Tag
context engineering
Context engineering is the practice of shaping what an AI system sees, remembers, and can act on: prompts, long-term memory, tool state, and access boundaries. It matters because reliable agents depend less on raw model size than on the context they are given and how it is managed.
3 articles
Why Prompt Engineering Is Dead for AI Agents
Prompt engineering is the wrong lever for AI agents; context engineering is what makes them reliable.
Context Is the New OS: Zettlab's Agent Computer
Zettlab is betting that personal data, not raw compute, will define the next PC. Its Agent Computer aims to run bots on your own context.
Harness Engineering: From Bridle to Operating System, The Missing Link in AI Agent Reliability
Harness Engineering is the discipline of designing external control frameworks for AI Agents. By integrating context engineering, architectural constraints, and garbage collection, it transforms unreliable large models into dependable production systems.