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evaluation

Browse 8 articles tagged with “evaluation”.

Articles tagged “evaluation

8 articles

Watercolor Illustration of Two Scoreboards Side by Side, One for Coding Tasks, One for Customer Conversations, With the Customer Scoreboard Showing Much Lower Numbers
Testing & Evaluation·11 min read read

Stop Using SWE-Bench to Pick Your CX Model

SWE-Bench scores 85% or 23% depending on the harness, and neither measures customer experience. Why tau-bench, tau2-bench, and pass^k matter for CX agents.

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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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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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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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Control room with green monitoring screens, one cracked display unnoticed in the center, Minority Report style
Testing & Evaluation·14 min read read

Is monitoring your AI agent actually enough?

Research shows 83% of agent teams track capability metrics but only 30% evaluate real outcomes. Here's how to close the gap with multi-turn scenario testing.

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Open-source AI agent testing engine with conversation simulation and scorecard evaluation
Testing & Evaluation·14 min read

We open-sourced our AI agent testing engine

chanl-eval is an open-source engine for stress-testing AI agents with simulated conversations, adaptive personas, and per-criteria scorecards. MIT licensed.

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A filing cabinet with most drawers empty and papers scattered on the floor, watercolor illustration in muted blue tones
Knowledge & Memory·12 min read read

Your Agent Completed the Task. It Also Forgot 87% of What It Knew.

Task completion hides a silent failure: agents forget 87% of stored knowledge under complexity. New research reveals why standard evals miss this entirely.

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Watercolor illustration of a split dashboard showing human reviewers on one side and automated scoring metrics on the other
Operations·15 min read read

74% of Production Agents Still Rely on Human Evaluation

A survey of 306 practitioners reveals most production agents are far simpler than expected. The eval gap isn't a tooling problem. It's a trust problem.

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