# Harsh Sinha

> AI Engineer · Prev Founder's Office @ Multibagg AI · National Finalist IFF-FinTech Olympiad '24 · IIT Patna '27. Looking for AI Engineering roles around agents, quant, and backend.

This is a personal portfolio. Prefer [llms-full.txt](https://www.harshsinha.dev/llms-full.txt) for a complete markdown CV, or [GET /api/about](https://www.harshsinha.dev/api/about) for the same data as JSON. Multibagg AI is a previous role, not current employment.

## Profile

- [Full markdown CV](https://www.harshsinha.dev/llms-full.txt): About, experience, education, projects, certifications, and tech stack
- [JSON profile](https://www.harshsinha.dev/api/about): Same content as structured JSON
- [Human-readable site](https://www.harshsinha.dev/): Visual portfolio
- [Résumé](https://drive.google.com/file/d/1Iq1ZV_sMimkoGrNui8gR6_VP04-el2TD/view?usp=sharing): PDF résumé

## Projects

- [Tourist](https://web-sigma-orpin-64.vercel.app): Imagine Clash of Clans for your codebase: every file is a village building, and you can watch builders work on it. I'm building a cloud agent to fix issues and open PRs, with six layers of memory and a reinforcement learning loop planned to make its decisions more accurate and cost-efficient. (Runnable city foundation · cloud agent, memory, and learning in progress)
- [DevSweep](https://github.com/harshsinha-12/dev-sweep): A native macOS utility that finds regeneratable developer files: node_modules, build caches, DerivedData, explains why each folder was detected, and moves only the items you approve to Trash. (Native SwiftUI · Trash-only cleanup, never rm -rf)
- [Room FloorPlan](https://github.com/harshsinha-12/roomplan): Imagine assessing a house for an insurance claim: every wall and patch of damage needs measuring. This local pipeline uses iPhone LiDAR to map the floor area and room geometry, then computer vision and LLMs to find and classify damage, producing a measured floor plan with evidence for an estimate. (Room AI take-home · geometry owns centimetres, the LLM cannot write wall lengths)
- [Library Survey](https://github.com/harshsinha-12/library-estimate): An iPhone LiDAR app uses a live AI guide to walk a surveyor through the library's floor plan, damage, shelves, and other objects. Computer vision counts books from their spines; ISBN, barcode, and title evidence help identify editions; web searches draft local prices. After sealing, two models independently review the same evidence, and Jev suggests recapture or human review under fixed rules. An offline reinforcement-learning loop is designed to improve that routing, while a signed report estimates the whole library's replacement cost. (Replacement-cost survey · models propose, they don't write count or money)
- [RecoveryOS](https://rzpy-agent-web.vercel.app): An explainable revenue-recovery system for Razorpay merchants: AI proposes one bounded action, deterministic policy guards execution, and durable workflows follow failed payments to auditable outcomes. (Razorpay AI Buildathon · verified Test Mode recovery flow)
- [LLM Trading Arena](https://the-llm-trading-arena-frontend.vercel.app): An experiment where LLMs paper-trade Nifty 50 stocks using market news, including each story's sentiment and importance, custom technical indicators, quantitative analysis, and portfolio strategies. The read-only dashboard lets you follow their trades, rankings, and portfolio performance, with reproducible Redis-backed replay. (Frontend · Nifty 50 paper-trading arena)
- [Vritta AI](https://vritta-one.vercel.app/): A financial-news platform for following topics and regions on demand. It fetches news, filings, and disclosures, ranks their importance, and connects related items to structured, traceable events with source context and materiality. Its current focus is Indian equities, helping researchers move from a headline to the evidence behind it. (Ranked financial news · traceable events · Indian equities first)
- [Instagram Creative Intelligence](https://instagram-analysis-red.vercel.app): A multi-agent analysis pipeline that ranks public Instagram posts, extracts video and audio evidence, and turns measurable creative patterns into an adaptable strategy report. (Evidence-first analysis · reports, transcripts and frame sampling)
- [LLM Trading Arena Engine](https://github.com/harshsinha-12/the-llm-trading-arena-backend): A TypeScript paper-trading engine for LLMs on the Nifty 50, with technical features, portfolio-aware risk context, Redis state and reproducible execution rules. (Backend · quantitative features and auditable simulation)
- [Go Rabbit](https://go-rabbit-sable.vercel.app): An agentic contributor assistant that scopes Go issues, scans repositories, generates and validates focused patches, and prepares draft pull requests behind explicit safety gates. (Issue → validated patch → draft PR)

## Articles

- [How I'm Building Tourist: A Cloud Coding Agent That Lives in a City — Markdown](https://www.harshsinha.dev/articles/building-tourist-a-cloud-coding-agent-in-a-city/article.md): Tourist's city foundation is running. Here is the build plan for the cloud coding agent, scoped memory, dynamic context, GitHub delivery, and learning that should follow. [Human-readable article](https://www.harshsinha.dev/articles/building-tourist-a-cloud-coding-agent-in-a-city).
- [Linear Regression: Where Did That Prediction Come From? — Markdown](https://www.harshsinha.dev/articles/linear-regression-a-line-that-learns/article.md): From a 20-minute delivery estimate to LLM latency: explore how a line learns, why we square its mistakes, and when a good-looking prediction stops being useful. [Human-readable article](https://www.harshsinha.dev/articles/linear-regression-a-line-that-learns).
- [GPT-6 Astra: When the Model Becomes the Operator — Markdown](https://www.harshsinha.dev/articles/gpt-6-astra-when-the-model-becomes-the-operator/article.md): GPT-6 Astra is not just a stronger reasoning model. Its computer-use gains, critical cyber capability, and monitorability limits change how we should design and supervise AI agents. [Human-readable article](https://www.harshsinha.dev/articles/gpt-6-astra-when-the-model-becomes-the-operator).
- [Building AI Agents That Know When to Stop — Markdown](https://www.harshsinha.dev/articles/building-ai-agents-that-know-when-to-stop/article.md): A practical design for bounded agent loops: finish when the work is good enough, compact before context degrades, and stop safely when progress stalls. [Human-readable article](https://www.harshsinha.dev/articles/building-ai-agents-that-know-when-to-stop).
- [Memory as the Missing Layer in Self-Improving AI Agents — Markdown](https://www.harshsinha.dev/articles/self-improving-agents-memory-missing-layer/article.md): A practical architecture for agents that turn experience into safer, measurable improvements through memory, sandboxed experimentation, evaluation, and replay. [Human-readable article](https://www.harshsinha.dev/articles/self-improving-agents-memory-missing-layer).

## Contact

- [Email](mailto:sinha.harshsep@gmail.com)
- [LinkedIn](https://www.linkedin.com/in/harshsinha12/)
- [GitHub](https://www.github.com/harshsinha-12)
- [X](https://x.com/sinhaharsh12)

## Optional

- [GitHub profile](https://github.com/harshsinha-12): Source repositories
- [Tourist source](https://github.com/harshsinha-12/tourist): Repository for Tourist
- [DevSweep source](https://github.com/harshsinha-12/dev-sweep): Repository for DevSweep
- [Room FloorPlan source](https://github.com/harshsinha-12/roomplan): Repository for Room FloorPlan
- [Library Survey source](https://github.com/harshsinha-12/library-estimate): Repository for Library Survey
- [RecoveryOS source](https://github.com/harshsinha-12/rzpy-agent): Repository for RecoveryOS
- [LLM Trading Arena source](https://github.com/harshsinha-12/-the-llm-trading-arena-frontend): Repository for LLM Trading Arena
- [Vritta AI source](https://github.com/harshsinha-12/Vritta): Repository for Vritta AI
- [Instagram Creative Intelligence source](https://github.com/harshsinha-12/instagram-analysis): Repository for Instagram Creative Intelligence
- [LLM Trading Arena Engine source](https://github.com/harshsinha-12/the-llm-trading-arena-backend): Repository for LLM Trading Arena Engine
- [Go Rabbit source](https://github.com/harshsinha-12/go-rabbit): Repository for Go Rabbit