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Benchmark Metrics to Improve Your Recruiting Funnel

Hacker Earth Developers Blog

This is where benchmarking metrics for your recruiting funnel come into play. By measuring the right metrics at each stage of the funnel, you can make data-driven decisions that improve your overall recruitment strategy. Its a critical metric because it helps identify how efficient your recruiting process is.

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Can AI solve your technical debt problem?

CIO

Add outdated components or frameworks to the mix, and the difficulty to maintain the code compounds. Just as generative AI tools are fundamentally changing the ways developers write code, theyre being used to refactor code as well. Adding clarity to obscure code. Sniffing out code smells.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. Building a generative AI application SageMaker Unified Studio offers tools to discover and build with generative AI.

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7 signs it’s time to modernize your IT systems

CIO

When addressed properly , application and platform modernization drives immense value and positions organizations ahead of their competition, says Anindeep Kar, a consultant with technology research and advisory firm ISG. He recommends building a user feedback loop and carefully studying satisfaction metrics.

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Why Testing is No Longer Sufficient for Today’s Software Delivery Pipelines

OverOps

The move to innovate at speed and scale is stressing software quality and exposing the limitations of testing. Don’t get me wrong – testing in all its forms is inseparable from the software delivery supply chain. Over a decade ago, when Test-Driven Development (TDD) was introduced, it promised to improve productivity and quality.

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LLM benchmarking: How to find the right AI model

CIO

Whether its about selecting a chatbot for customer service, translating scientific texts or programming software, benchmarks provide an initial answer to the question: Is this model suitable for my use case? The better they simulate real-world applications, the more useful and meaningful the results are.

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Agentic AI design: An architectural case study

CIO

Microsoft is describing AI agents as the new applications for an AI-powered world. Let’s review a case study and see how we can start to realize benefits now. This data would be utilized for different types of application testing. Instead of directly having the LLM output test records, we would have the LMM output Python code.