I've Shipped 113 Local-AI Projects in 18 Months — Here Are the Five Architecture Patterns That Actually Survived
The author has shipped 113 local-AI projects over 18 months using only local LLM inference with Gemma 4 and Ollama, avoiding cloud APIs and agent frameworks. Five recurring architecture patterns emerged as critical to project success, emphasizing simplicity, determinism, and structured outputs. These patterns focus on treating the LLM as a function call, precomputing data, and constraining outputs to improve reliability.
- ▪The author developed 113 local-AI projects under the GitHub identity kennedyraju55, all running on local LLM inference without cloud dependencies.
- ▪Each project uses a minimal function to call the LLM, bypassing complex agent frameworks like LangChain and LlamaIndex.
- ▪Deterministic functions handle data processing before LLM inference, with the LLM used only for interpretation on pre-structured inputs.
- ▪Output constraints are consistently applied to ensure reliable, parseable responses from the LLM.
- ▪The five surviving architecture patterns emphasize control, simplicity, and leveraging LLMs for their strengths in comprehension rather than computation.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3875587) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Nrk Raju Guthikonda Posted on May 2 I've Shipped 113 Local-AI Projects in 18 Months — Here Are the Five Architecture Patterns That Actually Survived #ai #architecture #llm #opensource I've Shipped 113 Local-AI Projects in 18 Months. Here Are the Five Architecture Patterns That Actually Survived Tags: ai, llm, architecture, opensource A weird thing happens around project number forty. You stop being excited about model picking. You stop arguing about which framework to use.
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