Remove Measurement Remove Reference Remove Testing
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Beyond “Prompt and Pray”

O'Reilly on Data

When we talk about conversational AI, were referring to systems designed to have a conversation, orchestrate workflows, and make decisions in real time. Instead of having LLMs make runtime decisions about business logic, use them to help create robust, reusable workflows that can be tested, versioned, and maintained like traditional software.

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Top Productivity Metrics Examples & KPIs To Measure Performance And Outcomes

datapine

2) How To Measure Productivity? For years, businesses have experimented and narrowed down the most effective measurements for productivity. Your Chance: Want to test a professional KPI tracking software? Use our 14-day free trial and start measuring your productivity today! How To Measure Productivity?

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The Race For Data Quality in a Medallion Architecture

DataKitchen

For instance, records may be cleaned up to create unique, non-duplicated transaction logs, master customer records, and cross-reference tables. This involves setting up automated, column-by-column quality tests to quickly identify deviations from expected values and catch emerging issues before they impact downstream layers.

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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. What breaks your app in production isnt always what you tested for in dev! The way out?

Testing 174
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Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). The Core Responsibilities of the AI Product Manager.

Marketing 364
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Start DataOps Today with ‘Lean DataOps’

DataKitchen

The best way to ensure error-free execution of data production is through automated testing and monitoring. The DataKitchen Platform enables data teams to integrate testing and observability into data pipeline orchestrations. Automated tests work 24×7 to ensure that the results of each processing stage are accurate and correct.

Testing 246
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You Can’t Regulate What You Don’t Understand

O'Reilly on Data

If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. And they are stress testing and “ red teaming ” them to uncover vulnerabilities. That is a crucial first step, and we should take it immediately.

Metrics 354