AI SYSTEMS · BACKEND · PRODUCTS
From model capabilities
to reliable systems.
I'm Arjun, a software engineer focused on AI applications, backend architecture, and independent products. I document what it takes to move from prototype through deployment to continuous iteration.
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SELECTED WORK
What I'm building
ALL REPOSITORIES ↗MediaForge
An AI image platform for ecommerce content workflows, connecting multimodal retrieval, agents, quality evaluation, and batch processing.
Python · Multimodal RAG · Agents
Finance Tweet Analyzer
A financial tweet analysis platform that uses a multi-agent pipeline for retrieval and analysis, with results streamed over SSE.
Python · LangGraph · RAG · SSE
FIELD NOTES
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How Agents Make Plans: From Task Decomposition to Search and Replanning
A useful plan is executable, verifiable, and willing to change. This article separates task decomposition, search, feedback, and formal planning into the problems they actually solve.
What ReAct Actually Does: How an Agent Acts, Observes, and Adjusts
Starting with a failed CI run, see how Thought, Action, Observation, and the Runtime let an Agent adjust its next move from environmental feedback.
How Does an LLM Agent Actually Finish a Task?
From reading a codebase and running tests to changing course after an error, an Agent works through a repeated act-observe-adjust loop.
Why I Built Made by Arjun
A personal site can show the engineering judgment that a list of technologies leaves out.
How Transformers Build Context with Self-Attention
Starting with a single service call, follow one token through self-attention: see how it forms Query, Key, and Value vectors, computes attention weights, and gathers context with multi-head attention.