The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
Latest Articles
Testing & EvaluationIs AI Better Than Your Humans? Score Both on One Rubric
Most teams can't say whether AI beats humans because they score them differently. One rubric, run on both, sliced by segment, gives you an honest answer.
Testing & EvaluationEvery Failed Call Is a Test Case You Haven't Written Yet
The gap between staging and production for AI agents is measured in surprise. Here's how to close the loop from live failure to regression gate.
All Articles
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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.
How to Build Agent Interrupt and Approval Checkpoints
How to pause an AI agent before high-stakes actions, persist full state through the approval window, and resume cleanly. Covers interrupt gates, approval queues, checkpointing, and EU AI Act compliance for production CX agents.
How to Build Idempotent Tool Calls for AI Agents
Naive retry logic charges customers twice, sends duplicate emails, and fires double webhooks. Here's how to build idempotent tool calls for AI agents with idempotency keys, deduplication, and safe retries.
How to Build the Context Package for AI-to-Human Handoffs
AI agents escalate every day, and most send the human in blind. Here's how to build the context package that makes handoffs invisible to customers.
How to Migrate Your MCP Server to Stateless Mode
The MCP 2026 release candidate makes stateless the recommended default. Your MCP server can now scale behind any load balancer without sticky routing. Here's how to migrate and use the new Tasks extension for async CX work.
Your Agent's Context Window Is RAM, Not Storage
Most agent failures trace back to one mistake: treating the context window like a database. Here's the RAM model that fixes attention dilution, latency spikes, and ballooning costs.
MCP Without a Gateway Is a Production Liability
Raw MCP is great for prototyping. But production agents need audit trails, per-user identity, tool-level RBAC, and rate limiting, none of which the spec provides. Here's the gateway pattern that fills the gap.
How to Build a Regression Test Suite for AI Agents
Your CI/CD pipeline catches code regressions. But who catches it when a prompt change breaks your agent's compliance behavior? Here's how to build behavioral regression testing for non-deterministic AI agents.
How to Write an Agent Spec Before You Write the Prompt
Inconsistent agent behavior isn't a prompt problem. It's a missing-spec problem. Here's the seven-section document that fixes it before code.
Learn Agentic AI
Weekly. Patterns and recipes for shipping AI agents that actually work — MCP, scorecards, regression tests, prompts, model comparisons. From teams running agents in production.
