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@MMEHDI0606

Free

Agentic AI pipelines that work in production

FreeFree tier
Type
Open Source

About @MMEHDI0606

Muhammad Mehdi (MMEHDI0606) is a Computer Science student and AI developer who builds production-grade AI systems, focusing on Agentic AI pipelines, LLM integration, and prompt engineering. He has contributed to the antigravity-awesome-skills repository, a library of 1,340+ agentic skills for various AI tools including Claude Code, Cursor, Codex CLI, Gemini CLI, and Antigravity. His work includes automated marketing solutions, voice agents, lead generation workflows, and multi-agent system coordination. He maintains versioned prompt libraries with fallback behaviors and emphasizes reliability in production AI deployments.

Key Features

Production-grade LLM evaluation and regression testing
Versioned prompt libraries with fallback behaviors
Multi-agent system coordination
Agentic AI pipeline creation for automated marketing (LLMs + GANs)
CI/CD and cloud fundamentals for AI systems
Integration with Claude API, MCP, and n8n
Installable library of 1,340+ agentic skills with CLI

Pros & Cons

Pros
  • Contributed to a 26,500-star open-source project (sickn33/agentic-awesome-skills)
  • Ranked 3rd nationally in the All Pakistan Prompt Engineering Competition
  • Focus on production reliability and real-world deployment
  • Practical experience with multi-agent systems and evaluation

Best For

Automated brand campaigns using LLMs and GANsVoice agent developmentLead generation workflowsSocial media optimizationAutomated AI system deployment for marketing

FAQ

What is the antigravity-awesome-skills repository?
A forked repository providing an installable GitHub library of 1,340+ agentic skills for tools like Claude Code, Cursor, Codex CLI, Gemini CLI, and Antigravity. It includes an installer CLI, bundles, workflows, and official/community skill collections.
What AI tools does this developer work with?
The developer works with Claude API, MCP, n8n, and various AI coding assistants. He also builds AI systems using LLMs and GANs in production.