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Beyond “Prompt and Pray”

O'Reilly on Data

This approach delivers substantial benefits: consistent execution, lower costs, better security, and systems that can be maintained like traditional software. 90% accuracy for software will often be a deal-breaker, but the promise of agents rests on the ability to chain them together: even five in a row will fail over 40% of the time!

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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. Traditional versus GenAI software: Excitement builds steadilyor crashes after the demo. The way out?

Testing 174
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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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Data Observability and Data Quality Testing Certification Series

DataKitchen

Data Observability and Data Quality Testing Certification Series We are excited to invite you to a free four-part webinar series that will elevate your understanding and skills in Data Observation and Data Quality Testing. Register for free today and take the first step towards mastering data observability and quality testing!

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The Quality of Auto-Generated Code

O'Reilly on Data

In a professional setting, where software needs to be maintained and modified over long periods, readability and organization count for a lot. We know how to test whether or not code is correct (at least up to a certain limit). But we don’t have methods to test for code that’s “good.”

Testing 363
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Is it worth measuring software developer productivity? CIOs weigh in

CIO Business Intelligence

At the same time, developers are scarce, and the demand for new software is high. This has spurred interest around understanding and measuring developer productivity, says Keith Mann, senior director, analyst, at Gartner. Organizations need to get the most out of the limited number of developers they’ve got,” he says.

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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