AI · Article or course
Building Effective AI Coding Agents for the Terminal: Scaffolding, Harness, Context Engineering, and Lessons Learned
A research paper formalizing architecture and context engineering for CLI coding agents.
This arXiv paper analyzes the shift from IDE plugins to autonomous terminal-native coding agents, introducing the open-source Rust agent OPENDEV as a reference blueprint. It outlines practical design patterns for context management, dual-agent planning versus execution splits, and safety harness design to prevent context bloat and reasoning degradation during long-horizon tasks.
What it's for
- Study architectural blueprints for building autonomous command-line coding agents
- Implement adaptive context compaction to prevent prompt bloat in long agent runs
- Design multi-agent orchestration systems separating planning from tool execution
- Address instruction fade-out using event-driven system reminders in LLM workflows
Features
- Four-level orchestration hierarchy spanning session, agent, workflow, and model routing
- Dual-agent architecture separating high-level planning from concrete execution
- Adaptive context compaction that progressively condenses older observations
- Lazy tool discovery to avoid overwhelming the model context window
- Cross-session automated memory storage for project-specific context
- Event-driven system reminders designed to counteract instruction fade-out
- Case study and reference implementation based on the OPENDEV CLI agent written in Rust
Pricing
Free
Details
- Type
- Article or course
- Category
- AI
- Topic
- AI Coding Agents
- Open source
- Yes
- Platforms
- Web
- For
- Software engineers and AI developers building autonomous coding agents or CLI developer tools.
- Alternative to
- Claude Code, Codex CLI
- Tags
- research, arxiv, agents, context engineering, developer tools, rust
Why it was saved
- @omarsar0: Formalizes design patterns from Claude Code/Codex-style agents: compound AI architecture, dual-agent planning/execution split, context management strategies — directly useful for anyone building coding agents.
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Updated