提示词工程、上下文工程都过时了，现在是 Harness Engineering 的时代

Core Insights - The article discusses the evolution of AI development practices from Prompt Engineering to Context Engineering, and now to Harness Engineering, emphasizing the importance of the environment in which AI agents operate [4][40][41] Group 1: Evolution of Engineering Practices - In 2023, Prompt Engineering was at its peak, focusing on crafting effective prompts for AI to deliver results [9] - By mid-2025, Context Engineering emerged, shifting the focus to designing dynamic systems that provide the necessary context for AI tasks [9][10] - As of February 2026, Harness Engineering was introduced, highlighting that the environment in which AI agents operate is crucial for their performance [11][12][13] Group 2: OpenAI's Experiment and Findings - OpenAI conducted an experiment with a team of engineers who delivered over 1 million lines of code without writing any human code, relying entirely on Codex Agent [15] - The experiment revealed that the most significant challenges lie in designing the environment, feedback loops, and control systems for AI agents [22][42] - The team learned that a well-structured documentation system is essential, evolving from a single large document to a more organized directory structure [17][18] Group 3: Framework of Harness Engineering - Birgitta Böckeler outlined a three-dimensional framework for Harness Engineering, which includes Context Engineering, Architectural Constraints, and Entropy Management [24][25][26] - Context Engineering ensures that agents receive the right information at the right time, while Architectural Constraints enforce boundaries through automated mechanisms [24][25] - Entropy Management addresses the degradation of the system over time, ensuring that the harness remains effective and does not become outdated [26] Group 4: Industry Adoption and Examples - Companies like Stripe and LangChain are implementing Harness Engineering principles, with Stripe's Minions system merging over 1,300 AI-generated pull requests weekly [28][29] - LangChain demonstrated a significant performance improvement in its coding agent by optimizing the harness without changing the underlying model [29][30] - The concept of Harness Engineering is being internalized by tool vendors, with MCP (Model Control Protocol) becoming a standard for agent tool access [31] Group 5: Future Directions for Engineers - The core responsibilities of engineers are shifting from writing code to designing environments that ensure reliable operation of AI agents [33] - Engineers are now focused on building documentation systems, defining business intents in machine-readable formats, and creating automated validation mechanisms [33][34] - The industry is recognizing the need for a deeper understanding of system design over mere coding speed, leading to a re-evaluation of team structures and roles [35][36]