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Deep dive into Reasonix coding agent: how it achieves 99% DeepSeek cache hit rate, cutting API costs to 1%. Covers setup, four conversation modes, MCP support, and more.

GitHub Trending Aug 5: AI Agents shift from demos to production with new projects for state management, long-term memory, skill systems, and security.

An insider's analysis of China's four AI labs — Qwen, DeepSeek, Moonshot, and Ling — revealing their distinct strategic bets on distribution, architecture, long-termism, and serving cost.

Redis creator antirez open-sources ds4, a pure C local inference engine for DeepSeek 4 Flash and PRO with native Metal, CUDA, and ROCm support, earning nearly 20K GitHub stars.

How to deploy LLMs locally on AMD RX 7800 XT 16GB for trading bots: ROCm ecosystem, 7B-14B model picks (Qwen2.5, Llama 3.1), Ollama/LM Studio setup, and system architecture design.

A developer built a pure C99 inference engine that runs the 1.56TB Kimi K3 model on 8GB RAM using MoE sparsity and NVMe on-demand loading—no GPU, 176KB binary.

A practical guide to consolidating scattered automation scripts into a local AI Agent hub. Covers Function Calling, Ollama+Qwen2.5 deployment, tool orchestration architecture, and a complete implementation roadmap.

A senior developer admits 95% of work is done by Claude Code, with 10x productivity gains. From coding to architecture, AI is eroding programmers' core skill moats. Deep analysis of AI coding's impact on tech employment.

GitHub Trending Aug 2: Agent-Reach enables zero-cost web access for AI Agents, while DeepSeek ecosystem explodes with ds4 inference engine and Reasonix coding Agent.

Deep analysis of the real cost of serving a 2.8 trillion parameter model. From MoE sparse activation to batching scale effects and inference optimization, revealing why model size and serving cost are less correlated than assumed.

A deep dive into building and self-hosting a code review AI Agent from scratch, covering architecture design, context management, model selection, and noise control.

A systematic learning path for understanding the Kimi K3 technical report, covering MoE, MLA, distributed training, and modern post-training techniques.

An in-depth analysis of why AI costs keep rising—inference expenses, premium model pricing, and context bloat—plus practical optimization strategies including model cascading, caching, and self-hosting.

In-depth analysis of DeepSeek-V4-Flash model's product positioning and technical approach. Examining lightweight trends through the Flash naming, MLA attention mechanism, MoE architecture evolution, and implications for the open-source AI ecosystem.

In-depth analysis of DeepSeek-V4-Flash model's positioning and technical path. Exploring the lightweight trend behind the Flash naming, MLA attention, MoE architecture, and its significance for open-source AI.

Deep analysis of DeepSeek V4 Flash 0731 across intelligence, performance, and price dimensions, exploring how this Chinese LLM delivers extreme cost-performance to reshape the AI industry.

OpenAI's GPT-5.6 series sees massive price cuts—Luna drops 80% to $0.20/M input tokens. Deep analysis of the AI price war's tech drivers, competitive landscape, and impact on developer costs and model selection.

OpenAI's GPT-5.6 series sees major price cuts with Luna dropping 80% to $0.20/M input tokens. Analysis of the AI price war's technical drivers, competitive landscape, and impact on developer costs.

OpenAI launches GPT-5.6 with 80% price cuts on its Luna model series, surpassing DeepSeek on the price-performance curve. Analysis of the tech logic, developer impact, and AI price war trends.

OpenAI releases GPT-5.6 with 80% price cuts on Luna models, overtaking DeepSeek on price-performance. Analysis of the tech logic, developer impact, and AI pricing trends.