# devcontext.ai

> AI Project Understanding & Technical Interview Preparation Platform

## Overview
devcontext.ai is a student-focused AI platform that transforms your own software project into a technical interview preparation environment. Connect your GitHub repository and the system analyzes the codebase, architecture, technologies, implementation decisions, and project structure. It then generates: (1) A complete technical project report with architecture, data flow, and component breakdowns; (2) Evidence-based explanations linking every claim to actual repository files and code locations; (3) Project-specific interview questions covering architecture, implementation, design decisions, security, performance, scalability, and failure scenarios; (4) An interactive interview simulation that progresses from basic project overview to deep technical discussion. The platform uses a grounded AI approach via Amazon Bedrock (Claude family) — every explanation references specific files and line numbers so you can verify and learn directly from your code. Built on a serverless AWS architecture (Lambda, API Gateway, DynamoDB, S3, Cognito, WebSockets) with real-time streaming updates during analysis.

- [Official Domain](https://revealr.rounakneema.in)
- [Author: Rounak Neema](https://rounakneema.in)
- [Source Repository](https://github.com/Rounakneema)

## Architecture & Features
An AI-powered platform where students upload their own repository and get a structured learning environment: project analysis, architecture explanation, evidence-based technical deep-dives, project-specific interview questions, and interactive interview simulation — all grounded in their actual codebase.

### Key Capabilities
- **Project Analysis**: Full repository analysis (~30s) covering architecture, tech stack, data flow, authentication, infrastructure, and external services.
- **Evidence-Grounded**: Every technical explanation links to actual repository files — learn your own codebase with AI guidance.
- **Interview Simulation**: Progressive interview from "What does your project do?" to "How would you scale to 100k users?" with AI evaluation and follow-ups.
- **Student-Focused**: Designed for college projects, hackathons, internships, portfolio projects, and placement preparation — not for recruiters.

### Technologies Used
React, TypeScript, AWS SAM, Amazon Bedrock, Claude 3.5 Sonnet, DynamoDB, S3, Cognito, WebSockets

### System Metrics
- **Analysis Time**: ~30s
- **Repo Size**: 50 MB
- **Context Window**: >50k tokens
- **Concurrent**: 10+
- **Cost/Analysis**: ~$1.42

## Author & Related Projects
- [Author: Rounak Neema](https://rounakneema.in)
- [GitHub Profile](https://github.com/rounakneema)
- [LinkedIn Profile](https://linkedin.com/in/Rnks23)

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