Context engineering
The practice of structuring and managing contextual information to guide AI systems toward high-quality, production-ready outputs in software development. It bridges the gap between raw AI code generation and professional development standards by establishing clear environmental constraints, data pipelines, and process integration.
Key developments
- BMAD method for coding: A universal AI agent framework for Agile AI-driven development, introduced via video (see 2026 04 14 BMAD method for coding).
- Addresses evolution from simple AI coding to sophisticated context engineering (tools: Cursor, claude-code)
- Prevents non-production-ready software by integrating full software development processes
- [[concepts/highl
- Evolution to Agent Harness Engineering: Represents the next phase beyond Prompt Engineering and Context Engineering, focusing on the structural orchestration of AI agents]] rather than just input context.
- Differentiates itself by managing the execution environment and agent workflows rather than merely curating input data.
- See detailed analysis in Agent Harness Engineering: Evolution from Prompt and Context. for historical context and significance (Source: Caleb Writes Code, video).