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Chatbots
RAG
Agents
Workflows & Automation
Voice Assistants
Evaluation & Testing
Computer Use Agents
Reference Architectures
Model Economics
Knowledge Graphs
⚡Make AI Work
Create Deliverables
Software Development
Data & Database Work
Backend Engineering
Frontend & UI/UX
Personal Productivity
AI Strategy & Product
Build with AI
🔧Build with AI
Chatbots
RAG
Agents
Workflows & Automation
Voice Assistants
Evaluation & Testing
Computer Use Agents
Reference Architectures
Model Economics
Knowledge Graphs
⚡Make AI Work
Create Deliverables
Software Development
Data & Database Work
Backend Engineering
Frontend & UI/UX
Personal Productivity
AI Strategy & Product
Build with AIReference Architectures

Reference Architectures

Instead of designing from scratch, start from a proven architecture and adapt it. These reference patterns cover the most common AI system types — each one shows the component stack, the data flow, the key design decisions, and the failure modes to guard against before you deploy.

In This Section

RAG Chatbot Architecture

The canonical retrieval-augmented generation chatbot — ingestion pipeline, vector store, query processing, reranking, generation, and citation rendering.

Voice Pipeline Architecture

STT → VAD → LLM → TTS pipeline design — latency budgets at each stage, interruption handling, streaming output, and on-device vs cloud trade-offs.

Coding Agent Architecture

Autonomous coding agent design — codebase context, tool loop (read/write/run/test), sandboxed execution, and the human-in-the-loop approval layer.

Hybrid Router Pattern

Route queries across multiple models by task type, cost tier, and data sensitivity — classifier-based routing, fallback chains, and cost-quality trade-off measurement.

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Page built: 01 Jun 2026