Pranav Ganesh Pranav1405ML

const pranav = {
    role: "CS Student → Systems Engineer",
    focus: ["Backend", "Systems", "AI Infrastructure"],
    philosophy: "Build it. Break it. Understand it.",
    currently: "Going deeper, not wider.",
    goal: "Understand computing from React to registers."
};

I don't collect frameworks — I study how things are built.

CS student building backend systems, AI infrastructure, and low-level computing projects. My work spans from full-stack applications down to cycle-accurate CPU simulation. Everything I build is driven by a single question: how does this actually work?

⚡ What I've Built

Not tutorials followed — systems designed, architected, and shipped.

🔍 Cortex — AI Search Engine

A Perplexity-inspired search engine — not a chatbot wrapper, an actual retrieval pipeline.

Built an end-to-end AI search system that takes a user query, retrieves real web sources, embeds and chunks content into vector storage, performs similarity search, and synthesizes answers with source attribution via LLM.

Query → Web Retrieval → Embedding → pgvector Search → LLM Synthesis → Cited Answer

🤖 Coding Agent

A CLI agent that turns an LLM into an iterative, tool-using engineer with persistent memory.

Designed a multi-step autonomous coding agent — it reasons about tasks, selects tools, reads/writes files, executes code inside isolated Docker containers, observes results, and iterates. State persists across sessions via SQLite.

Prompt → Agent Reasoning → Tool Call → Docker Execution → Observation → Loop

🔧 CPU Simulator

A cycle-accurate CPU simulator — computing understood from first principles.

Built a custom microarchitecture simulator from scratch: instruction set design, data paths, control signal generation, and cycle-accurate execution. Not a toy — a tool for understanding the hardware-software boundary.

Instruction Fetch → Decode → Execute → Memory → Write Back (cycle-accurate)

🛠 Tech Arsenal

`SYSTEMS`	`BACKEND`	`AI / INFRA`	`DEV & FRONTEND`

🔭 Currently Building

🔍 AI SEARCH

_{Building a full retrieval-augmented search engine. Learning RAG, vector databases, backend architecture, and deployment.}

⚙️ SYSTEMS

_{Going deeper into OS, architecture, networking, and databases. Building a CPU simulator from scratch.}

🌐 OPEN SOURCE

_{Preparing for GSoC / LFX. Learning how production codebases are designed, reviewed, and evolved.}

📐 ALGORITHMS

_{NeetCode 150 + systematic revision. Understanding patterns, not just solving problems.}

🗺 Depth Map

	Layer	Technologies	Status
`0x07`	Application	React · REST APIs · CLI Tools	`building`
`0x06`	Backend	FastAPI · PostgreSQL · Redis · Docker	`building`
`0x05`	AI Systems	RAG · Agents · LLMs · Embeddings	`building + learning`
`0x04`	Databases & Net	Storage Engines · Protocols · TCP/IP	`learning`
`0x03`	Operating Systems	Processes · Memory · Scheduling	`learning`
`0x02`	Architecture	ISA · Datapaths · Caches · Pipelines	`building + learning`
`0x01`	Distributed Systems	Consensus · Replication · Fault Tolerance	`exploring`
`0x00`	Research / Advanced	Compilers · Quantum · HPC	`long-term`

🏆 Achievements

⌁ System Metrics

_{Building systems. Understanding abstractions. Going deeper.}

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