaluation Metrics
Improve LLM security, trust, and observability with our pioneering Groundedness metric for RAG applications
Product
AI Best Practices

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