This content details a setup for running the Qwen3.6-35B-A3B model locally on a MacBook Pro M2 Max. It describes the integration with the `pi` coding agent via `llama.cpp` and `llama-server`, including configuration parameters and command line setup.
This project introduces a local coding agent that leverages Large Language Models (LLMs) to delegate specific tasks, particularly tool calls, to more specialized small AI models. It aims to improve efficiency and modularity in AI-powered development by distributing workloads.
A user is considering switching from Opus 4.7 to Qwen-35B-A3B as their daily coding agent and is seeking community experiences. They question if Qwen-35B-A3B will suffice for most tasks, acknowledging Opus might have an edge in complex reasoning, running on an M5 Max 128GB.
O autor compartilha Kon, seu agente de codificação de IA, que funciona bem com modelos locais para tarefas simples. Ele é notável por seu prompt de sistema pequeno, ausência de telemetria, compatibilidade com os melhores modelos locais e provedores populares, além de uma base de código simples e recursos avançados.
The user is seeking help to set up the Claude Code agent for local development, specifically with llama.cpp and the Qwen3.6-35B-A3B model, as they are encountering difficulties. They are asking for guidance, pointers, or suggestions for alternative tools like pi.dev.
The user asks what hardware (around $20k, e.g., RTX 6000 GPUs) would be needed to set up a local coding agent and go completely off the social grid. The question also touches upon the role of the AI model in this setup.
The author expresses excitement about DeepSeek's Native Coding Agent, an AI tool designed to offer high caching and low costs for scaling projects. After discovering it in a developer forum, the author explored its potential, finding its promise of faster and cheaper coding appealing.
The article explains how CodeVibe built zero-knowledge end-to-end encryption for its mobile AI coding agent companion. It details the cryptographic protocol using well-audited primitives to protect prompts, code, and responses across multiple devices.
This article details how to set up a free, open-source coding agent locally in just 10 minutes, emphasizing data privacy and eliminating recurring costs. It leverages tools like Ollama to run AI models directly on the user's machine, enabling code reading, writing, and command execution.
O autor analisou o código-fonte de Cline, um popular agente de codificação open-source, destacando achados impressionantes e preocupantes. Uma crítica principal é a classe 'Task' de 3.756 linhas, considerada um 'God Object' por misturar muitas funcionalidades distintas.
O autor transformou um MacBook M1 em um agente de codificação de IA 100% offline, sem custos de API ou conexão à internet, alcançando uma experiência similar ao GPT-4. Ele detalha o processo de compilar `llama.cpp` com Metal, usar `Gemma-4 26B` e integrar ao OpenCode para um fluxo de trabalho autônomo e local.