The 2026 evolution of prompt engineering: systematically designing the schemas, tools, retrieval pipelines, and memory that an LLM-based agent has access to. Co
Context engineering is the discipline that superseded prompt-tweaking: programmatically assembling everything a model sees, instructions, retrieved knowledge, tool schemas, memory, history, within token budgets, so behavior is reliable by construction rather than incantation.
The 2026 premium skill within AI engineering: as systems grow agentic, context architecture determines reliability, and practitioners who treat it as engineering are the ones senior teams fight for.
Scope: prompts are one component; context engineering owns the whole input surface, retrieval, tools, memory, history, assembled programmatically per request. It's systems design, not copywriting.
Stuffing: maximal context on every call, degrading both quality (attention dilution) and cost. Curated relevance with measured ablations beats volume every time.