Blog
Systems thinking applied to AI infrastructure.
Architecture-first blog posts on production challenges. How real teams build durable agents, secure workflows, observable systems, and reliable AI infrastructure that doesn't break under load.
// DEEP ARCHITECTURE JOURNAL
Featured Systems Breakthroughs
Durable specification sheets detailing Manoj's actual production pipelines. Built with real telemetry metrics, code files, and verification evaluations.
Building a Private AI Home Lab API Gateway
A production‑shaped walkthrough of my local AI gateway: Cloudflare Tunnel, FastAPI, OpenAI‑compatible routes, Ollama 0.30.6, qwen3.5:9b, API‑key auth, concurrency guardrails, and synchronized documentation with the architecture guide.
Durable Agent Architecture with LangGraph v1
Production agents crash. When they do, you need checkpoints. This is how real teams build resumable workflows that survive restarts, approval delays, and API failures without replaying unsafe work.
MCP Security Architecture & Enterprise Guardrails
MCP is elegant for tool integration, but it concentrates risk. Here's how to architect tool permissions, isolation boundaries, governance policies, and audit logs before you wire enterprise systems into agents.
GenAI Observability with OpenTelemetry Traces
Token counts lie. Agent failures are loud but opaque. This is how production teams use OpenTelemetry semantic conventions to trace multi-agent workflows, isolate failures, and debug without guessing.
Context Engineering for Enterprise RAG
Longer context windows changed RAG architectures completely. Here's how production teams layer system instructions, memory, evidence, and governance to build retrieval systems that actually work.
FastAPI AI Backends for Background Reasoning
Reasoning models need backend architecture. Your API shouldn't hold an HTTP connection hostage while the model thinks. Here's how to do async reasoning right.
// DISTRIBUTION CHANNELS
Medium & LinkedIn Synthesis
Manoj publishes general architecture guidelines and supercomputing reports to Medium, and aggregates stateful agent breakdowns to LinkedIn.
Desktop AI Supercomputing is Here: A Practical Look at NVIDIA DGX Spark™ for Startups
The Future of AI: Building Agent-to-Agent Communication Systems
Building an AI-Powered Stock Analysis Pipeline with LangGraph, DeepSeek, and Ollama
Building a Real-Time AI Agent with LangChain, LangGraph, and Open Source LLMs using Ollama
Advanced Retrieval-Augmented Generation (RAG) with LangChain, LangGraph, and AI Agents
Advanced Agent Functionality with Ollama and LLAMA 3 in LangChain
Extracting Information from Images with OCR, Vision AI, and Language Models
Local Image Understanding with OpenSource LLaVA and Ollama
React Testing Library: Portal Modal
Replay.io: A Game-Changing Tool for Web Developers
Cypress 10 — As Frontend or JavaScript Engineer
Manoj's LinkedIn Engineering Thread Hub
Manoj shares technical solutions diagrams, RAG pipeline evaluation traces, and platform deployment topographies directly with a 2.8K+ strong developer audience.
Connect & Review LinkedIn FeedWork With Me
Building systems that matter? Let's talk.
Bring the hard system constraint: retrieval quality, agent failure modes, latency, evaluation, deployment topology, or technical market education.