/Abi Noda

What Predicts Software Developers’ Productivity? 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.

featured in #451

Enabling Good Work Habits Through Reflective Goal-Setting tl;dr: Abi highlights a study on developers' productivity, revealing that reflective goal-setting leads to improvements. 84% of participants identified concrete goals through reflection, 80% saw positive behavior change, and 92% planned to maintain new habits. The key takeaway is that reflective goal-setting not only enhances awareness and productivity but also encourages lasting behavioral changes, empowering developers to gain control over their work.

featured in #438

Build Times And Developer Productivity 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.

featured in #431

What Drives Adoption Of Internal Developer Tools? tl;dr: The highest priority adoption factor for 4 types of internal tools: (1) For build tools, it is whether the tool is highly configurable. (2) For continuous integration tools, it’s whether the tool is compatible with the technologies developers use. (3) For infrastructure as code tools, it’s how visible the usage of the tool is within the organization. (4) For version control tools, it’s whether the tool fits well with the way developers work.

featured in #425

How Google Measures And Manages Tech Debt tl;dr: The first part describes the categories of tech debt and the second part explores how categories may be measured, providing insights on how to determine whether teams are struggling with technical debt and the types of tech debt they’re struggling with. The final part of this paper provides several tactics that may help reduce tech debt. 

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DevEx: What Actually Drives Productivity 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.

featured in #417

10 Years Of Tech Debt Research tl;dr: Abi recommends to better communicate and manage tech debt by: (1) Moving away from using the phrase “technical debt.” (2) Defining what the problem really is. He explains why in this post.

featured in #415

Measuring Flow And Focus 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.”

featured in #412

The Case Against Measuring Cycle Time tl;dr: “There are cases in which individual teams may find cycle time useful. However, using cycle time as a top-level performance measure that is pushed onto all teams is counterproductive. To actually improve performance, leaders should focus on measuring the friction experienced by developers and removing the bottlenecks that slow them down.”

featured in #409

Three-Bucket Framework For Engineering Metrics tl;dr: “CEOs don’t know or care about the technicalities of engineering measurement; what they really want is a way to have confidence that you’re accountable for the millions of dollars they are spending on engineering.” Abi argues that you should be concerned about 3 types of metrics as an engineering leader: (1) Business impact: Current or planned projects, and project roadmap. (2) System performance: Reliability, speed and user experience. (3) Developer effectiveness.

featured in #397