The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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303 articles · Page 9 of 26
Shadow Mode: Deploy AI Agent Updates Without Risk
Shadow mode runs your new agent version in parallel with production, comparing behavior before customers ever see it. Here's how to build the full deployment pipeline from shadow to canary to 100%.
Your CX Agent Crashes Mid-Task. Here's the Fix.
When your CX agent crashes mid-refund or mid-booking, the customer is stuck. Durable execution guarantees long-running agent tasks survive failures. Here's how to build it.
AG-UI: The Protocol That Connects Agents to UIs
AG-UI is the open event-based protocol that streams AI agent state to any frontend in real time. Here's how it works, what events it defines, and how to wire it up in TypeScript.
Your Agent Is Already a State Machine. Make It Explicit.
Every production AI agent is secretly a state machine. Making it explicit gives you checkpointing, testable paths, and observable state transitions -- without rewriting your agent logic.
Your Agent Has Observability. It Doesn't Have Measurement.
89% of AI teams added observability. 52% added evals. But only 31% can say whether their agent is getting better or worse. Here's the difference between watching your agent and actually measuring it.
Why CX Agents Fail Between Conversations
Your AI agent handles the call perfectly and still fails your customer. The problem isn't the conversation -- it's everything that happens after it. Here's how async task queues fix the gap.
AI Agent KPIs: What to Measure Before You Ship
Only 31% of teams have a measurement framework for their AI agents. Here's how to define task completion rate, escalation rate, cost per outcome, and CSAT delta before your first production interaction.
MCP Auth in Production: Scopes, Tokens, and Tenant Isolation
Most MCP servers ship with no auth. Here's how to add OAuth 2.0 scopes, per-tenant tool sets, and client isolation before your MCP server becomes load-bearing production infrastructure.
Circuit Breakers for AI Agents: Stop the 3 AM Meltdown
One retry loop at 11 PM becomes $437 by 7 AM. Here's how to implement circuit breakers for AI agent tool calls, LLM calls, and external APIs, with TypeScript patterns that stop cascading failures before they start.
Past 50 tools, function-calling accuracy falls off a cliff
Past 50 tools, function-calling accuracy falls off a cliff. Measure the curve on your own agent and recover accuracy with per-turn toolset scoping.
GPT-5, Claude 4.5, Gemini Score the Same Calls. Their Kappa Is 0.52
Run the same calls through GPT-5, Claude 4.5, and Gemini and Cohen's kappa lands at 0.52. Here is how to measure judge agreement on your own corpus.
1M-Token Context or RAG? How to Pick for Your CX Agent
Gemini's 1M-token window is real but not free. A practical decision framework for choosing between long-context and RAG for customer experience agents, with cost numbers, code, and the hybrid pattern most production teams land on.
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Weekly. Patterns for shipping agents that work. MCP, scorecards, regression tests, prompts, model comparisons.
