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Developer Ditches Local LLMs for Cloud Model After Ollama Bug Derails Infra Agent Build

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A developer building a lightweight, local-first infrastructure monitoring agent using PicoClaw encountered an undocumented Ollama bug related to Qwen3's default 'thinking' mode, which caused the model to reason in circles instead of executing clean tool calls. Several local models, including Gemma4 and Qwen3 variants, were stress-tested specifically for tool-calling reliability rather than conversational quality, but hallucination — not raw capability — proved to be the critical blocker. Docker was also abandoned early in the setup after networking conflicts between a local Ollama instance and a tunneled cloud endpoint created more complexity than it resolved. Ultimately, the developer settled on DeepSeek V4 Flash accessed via a self-hosted LiteLLM proxy as the Tier 3 cloud fallback, prioritizing reliability for unattended infrastructure tasks. The project highlights a broader tension between the appeal of fully local AI agents and the practical reliability demands of running automated tooling near production systems.

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Developer Ditches Local LLMs for Cloud Model After Ollama Bug Derails Infra Agent Build · ShortSingh