Activity: Consultancy and contribution to enterprise › Expert advice provision
Description
The paper "Context Engineering: Beyond Prompting AI" argues for a paradigm shift from the reactive practice of prompt engineering (crafting a single, perfect input) to the proactive discipline of context engineering (architecting the entire information ecosystem an AI inhabits). Context engineering is essential for building reliable, scalable, and production-grade AI agents by systematically managing the model's "working memory" (the context window), which includes system instructions, tool outputs, and retrieved data (RAG). A failure to manage this dynamic environment leads to predictable issues like Context Poisoning and Context Distraction; the solution involves an "Engineer's Toolkit" of techniques such as Summarisation, Pruning, and Offloading (Scratchpads) to balance fidelity, cost, and latency, ultimately moving the industry from focusing on the single question asked to architecting the entire world the AI knows.
Resulting in follow workshops on context engineering and AI automations.