[1/2] Title: Developer Productivity for Humans (Category Management)

I decided to make a general post about articles in the series about the productivity of engineers from Google. This thought came after a recent story pro**Measuring Productivity: All Models are Wrong But Some are Useful"**The authors summarize their approaches and principles for building productivity models. Below is a list of articles in this series that I have already mentioned.

1) A Human-Centered Approach to Developer Productivity. This article began the series, and in it the authors described why they looked at the question of productivity of engineers not only from the point of view of process and technology, but also from the point of view of the people involved. Here they recall Taylor's science management (performance of the conveyor) And it shows why it's a little more difficult to develop approaches now:) Detailed analysis blogging 2) Enabling the Study of Software Development Behavior With Cross-Tool Logs. Article 2020 The year, where the authors from Google talked about the creation of their system InSession, which allows you to conduct a comprehensive analysis of the behavior of engineers by integrating logs from a variety of development tools. Detailed analysis is available in separate post in tg 3) Measuring Developer Experience With a Longitudinal Survey. A story about long-term studies in the form of surveys that are conducted with 2018 years. Surveys are one of the pillars for collecting productivity information, along with logs. The authors share insights on how to build such a program in their company and what it allows to measure. Discussion is in separate post in tgWe also worked with this white paper in 10 podcast Research Insights Made Simple with Artem Aryutkina n 4) Measuring Developer Goals. In this paper, the researchers described how understanding and effectively measuring goals is critical to improving the developer experience and improving their effectiveness. To answer questions about productivity, it is more convenient to link measurements not to specific tools, but to the goals that developers set for themselves when using tools. This allows you to answer questions similar to those above, keeping metrics user-centric rather than a tool. Detailed analysis bloggingand also podcast Research Insights Made Simple, where we discussed this article with Sasha Kusurgashev, my colleague who directs the development of Spirit. (Our internal development platform) 5) What Do Developers Want From AI?. Here, the authors say that the evolution of AI is a turning point, but with technological revolutions that change the format of human work, humanity faces not for the first time. Therefore, the authors of the article decide to draw parallels between AI and the development of the automotive industry and focus on the needs and goals of our developers. Discussion is in separate post in tgWe have also discussed this article in ninth edition Research Insights Made Simple with Kolya Bushkov, my colleague at the RnD Center. 6) Software Quality. A cool article where the authors discuss a holistic approach to measuring productivity should pay attention to speed, ease and quality in order to avoid short-term improvements due to long-term negative effects. And then the kids focus on the quality theme that touches on processes, code, system and product as a whole. This topic is very close to me, as it intersects very closely with architecture and architectural characteristics:) Detailed analysis blogging 7) Defining, Measuring, and Managing Technical Debt. An interesting discussion of the concept of technical debt, as well as an example of how it was measured at Google and how it was dealt with with with good results. I have a detailed analysis. bloggingWe also worked on this whitepaper together with Dima Gaevsky. Next Next post: Review Insights Made Simple

The end of the article in this series next post.

#Engineering #Software #Bigtech #Productivity #Management #Leadership #Processes