The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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307 articles · Page 6 of 26
A quality control plane for your production agent fleet
Quality drift in production AI agents is silent. Build a quality control plane that scores every conversation, enforces SLOs, gates deployments, and alerts on drift.
Five things your CX agent needs that its framework won't provide
LLM frameworks handle conversations. They don't handle memory, tool reliability, pre-production testing, or observability. Here's what every production CX agent actually needs.
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.
MCP tasks: how async tool calls fix your agent's timeout problem
The November 2025 MCP spec introduced Tasks: a call-now, fetch-later primitive that lets agents kick off slow operations without blocking. Here's how it works and how to build with it.
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 MCP registry: managing a fleet of agent tools
When you have more than 3 MCP servers, you need a registry. Here's the architecture Pinterest and Cloudflare use to manage fleets of domain-specific tool servers at scale.
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.
Learn Agentic AI
Weekly. Patterns for shipping agents that work. MCP, scorecards, regression tests, prompts, model comparisons.
