Building AI Coding Agents for the Terminal: Scaffolding, Harness, Context Engineering, and Lessons Learned
This work provides a blueprint for robust autonomous software engineering for developers who prefer terminal-native AI assistance, potentially shifting the paradigm of AI coding assistance.
The paper introduces OPENDEV, an open-source, command-line coding agent designed for autonomous software development in the terminal. It addresses challenges like context bloat and reasoning degradation through a compound AI system, dual-agent architecture, lazy tool discovery, adaptive context compaction, and an automated memory system.
The landscape of AI coding assistance is undergoing a fundamental shift from complex IDE plugins to versatile, terminal-native agents. Operating directly where developers manage source control, execute builds, and deploy environments, CLI-based agents offer unprecedented autonomy for long-horizon development tasks. In this paper, we present OPENDEV, an open-source, command-line coding agent engineered specifically for this new paradigm. Effective autonomous assistance requires strict safety controls and highly efficient context management to prevent context bloat and reasoning degradation. OPENDEV overcomes these challenges through a compound AI system architecture with workload-specialized model routing, a dual-agent architecture separating planning from execution, lazy tool discovery, and adaptive context compaction that progressively reduces older observations. Furthermore, it employs an automated memory system to accumulate project-specific knowledge across sessions and counteracts instruction fade-out through event-driven system reminders. By enforcing explicit reasoning phases and prioritizing context efficiency, OPENDEV provides a secure, extensible foundation for terminal-first AI assistance, offering a blueprint for robust autonomous software engineering.