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Achievement: Pair Extraordinairex2Achievement: Pull Sharkx4Achievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pair Extraordinairex2Achievement: Pull Sharkx4Achievement: YOLOAchievement: Quickdraw

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yshishenya/README.md

Hi there, I'm Yan 👋

AI Systems Architect & Engineer focused on autonomous agent runtimes, multi-agent orchestration, and prompt-to-UI workflows.

🚀 Featured Project

  • StitchFlow — Portable Stitch workflow turning prompts into UI directions, Tailwind-friendly HTML, and screenshots across Codex, Claude Code, OpenClaw, GitHub Copilot, and Gemini CLI.

🔭 Focus & Architecture

  • Autonomous Agent Architectures: Resilient agent runtimes, tool-calling pipelines, and multi-agent coordination.
  • Local & Hybrid Memory Systems: Cloud-independent, low-VRAM context stores using SQLite FTS5 and structured Markdown.
  • Enterprise Integrations: Connecting autonomous LLM agents with messaging APIs and CRM backends (WABA, APIs).

🛠 Tech Stack & Core Competencies

  • AI & Agents: Autonomous Runtimes, Tool Calling, Multi-Agent Workflows, LLM Orchestration
  • Memory & Storage: SQLite (FTS5), Vector-Free Context, Markdown Knowledge Graphs
  • Systems & Infra: Linux, Local GPU Optimization (NVIDIA RTX / Ampere)
  • Integrations: REST APIs, Webhooks, WhatsApp Business API (WABA), CRM Pipelines

⚡ Engineering Principles

  • Vendor-Neutral First: Prioritizing local, self-hosted memory and orchestration models to eliminate cloud API lock-in.
  • Resource Efficiency: Maximizing throughput and context precision while minimizing footprint.
  • Pragmatic Automation: Bridging the gap between raw LLM capabilities and reliable production workflows.

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  1. stitchflow stitchflow Public

    StitchFlow turns prompts into UI directions, Tailwind-friendly HTML, and screenshots across Codex, Claude Code, OpenClaw, GitHub Copilot, and Gemini CLI.

    JavaScript 14 1