Context engineering, a term popularized in June 2025 by Shopify CEO Tobi Lutke, is the practice of designing everything a language model sees before it generates a response, including system instructions, conversation history, retrieved documents, tool definitions, and memory. Six days later, Andrej Karpathy amplified the concept, describing it as “the delicate art and science of filling the context window with just the right information for the next step.” Within months, Gartner declared 2026 “the year of context.” A 2026 State of Context Management Report found that 82% of IT and data leaders agree prompt engineering alone is no longer sufficient to power AI at scale, and 95% of data teams plan to invest in context engineering training during 2026. Prompt engineering, which focuses on the instruction layer, has been absorbed into context engineering, which optimizes all six layers of the context window simultaneously. Karpathy’s analogy states, “The LLM is like the CPU, and its context window is like RAM.” In 2026, agents run multi-step workflows across dozens of tool calls, and the instruction is 5% of what the model sees, while the other 95% is context.