Use Qwen3.6 Right Way – Send It to Pi Coding Agent and Forget
Use Qwen3.6 with pi.dev harness and exa web search to handle coding, maintenance, and research tasks; it can replace Perplexity for many use cases.
Test Qwen3.6 with pi.dev harness on a small project to evaluate performance for coding and research tasks.
Summary
The author demonstrates how to pair the 35B Qwen3.6 model with the pi.dev harness and exa web search to create a powerful local LLM workflow. By connecting the harness to a browser extension, the setup can browse the web in real time, enabling tasks such as coding, maintenance, and research. The author reports that 80% of their use cases—coding in Python, Rust, and C++, Linux administration, and web research—are handled by this configuration. Qwen3.6, when combined with exa web search, outperforms Perplexity for many search‑heavy tasks. For complex planning, the author delegates to Kimi2.6 while the coding itself is handled by Qwen3.6. The workflow is described as “send it to pi coding agent and forget,” implying minimal manual intervention. The harness’s ability to integrate local LLMs with external services is highlighted as a key advantage. Overall, the post serves as a practical guide for developers looking to leverage Qwen3.6 in a local, browser‑enabled environment.
Key changes
- Qwen3.6 35B model integrated with pi.dev harness for local LLM execution.
- pi.dev harness connects to exa web search and agent-browser extension for real‑time browsing.
- 80% of the author’s use cases (coding, maintenance, web research) are handled by this setup.
- Coding support includes Python, Rust, and C++ generation.
- Maintenance and administration tasks focus on Linux machines.
- Web research performance surpasses Perplexity when combined with exa web search.
- Kimi2.6 is used for complex planning tasks delegated to the LLM.
- The author recommends “send it to pi coding agent and forget” as a workflow.