Research Insights Made Simple 9 "What Do Developers Want From AI?" (AI column)

In this podcast It’s called “What Do Developers Want From AI?” wrote earlier. To discuss it, I invited Nikolai Bushkov from the T-Bank RnD Center to visit. Nikolai is engaged in engineering productivity research and is deeply immersed in how AI can improve engineering processes. By the way, here you can read more about RnD Center T-Bank and engineering productivity.

We discussed the following topics.

1. Introduction to the topic: AI and developers
2. Metaphors of technological change (parallels with electrification)
3. Three Levels of AI Improvements (parallels with the automotive industry)
4. Approaches to measuring productivity (polling-log)
5. Code review and the role of AI (case studies)
6. Documentation and technical debt problems
7. Platform approach to tools
8. Agent systems and the meta-level
9. Productivity research and collaboration (Examples from Google and T-Bank)

We also mentioned other scientific articles that fit well into the topic of discussion.

1. "Measuring developer goalsFrom Google, we discussed it in the Previous Research Insights Series along with Sasha Kusurgashev, and I had sammari according
2. "Resolving code review comments with MLGoogle – I haven’t written about it yet, but I’ll be reviewing it soon.
3. "BitsAI-CR: automated code review via LLM in practiceFrom ByteDance, there will also be a review.
4. "Defining, Measuring, and Technical DebtFrom Google, we discussed it in the One of the Research Insights series along with Dima Gaevsky, and I had sammari article
5. "Build Latency, Predictability, and Developer ProductivityFrom Google -- I had sammari article

Episodes available on Youtube, VK Video, Podster.fm, Ya Music.

#Management #Leadership #Software #SoftwareDevelopment #Metrics #Devops #Processes #AI #ML #DevEx