This project is a C++ mini–AI infrastructure simulation designed to demonstrate core object-oriented and systems-level design patterns commonly used in AI infrastructure, compute backends, and large-scale frameworks.
Zero-intrusion guard for LLM calls in dev: dedupe, cache, and protect AI requests across Node, browser, and Vite.
Provider-agnostic MCP control plane for managing connections, routing requests, and policy enforcement across AI vendors.
ACID transactions for AI agent tool calls. A Rust gRPC proxy that finds the step that really caused a failure, rewinds state in milliseconds, undoes side effects and gives the agent a one-line fix.
Cloud Execution • Platform Engineering • AI Infrastructure | Building secure, scalable, and automated cloud platforms.
IntentMesh is an open protocol and reference architecture for structured negotiation between autonomous software agents.
End-to-end AI deployment decision system combining real model benchmarking, system-level optimization, and infrastructure-aware trade-off analysis (latency, cost, energy, carbon).
ai-application-development, ai-infrastructure-development etc
Hands-on learning notes for AI Infrastructure & GPU high-performance computing
Secure Agent Governed Execution OS
Workload-scoped runtime enforcement for AI workloads. Deterministic governance at the workload boundary.
Interactive storage engineering and AI infrastructure labs: RAID, SAN, NVMe, GPU memory, RAG, simulators, and a hands-on network academy.
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