Filter by tags and quickly find posts.
In computer science, this is called pruning. Through a complete iterative process of building a TikTok video summarization tool, learn how to optimize AI workflows to the extreme using pruning thinking.
Nine efficient principles summarized from four prompt engineering whitepapers: from efficiency formulas to pipeline splitting, from XML tags to parameter configuration—transforming prompts from one-time conversations into reusable assets.
Explaining the version numbering logic of Google's Gemini Image series (Nano Banana), and why Nano Banana 2 didn't surpass Nano Banana Pro.
From Plan mode to Sub-fractal Architecture, from MCP retrieval to Agent collaboration—seven battle-tested tips to double your Claude Code efficiency.
After watching OpenAI CEO Altman's live interview: the future of software engineers, GTM bottlenecks, competitive moats for AI products, GPT-5 writing issues, and the most critical skills in the AI era.
Writing a Skill requires planning first. Using daily digest scraping as a case study, this article breaks down how technical research can create order-of-magnitude improvements in Skill stability, speed, and Token consumption.
From selecting a Clash distribution to tuning Tun stack mode, I troubleshot the proxy speed issue step by step and finally pinpointed the performance bottleneck caused by DNS resolution going through gVisor.
X officially open-sourced the x-algorithm project, completely exposing the core code of its recommendation system. An in-depth analysis of positive/negative weight parameters and Grok transformer-driven recommendation mechanism.
