What Predicts Software Developers’ Productivity?

- Abi Noda tl;dr: Abi summarizes a study by Google researchers on the factors that correlate with software developers' productivity. The study found that "Job enthusiasm," "Peer support for new ideas," and "Useful feedback about job performance" were the most strongly correlated factors with self-rated productivity. The top 10 productivity factors were non-technical.

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The Ultimate Guide To Developer Counter-Productivity

- John Cutler tl;dr: John highlights 20+ specific areas where developers often lose productivity, including: (1) Reactive, unplanned work. (2) Context switching and startup costs. (3) Non-value-adding admin & compliance work. (5) Ineffective planning. (6) Dependency management overhead. (7) Ineffective meetings and communication. (8) Redundant manager briefing & orientation. (9) Consensus seeking and decision-making drag. (10) Ineffective collaboration arrangements. And more.

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Three Dimensions Of Developer Productivity

tl;dr: Abi offers a three-dimensional approach to understanding and measuring developer productivity. The dimensions are Velocity, Quality, and Satisfaction. The authors argue that "any picture of productivity would be incomplete if these dimensions are not considered." Velocity is the speed at which tasks are completed, but the authors caution that the type of task, its complexity, and routineness must be considered. Quality can be both internal (code quality) and external (end-user experience). Satisfaction encompasses feelings like happiness, autonomy, and flow, and it balances the other two dimensions e.g. "an increase in velocity may lead to reduced costs, but at the same time it can lead to increased stress for developers reducing satisfaction."

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How To Create Compound Efficiencies In Engineering

tl;dr: The article covers the shift towards efficiency in engineering in 2023 and outlines three compound efficiencies: real-time visibility into metrics, automating pull requests & code reviews, and protecting developer focus. By layering these efficiencies, teams can achieve elite performance. Sustainable efficiency in software engineering isn't about one-time decisions but building organizational habits that compound over time, leading to significant improvements in quality, speed, and business impact.

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Build Times And Developer Productivity

- Abi Noda tl;dr: The takeaway is that even modest improvements to build times are helpful. Three things: (1) There is no specific threshold for how fast builds need to be for developers to stay on task and be productive. (2) Providing developers with estimated build times can improve productivity. (3) Even modest improvements in build latency can be helpful.

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An Explosion In Software Engineers Using AI Coding Tools?

- Gergely Orosz tl;dr: What do AI coding tools help the most with? The survey lists the top areas mentioned by developers: (1) Learn: develop coding language skills (57%). (2) Productivity: become more productive (53%). (3) Focus: spend more time building and creating, less on repetitive tasks (51%). Gergely dives how engineers are leveraging AI tools.

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DevEx: What Actually Drives Productivity

- Abi Noda tl;dr: The 3 pillars are: (1) Reducing friction: minimizing obstacles, inefficiencies, and complexities in the development process. (2) Optimizing workflows: streamlining processes, automating repetitive tasks, and integrating tools and technologies. (3) Enabling a state of flow: creating an environment that fosters concentration, creativity, and intrinsic motivation.

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Measuring Flow And Focus

- Abi Noda tl;dr: Based on a study with Google engineers, the best predictor of flow is “focus time:” performing a number of similar actions in a given window of time. Researchers also identified 3 practices for facilitating flow: (1) Schedule management. (2) Goal setting so engineers are working on tasks that feel fulfilling. (3) Giving time to “get into flow.”

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An Example Of LLM Prompting For Programming

- Martin Fowler tl;dr: Martin shows us how ChatGPT produces useful self-tested code. The initial prompt primes the LLM with an implementation strategy asking for an implementation plan rather than code. Once that plan is in place, it’s refined and the author uses it to generate useful sections of code.

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Measuring Developer Productivity And Happiness At LinkedIn

- Viktoras Truchanovicius tl;dr: We developed a new internal product called the Developer Insights Hub. It visualizes developer experience and happiness metrics describing key developer activities such code building, reviewing, publishing, as well as the sentiment towards the tools being used… this post provides an overview of how we approached metrics selection and design, system architecture and key product features.

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