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 7 of 26
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.
Structured Outputs: Make Your AI Agent Stop Guessing
JSON mode isn't enough. Learn how constrained decoding, Zod schema validation, and validator-retry patterns cut agent parsing failures in production.
Synthetic Users: Test Your Agent Against AI Personas
Scripted tests catch only the failures you anticipated. Build AI-powered synthetic users that simulate real customers and break your agent before it ships.
How to Build a Trajectory Eval for Your AI Agent
Outcome evals check the final answer. Trajectory evals check the path: tools called, data touched, steps taken. Here's how to build one for a CX agent.
How to Build Production-Safe Credentials for AI Agents
After PocketOS lost its production database to a nine-second AI agent error, here's the credential model that would have stopped it: vaults, scoping, RBAC, and boundary tests.
Learn Agentic AI
Weekly. Patterns for shipping agents that work. MCP, scorecards, regression tests, prompts, model comparisons.
