Industry AI Agent System Design

A hellointerview-style system design deep dive into autonomous AI coding agents like Devin, Cursor, and Claude Code. Covers requirements, core entities, the ReAct loop, and three production deep dives: codebase indexing and retrieval, context window management, and sandboxed execution and safety. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI-powered code review systems like GitHub Copilot Code Review, CodeRabbit, and Graphite Reviewer. Covers requirements, core entities, the review pipeline, and three production deep dives: diff understanding and semantic analysis, noise reduction and feedback quality, and CI/CD integration with latency optimization. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI-powered search engines like Perplexity, SearchGPT, and Google AI Overviews. Covers requirements, core entities, the search-to-synthesis pipeline, and three production deep dives: query decomposition and tool routing, retrieval and reranking pipelines, and citation-grounded synthesis with source verification. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into autonomous deep research agents like OpenAI Deep Research, Anthropic multi-agent research, and Gemini Deep Research. Covers requirements, core entities, the orchestrator-worker architecture, and three production deep dives: research orchestration with adaptive budget allocation, hierarchical memory with progressive summarization, and iterative report synthesis with source verification. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI customer support systems like Klarna AI (replaced 700 agents), Sierra AI, and Salesforce Agentforce. Covers requirements, core entities, the conversation pipeline, and three production deep dives: intent classification and routing, action execution and tool use, and human handoff and escalation. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into hallucination-free banking chatbots like JP Morgan's LLM Suite and Bank of America's Erica. Covers requirements, core entities, the no-hallucination architecture, and three production deep dives: hallucination prevention via LLM-as-router, audit trail and regulatory compliance, and graceful degradation with confidence-based fallback. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI email and calendar agents like Google Gemini in Workspace, Microsoft Copilot for M365, and Lindy AI. Covers requirements, core entities, the action planning pipeline, and three production deep dives: intent understanding and multi-turn planning, calendar constraint solving with preference optimization, and progressive autonomy with trust scoring. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into enterprise RAG systems like Glean, Notion AI, and Confluence AI. Covers requirements, core entities, the retrieval-augmented generation pipeline, and three production deep dives: ingestion and chunking strategies, access control at retrieval time, and multi-hop retrieval with agentic self-correction. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI workflow automation platforms like n8n AI agents, Zapier AI, and Power Automate Copilot. Covers requirements, core entities, the natural-language-to-workflow pipeline, and three production deep dives: NL to workflow DAG translation, tool registry and discovery, and execution engine with error handling. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into computer-use agents like OpenAI Operator (CUA), Anthropic Computer Use, and Google Project Mariner. Unlike API-based agents, these systems process raw screenshots via vision models and control computers through virtual mouse and keyboard actions. Covers requirements, core entities, the perception-action loop, and three production deep dives: screen understanding, action planning and error recovery, and sandboxing and security. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI data analyst agents like ChatGPT Code Interpreter, Julius AI, and Databricks Genie. The agent translates natural language questions into SQL and Python, executes code against real databases in a sandbox, generates visualizations, and produces narrative insights. Covers requirements, core entities, the analysis loop, and three production deep dives: schema understanding and query generation, sandboxed code execution, and visualization and insight generation. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into multi-agent software development systems like MetaGPT, ChatDev, and Anthropic agent teams. Multiple AI agents with specialized roles (PM, architect, developer, QA) collaborate to build software from a product requirement. Covers requirements, core entities, the orchestration pipeline, and three production deep dives: role specialization, inter-agent coordination, and the honest single-agent versus multi-agent trade-off. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI content moderation systems at the scale of Meta, OpenAI safety, and YouTube automated moderation. The system classifies user-generated content across multiple modalities, enforces jurisdiction-specific policies, resists adversarial evasion, and routes edge cases to human review. Covers requirements, core entities, the classification pipeline, and three production deep dives: cascading classification architecture, policy as code, and adversarial robustness. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into real-time AI fraud detection systems like Stripe Radar, PayPal, and Featurespace. Covers requirements, core entities, the two-speed scoring architecture, and three production deep dives: real-time scoring pipeline, feature engineering, and adversarial adaptation with cold-start handling. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI legal contract generation systems like Harvey AI, Ironclad, and Luminance. Covers requirements, core entities, the template-based generation architecture, and three production deep dives: clause library and generation architecture, compliance and risk checking, and template-based versus free-form generation trade-offs. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.

A hellointerview-style system design deep dive into AI recommendation systems like Netflix, Spotify DJ, TikTok For You, and Amazon. Covers requirements, core entities, the multi-stage retrieval pipeline, and three production deep dives: multi-stage retrieval architecture, conversational recommendation layer, and exploration versus exploitation. Each deep dive walks through naive, better, and production-grade approaches with trade-offs.