WASEEM HABIB

I build AI products for the people inside a company — internal assistants, copilots and IT-operations automation. Enterprise AI that gets adopted, not just deployed.

Product and architecture for employee-facing AI: taking the AI platforms an enterprise already licenses, building first-party capability on top so they fit how teams actually work, publishing that as internal product, and driving adoption across go-to-market, sales, engineering and IT — then feeding what breaks back to the vendor. Shipped a three-layer assistant ecosystem that cut preparation work from hours to under 30 seconds per query at zero incremental license cost, and owned product definition for an agentic AI platform under FedRAMP High and CJIS constraints, where a wrong answer has legal consequences. Fifteen-plus years of enterprise systems underneath it, which is why I can specify an AI product rather than just describe one: I benchmark the models and build the prototype before I write the requirements.

Core Competencies

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.