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The Chanl Blog

Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.

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171 articles · Page 1 of 15

Architecture diagram of an agentic data layer with event log, signal extraction, entity store, and improvement loop
Agent Architecture·14 min read

The Modern Data Stack Wasn't Built for Agents

Snowflake, dbt, and Fivetran were built for humans asking batch questions. Agents need streaming signals, per-entity memory in under 100ms, and write-back.

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Illustration of a person drawing a causal graph on a whiteboard while teammates watch
Learning AI·22 min read

Correlation Killed Your Retention Model. Causal AI Fixes It.

Your churn model says support calls cause retention. They don't. Build a causal pipeline with DoWhy, EconML, and propensity matching in Python.

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Watercolor illustration of an engineer at a desk reviewing wall of screens with charts and signals — schema design in the Arrival-inspired sage & olive palette
Agent Architecture·14 min read read

Stop Storing Transcripts. Start Modeling Signals.

A JSON blob of transcripts works at 1k calls and collapses at 50k. Design a Signal schema with entity/event split, confidence, provenance, and versioning.

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Warm watercolor illustration of an engineer reviewing A/B test scorecards and conversation analytics at a rooftop workspace during golden hour
Testing & Evaluation·12 min read

Every Conversation Is an Experiment You Didn't Run

Your agent already ran the A/B test you're scoping. Here's how to read the results in your logs with propensity matching, synthetic control, and diff-in-diff.

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A watercolor illustration of a revenue leader turning away from a wall of dashboards to act on a single highlighted customer conversation
Industry & Strategy·10 min read

Stop Building Dashboards. Start Shipping Signal.

Dashboards tell VPs what happened last quarter. Signal tells them which account to call today, and why. How CX is exiting the post-dashboard era in 2026.

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Watercolor illustration of an observation tower overlooking two parallel worlds, Blade Runner 2049 style in sage and olive tones
Testing & Evaluation·8 min read

Is 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.

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Watercolor illustration of two figures walking through a warm corridor of looping paths, Her style in warm plum tones
Testing & Evaluation·9 min read

Every 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.

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Watercolor illustration of a space mission control room with signal data flowing across screens, Interstellar style in dusty blue tones
Industry & Strategy·8 min read

Your Conversations Are Already CRM Data. Here's How to Use Them.

Every customer call carries churn risk, expansion intent, and compliance signal. Most teams toss it. Here's how to turn conversations into live CRM data.

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Grid of test scenario cards with pass and fail indicators showing evaluation coverage distribution
Testing & Evaluation·13 min read

How Much Testing Is Enough for Your AI Agent?

Code coverage doesn't apply to AI agents. Here's a framework for thinking about evaluation coverage: how many scenarios you need, what distribution to target, and how to know when you've tested enough.

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Network diagram showing HTTP transport routes consolidating from two paths to one streamlined endpoint
Tools & MCP·12 min read

MCP SSE Is Deprecated. Here's How to Migrate

SSE transport is being deprecated across major MCP platforms in 2026. Here's a practical migration guide from HTTP+SSE to Streamable HTTP, with TypeScript examples and a phased rollout strategy.

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A person standing before multiple transparent evaluation panels in a semicircle, each showing a different lens on the same conversation
Testing & Evaluation·16 min read read

Your LLM-as-judge may be highly biased

LLM-as-Judge has 12 documented biases. Here are 6 evaluation methods production teams actually use instead, with code examples and patterns.

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Developer at a desk surrounded by sticky notes with warning symbols, red warning lights on a server rack nearby
Tools & MCP·14 min read read

7 FastMCP mistakes that break your agent in production

FastMCP servers that work locally often fail at scale. Seven common mistakes, from missing annotations to monolithic tool sets, and how to fix each one.

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