AI System Design - Learn how to design AI systems built on LLMs, RAG, and AI Agents step by step.
Complex code hides connections, workflows, and business risks.Unvibe complex code. Trace business workflows.
System Design explained from first principles to senior engineer-level thinking, with a focus on AI-assisted (vibecoding) development. Learn how to reason about systems, understand trade-offs, and validate AI-generated designs beyond just working code.
Free, open-source AI engineer interview questions & handbook — Applied AI Engineer / Forward Deployed Engineer (FDE), LLM, RAG, AI agents, evals, fine-tuning, AI system design (2026).
The Facial Recognition Based Attendance System is an automated solution designed to streamline attendance management in educational institutions. By utilizing advanced facial recognition technology, the system eliminates manual attendance processes, reduces proxy attendance, and provides real-time attendance tracking with comprehensive reporting .
First-Person Agent Memory Bench. 10 Categories including fact recall, multi-hop links, temporal reasoning, fact overwrites, speaker traps, refusal, credibility, and agentic tool usage. 540K token / 60 session corpus, all in first person. Dynamic output-answer-key portion. Comprehensive report with visuals and miss breakdown.
AI 系统设计指南非官方简体中文镜像与阅读站
An open source, end-to-end AI engineering curriculum—blending hands-on projects with deep theory. Covers ML, deep learning, data science & full-stack AI system design. Built for future engineers, researchers & innovators.
A capability-first method for designing AI-enabled software systems in line with the CloudPedagogy AI Capability Framework.
The free, open companion to Grokking the AI System Design Interview: building blocks, design questions, and reference sheets for machine learning, LLM, and agent interview rounds.
Presentations/tutorials delivered by me at various conferences 👩🏽💻
LLM-Powered Multi-Agent System for Market Intelligence using LangGraph, RAG, and Tool-Based Reasoning to Generate Structured Financial Insights.
A new package that helps extract and structure insights from discussions about AI system design challenges. Users can input text from forums, articles, or discussions, and the package will use llmatch
A minimal, contract-first AI workflow architecture that decouples execution from visibility. Focused on streaming LLM execution, policy-gated visibility, explicit failure semantics, and cursor-free replay, extracted from a real-world MVP.
Real-world AI system design interview problems with production-ready architectures, scalability, reliability, AI/ML deep dives, trade-offs, and mock interview walkthroughs.
Purple Cove Labs - Website
A Reproducible Engineering Environment for AI, Cloud, DevOps & Software Engineering Modern AI systems don't begin with a model. They begin with the engineering environment underneath it.
Corporate loan decisioning system using ML + LLMs with explainable risk intelligence
An ultra-modern AI-native architecture engine showcasing layered intelligence, orchestration, and scalable infrastructure through real-time visualization. Built for enterprise-grade systems, it integrates advanced UI, AI workflows, and cloud-native design—optimized for SEO, AEO, GEO, LLMO, and high-impact digital presence.
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