Industry professional — building with AI in production

At the frontier
of Agentic AI

I'm Arun — working with Generative AI, Agentic systems, and Multi-Agent architectures day in and day out. I share what's actually happening at the edge.

Agentic AI LLM Engineering Multi-Agent RAG Systems MCP Protocol A2A Claude / GPT-4o AI Workflows

Areas of deep focus

Not surface-level AI — the architectures and systems reshaping what's possible.

01

Agentic AI

AI systems that autonomously plan, reason, and execute multi-step tasks — from tool-using loops to self-correcting pipelines that actually work in production.

ReActTool UsePlanningSelf-Reflection
02
🧠

Generative AI & LLMs

Foundation models, RAG architectures at scale, context engineering, fine-tuning strategies, and GenAI applications that move past the demo stage.

RAGFine-tuningClaudeGPT-4o
03
🔗

Multi-Agent Systems

Orchestrating networks of AI agents that collaborate, debate, and specialize. MCP, A2A, and swarm architectures — the next layer of intelligence.

OrchestrationMCPA2A ProtocolSwarm
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🛠️

AI Infrastructure

The production stack behind real AI — vector databases, embedding pipelines, context management, evals, and the LLMOps tooling that keeps it all from breaking.

Vector DBLLMOpsEvalsTracing

AI Explorations

Deep dives from inside the industry — no fluff, no beginner hand-holding.

AI is moving fast.

The developments that are actually changing how we build AI systems — not hype, real shifts.

Agentic2025

Agent-to-Agent Communication (A2A)

Google's A2A protocol lets AI agents discover each other and collaborate across different systems — a foundational step toward interoperable AI networks that span vendors and platforms.

Protocol2025

Model Context Protocol (MCP)

Anthropic's open standard for connecting AI models to tools, data, and APIs is rapidly becoming the industry default — the "USB-C" layer that every serious AI system will eventually use.

Reasoning2025

Long-Horizon Reasoning

Models like o3 and Claude Opus now sustain multi-step reasoning over hours of work — unlocking software engineering, research synthesis, and complex planning tasks previously out of reach.

Memory2025

Persistent Agent Memory

Agents maintaining context across sessions using episodic, semantic, and procedural memory layers. The shift from one-shot tools to continuous AI collaborators is happening now.

Computer Use2025

Vision + Action Agents

Computer-use agents (Claude, Operator, Gemini) that see screens and take real actions — collapsing the gap between AI understanding and execution across any software interface.

Infra2025

LLMOps Matures

Productionizing AI now requires serious tooling: evals, tracing, red-teaming, prompt versioning, cost optimization. LangSmith, Braintrust, and Weave are becoming real engineering infrastructure.

Let's talk AI.

Whether it's Agentic AI architecture, GenAI implementation, corporate AI strategy, or where the field is heading — I'm open to conversations that go deep.