OpenCode + Ollama: Claude Code Failed. This Works. (Full Setup) — AI Summary

Summary

Claude Code's heavy system prompts often overwhelm local hardware, causing hallucinations and tool failures. By using OpenCode as a lightweight harness with Ollama, you can run powerful open-source models like Qwen 2.5 locally while maintaining high instruction-following performance for complex coding tasks.

Key Topics

• System Token Overhead: This represents the non-productive tokens consumed by system prompts and tool definitions. In local setups, this significantly reduces the space available for actual code logic, leading to degraded model performance.
• Incremental Agent Prompting: By segmenting a project into phase files, you keep the agent's context window clean and focused on immediate goals, which prevents hallucination and logic errors in complex codebases.
• Model-Harness Compatibility: Not all frameworks are tuned for local models. A 'harness' needs to be lightweight enough to allow the model to interpret instructions clearly, otherwise the system tools will drown out the actual coding tasks.

Key Takeaways

• Install OpenCode and connect it to your local Ollama instance.
• Segment your project tasks into small files.