The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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235 articles · Page 15 of 20
MCP Deep Dive: Advanced Patterns for Agent Tool Integration
Production MCP patterns for teams who've built their first server and need to scale it — OAuth 2.1 with PKCE, Streamable HTTP transport, gateways, sampling, dynamic tool registration, and multi-tenant security.
Multimodal AI Agents: Voice, Vision, and Text in Production
How to architect multimodal AI agents that process voice, vision, and text simultaneously — from STT→LLM→TTS pipelines to vision integration, latency budgets, and production fusion strategies.
Voice Agent Platform Architecture: The Stack Behind Sub-300ms Responses
Deep dive into voice agent architecture — the STT→LLM→TTS pipeline, latency budgets, interruption handling, WebRTC vs WebSocket transport, and what orchestration platforms leave on the table.
Fine-tuning vs RAG: why most teams pick wrong and how to decide
When to fine-tune, when to use RAG, and when you need both — with hands-on LoRA fine-tuning and RAG implementation on the same task to show the difference.
Multi-Agent AI Systems: Build an Agent Orchestrator Without a Framework
Build a multi-agent system from scratch — delegation, planning loops, and inter-agent communication — before reaching for LangGraph or CrewAI.
Streaming AI Responses: SSE, WebSockets, and the Architecture Behind ChatGPT's Typing Effect
Build three streaming implementations from scratch — SSE, WebSocket, and HTTP/2 — and learn why token-by-token rendering is harder than it looks.
Who's Testing Your AI Agent Before It Talks to Customers?
Traditional QA validates deterministic code. AI agent QA must validate probabilistic conversations. Here's why that gap is breaking production deployments.
How to Evaluate AI Agents: Build an Eval Framework from Scratch
Build a working AI agent eval framework in TypeScript and Python. Covers LLM-as-judge, rubric scoring, regression testing, and CI integration.
MCP Explained: Build Your First MCP Server in TypeScript and Python
Build a working MCP server from scratch in TypeScript and Python. Hands-on tutorial covering tools, resources, transports, and testing.
Prompt Engineering from First Principles: 12 Techniques Every AI Developer Needs
Master 12 essential prompt engineering techniques with real TypeScript examples. From zero-shot to ReAct, build better AI agents from first principles.
RAG from Scratch: Build a Retrieval-Augmented Generation Pipeline
Build a working RAG pipeline from scratch in TypeScript and Python. Covers embeddings, chunking, vector search, and generation with real, runnable code.
Voice AI Escaped the Call Center. Here's Where It Landed.
From $50K M&A due diligence to 9 million burger orders, voice AI agents are breaking into verticals nobody predicted. Here's what developers need to know.
Learn Agentic AI
Weekly. Patterns for shipping agents that work — MCP, scorecards, regression tests, prompts, model comparisons.
