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 6 of 26
Build agents that fix themselves when they fail
Most agents fail silently in production. Self-healing agents detect their own failures, classify what went wrong, and take a different path rather than retrying blindly.
When your agents call other agents, don't assume trust
Multi-agent systems create delegation chains where each agent trusts the one that called it. That assumption is how prompt injection and privilege escalation get in. Here's how to enforce scoped trust instead.
Context engineering: why your agent gets dumber mid-conversation
82% of AI teams say prompt engineering alone no longer works for production. Context engineering decides what your agent sees, when, and what gets removed as conversations grow.
Agent containment: what Microsoft's MXC means for CX
Microsoft unveiled MXC at Build 2026: OS-level sandboxes for AI agents with policy-driven containment and Entra-backed identity. Here's what it means for teams building CX agents.
The OpenAI Assistants API shuts down August 26
The OpenAI Assistants API sunsets on August 26, 2026. If you built a CX chatbot or support agent on it, here's what's actually changing, your migration options, and why this is the right time to build the architecture you should have had from the start.
Why your eval scores don't predict real conversation quality
Your agent passes 91% of your eval suite but customers keep escalating. The problem is almost always the same: you're measuring single-turn quality, and customers experience multi-turn conversations. Here's how to build evaluation that reflects what actually happens.
When voice becomes chat: carrying context across channels
When a customer switches from a call to chat, your AI agent loses everything it learned on the phone -- unless you package and transfer context deliberately. Here's how to build channel context handoffs that actually work.
CX agent personas: why brand voice is an infrastructure problem
Generic AI agents erode the brand identity you spent years building. Here's the system prompt architecture that gives your CX agent a consistent, testable, on-brand voice -- across every session and channel.
How to Build Ambient AI Agents for Always-On CX
Most AI agents wait for prompts. Ambient agents watch event streams and act first. Here's how to build always-on CX intelligence that catches problems before customers notice them.
SRE for AI Agents: SLOs, Error Budgets, and Reliability
Traditional SRE doesn't catch AI agent failures. Here's a practical SRE playbook for agents: the five SLIs that matter, how to set SLOs that are actually useful, and how error budgets control agent autonomy before problems escalate.
Managed Agents in 2026: Three Runtimes, Three Trade-Offs
Google, Anthropic, and OpenAI all shipped 'managed agents' in May 2026, and they mean completely different things. Here's what each runtime trades away for CX teams.
How to Use MCP Sampling, Roots, and Elicitation in CX Agents
Most MCP tutorials cover only server-side features: tools, resources, prompts. The three client capabilities (Sampling, Roots, Elicitation) unlock human-in-the-loop patterns that server tools alone can't. Here's how to use them.
Learn Agentic AI
Weekly. Patterns for shipping agents that work. MCP, scorecards, regression tests, prompts, model comparisons.
