Shift focus from AI hype (latest models, vector DBs, agentic frameworks) to high-leverage activities that actually improve product quality. Use this when an AI feature is underperforming, when the team is stuck in a "research loop," or when planning the roadmap for a new AI application.
Quickly install ai-app-performance-optimization AI skill to your development environment via command line
Source: samarv/shanon.
To build successful AI applications, move beyond the "ideal crisis" of chasing every new research paper or model update. Real performance gains come from traditional product engineering applied to AI: data quality, workflow optimization, and user-centric evaluation.
The Optimization Pivot Differentiate between activities that offer marginal gains (The Hype) and those that drive exponential product quality (The Reality).
Optimize Data for Retrieval (RAG) If using Retrieval-Augmented Generation (RAG), the biggest lever for quality is not the retrieval algorithm, but how the data is prepared.
Shift focus from AI hype (latest models, vector DBs, agentic frameworks) to high-leverage activities that actually improve product quality. Use this when an AI feature is underperforming, when the team is stuck in a "research loop," or when planning the roadmap for a new AI application. Source: samarv/shanon.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/samarv/shanon --skill ai-app-performance-optimizationShift focus from AI hype (latest models, vector DBs, agentic frameworks) to high-leverage activities that actually improve product quality. Use this when an AI feature is underperforming, when the team is stuck in a "research loop," or when planning the roadmap for a new AI application. Source: samarv/shanon.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/samarv/shanon --skill ai-app-performance-optimization Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/samarv/shanon