The hottest Productivity Metrics Substack posts right now

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Are AI Coding Assistants Really Saving Developers Time? Study Suggests These Tools Don’t Increase Coding Speed.

Shenisha’s Substack • 19 implied HN points • 04 Oct 24
🕹 Technology AI Tools Software Development Coding Practices Productivity Metrics Quality Assurance
  1. AI coding tools, like GitHub Copilot, may actually slow down developers by increasing the number of bugs in their code. This raises questions about whether these tools truly help improve code quality.
  2. While some surveys show that many developers use AI tools and feel productive, a study found that these tools didn't significantly improve coding speed or help reduce burnout among developers.
  3. The rise of AI tools may require developers to spend more time reviewing the code these tools produce, which can cancel out any time they might save overall.

Measuring developer productivity: A clear-eyed view

Engineering Enablement • 21 implied HN points • 05 Feb 25
🕹 Technology Software Development Developer Experience Productivity Metrics Engineering Management Data Analysis
  1. Metrics for developers should help improve their work experience, not just measure their output. Goodhart's Law reminds us that once metrics are tied to rewards, they can become misleading.
  2. Developer experience is more about effectiveness than happiness. Measuring how developers feel needs to focus on the frustrations they face, and not just on making them comfortable.
  3. Using benchmarks is important but context is key. Just like medical tests, numbers need interpretation to make sense; comparing different teams requires understanding their unique challenges.

The DX Core 4 Framework

Fish Food for Thought • 11 implied HN points • 11 Dec 24
🕹 Technology Software Development Productivity Metrics Engineering Practices Data Analysis
  1. The DX Core 4 Framework helps companies measure developer productivity by looking at four main areas: Speed, Effectiveness, Quality, and Impact. This balanced approach provides a complete picture of how well teams are performing.
  2. It includes a Developer Experience Index (DXI) that shows how developers feel about their work, helping identify areas for improvement. This means companies can catch issues before they become bigger problems.
  3. The framework focuses on connecting developer productivity to business goals, making it easier for all levels of the organization to understand how engineering work impacts the company's success.

Measuring the Productivity of Developers

burkhardstubert • 39 implied HN points • 04 Oct 23
🕹 Technology Software Development Productivity Metrics Organizational Culture Team Dynamics
  1. McKinsey suggests measuring developer productivity using new metrics that track time spent on development versus other tasks. This way, they want to see more time in real coding and less in meetings.
  2. Orosz and Beck argue that measuring effort or output isn't very useful because people might manipulate those numbers. Instead, they say to focus on the actual effects of the work, like the value that reaches customers.
  3. Team performance is more important than individual effort. It's better to measure how well a team works together than to judge each person separately.
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