ABOUT ME
WASEEM HABIB
Building production agentic AI systems and Model Context Protocol (MCP) integrations for enterprise and public safety. Bridging the gap between AI research and deployed infrastructure.
Architecting the stack where agentic AI meets real-world operations — low-latency voice pipelines, multi-agent orchestration in production, and RAG systems with citation-grade accuracy. Focused on the LLM OS thesis: how MCP, tool registries, and trust layers are reshaping enterprise AI. Orchestrated partner-driven deals across the GSI ecosystem including FIFA 2026 and LA Olympics 2028. Enabled 100+ architects across GSI partners.
waseem@qbitloop.comCore Competencies
CAREER JOURNEY
DASHBOARDS
ops.qbitloop.com
open_in_newEnterprise MLOps research hub — 7-layer reference architecture, Visa & Goldman case studies, inference economics, and multi-agent protocols (MCP/ACP/A2A).
The Crow Code
open_in_newMarketplace for Claude Code skills, MCP servers, and AI tools. CLI-first discovery and installation for AI coding agents.
HIGHLIGHTED WORK
SIDE PROJECTS
RealtimeVoice
ASR benchmark proving NVIDIA Nemotron is 21x faster than Whisper (43ms vs 916ms). Reproducible Colab notebooks.
nvidia-nim-rag-demo
Production-ready RAG with NIM API, FastAPI, Streamlit, pgvector. Reference implementation.
Jensen Insights Compass
AI-powered keynote analyzer for NVIDIA content. YouTube transcript extraction and analysis.
QbitLoop Code CLI
Memory-aware AI CLI with 13 bundled plugins. Personal AI development toolkit.
MLX-OCR
Apple Silicon optimized OCR using MLX-VLM. Fast local document processing.
Digital Twin Template
7-domain personal AI framework. Template for building your own digital twin.
ai-infra-advisor
AI infrastructure TCO calculator. Compare cloud vs on-prem costs with DGX pricing.
roi-calculator
AI project ROI calculator with industry benchmarks and cost models.
IDEAS I'M EXPLORING
The LLM OS Thesis
Tracking how MCP, tool registries, and trust layers are forming the actual operating system for AI. Writing a multi-part series on Medium.
Agent Trust & Governance
The missing layer between silicon and applications: identity, provenance, audit trails, and kill switches for autonomous agents.
Silicon Split Analysis
Training stays NVIDIA-dominant, inference is fragmenting (Cerebras, Groq, custom ASICs). Tracking the economics of the split.
Voice-First RAG
GPU-accelerated ASR (Nemotron 43ms) with RAG for hands-free document querying. Sub-second voice-to-answer pipeline.
Production Agent Teams
Five-agent meeting prep system in production. Documenting what actually works: sequential beats parallel, role specificity matters.