RDEL #73: Our most popular posts of 2024
Impact of interruptions, developer thriving, onboarding, and AI adoption topped the list for our most popular posts.
Welcome back to Research-Driven Engineering Leadership. Each week, we pose an interesting topic in engineering leadership and apply the latest research in the field to drive to an answer.
As the year comes to an end, we’re looking back at the posts that got the most attention in 2024. The popularity of these posts reflect the sentiment of the year at large - a focus on intentionality, efficiency, and building resilience into the engineering organization. Enjoy!
1. What causes new engineers to “sink or swim”? (RDEL #41)
Research Focus: This study explores factors influencing the success or failure of new software engineers during onboarding. The core question addresses how companies can improve onboarding to minimize frustration, productivity loss, and turnover risks.
Study Methodology: Researchers at Seattle University conducted an online questionnaire with 104 early-career software engineers. Questions covered topics like job assignments, managerial support, job satisfaction, and suggestions for improving onboarding. Data analysis identified key contributors to successful (and challenging) onboarding experiences.
Top Findings:
Role clarity is essential: 38.5% of engineers reported not knowing what to work on during onboarding, causing distress and reduced productivity.
Managerial and team support greatly impacts success: 74.3% of engineers felt their manager supported their development, and 85.71% felt supported by their team.
Manager assignment gaps: 19.8% of engineers were not paired with a manager during onboarding.
Top recommendations for improvement included better training and structured work distribution.
Application for Engineering Leaders: To prevent "sink or swim" experiences, leaders should focus on:
Structured learning plans: Implement roadmaps, 30/60/90-day plans, and frequent check-ins to build context and domain knowledge systematically.
Clear role expectations: Repeatedly communicate and clarify role goals to guide skill development and foster independence.
Prepared first tasks: Assign tasks that incrementally build organizational understanding and confidence.
2. What Types of Interruptions Impact Developer Productivity Most? (RDEL #28)
Research Focus: Software engineers face frequent interruptions, both from external sources and self-initiated task switching, which significantly impact their productivity. Achieving "developer flow," or deep focus, is crucial for productivity but challenging in environments where tools and collaboration necessitate frequent context switching. This study explores which types of interruptions—self-imposed or external—are most disruptive to developer tasks and identifies factors that make certain tasks more vulnerable.
Study Methodology: Researchers at the University of Calgary used a mixed-methods approach, analyzing longitudinal data from nearly 5,000 tasks and conducting surveys with 132 software engineers. Through analysis, the researchers correlated task characteristics with the type and impact of interruptions, assessing factors like task priority, interruption type, and contextual variables such as the time of day.
Top Findings:
Self-interruptions are more disruptive to productivity than external interruptions, despite developers perceiving the opposite.
Contextual factors, like the type of interruption and time of day, have a stronger impact on disruption than task-specific factors like priority or difficulty.
Tasks that involve switching between programming and testing are particularly vulnerable to interruptions.
How strongly participants feel that the following statements lead to interruptions
Application for Engineering Leaders: to minimize the impact of interruptions:
Limit self-interruptions by reducing work-in-progress. Encouraging developers to focus on completing fewer tasks at a time lowers cognitive load and interruption risk.
Support deep focus time by limiting external interruptions, such as unplanned Slack messages or other asynchronous communications. Leaders can create protected "focus blocks" where developers are unavailable for external collaboration.
3. What Conditions Make Developers Thrive? (RDEL #57)
Research Focus: In the fast-paced world of software engineering, developers face high-pressure environments where technical skills alone aren't enough for success. This study examines the socio-cognitive factors that enable developers to thrive—not just survive—amid these challenges. Thriving encompasses both productivity and psychological well-being, leading to greater resilience, innovation, and engagement.
Study Methodology: Researchers analyzed survey data from 1,282 software engineers across various industries. They focused on four key dimensions of thriving (agency, motivation and self-efficacy, learning culture, and support and belonging) and tested how these dimensions interact with healthy metrics use (HMU) and visibility and value of work (VVQ).
Top Findings:
Key dimensions of thriving:
Agency: Developers thrive when they can influence decisions and take ownership of their work.
Motivation and self-efficacy: Passion for their work, confidence in their abilities, and visible progress drive thriving.
Learning culture: Continuous learning and knowledge sharing foster growth and innovation.
Support and belonging: Feeling supported and accepted enhances resilience.
Developer thriving mediates productivity: Thriving directly impacts perceived productivity and explains how healthy metrics use and value of work influence productivity.
Healthy metrics and visibility enhance thriving: The thoughtful use of metrics and the visibility of meaningful work bolster psychological safety and engagement.
The relationship between thriving, productivity, healthy metrics use, and visibility and value of work
Application for Engineering Leaders:
To cultivate resilient, high-performing teams that maintain productivity and well-being over the long term, look to incorporate the following areas of focus:
Psychological safety: Create an environment where team members feel safe sharing ideas and taking risks.
Purpose: Align team goals with a compelling mission to inspire engagement and motivation.
Strong relationships: Facilitate team bonding and collaboration to create a sense of belonging and mutual support.
4. What is the impact of AI adoption on engineering organizations? (RDEL #66)
Research Focus: The 2024 DORA report explores the widespread adoption of AI in software engineering (over 75% of respondents are currently using AI tools professionally). This study looks at how AI has affected individual productivity, team workflows, and organizational outcomes. Researchers aim to understand both the benefits and drawbacks of AI adoption, including its influence on key metrics like flow, job satisfaction, delivery performance, and product success.
Study Methodology: The DORA team conducted a large-scale survey of over 39,000 technical professionals across diverse roles and industries, supplemented by in-depth interviews for richer insights. Statistical models were used to analyze how AI adoption influenced individual, team, and organizational performance. They focused on AI's effect on productivity, workflows, and delivery metrics, alongside downstream impacts on team and product outcomes.
Top Findings:
Positive impacts of AI:
Enhanced flow, job satisfaction, and individual productivity.
Improved team workflows, especially in documentation, code quality, and code review speed.
The “vacuum hypothesis” for valuable work: AI expedites valuable work but has yet to address toilsome tasks, leaving opportunities for improvement in developer experience.
Negative impacts on delivery metrics:
Increased code generation led to larger change-lists, reducing delivery performance and stability.
Divergent impacts on outcomes:
Organizational and team performance improved due to better communication and knowledge sharing.
Product performance showed little improvement, which researchers hypothesis is because it relies more on human intuition and expertise, which AI has not impacted much.
Application for Engineering Leaders: AI adoption brings both opportunities and trade-offs for engineering teams. To maximize its benefits:
Set a clear vision: Define how AI aligns with organizational goals to ensure teams view it as a productivity accelerant.
Foster continuous experimentation: Encourage teams to iterate and explore new AI tools, while maintaining high standards for quality and measuring their effectiveness.
Be aware of trade-offs: Monitor challenges like reduced delivery stability and the evolving nature of valuable work to adapt strategies for developer experience.
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Finally, a short thank you. This has been a fantastic year for RDEL - we’ve built a strong following from researchers and practitioners alike who care about building great engineering cultures. We have also been so grateful to hear stories where RDEL led to powerful change in engineering team culture and productivity.
On a personal note, every RDEL has been a treat to write. We’re in an inflection point in the software engineering field, and research is helping guide our understanding of the best practices in this new paradigm. As a practitioner myself (and co-founder of Quotient), I’ve been able to use the research to improve the lives of our internal team and the lives of our customers. I hope that RDEL gave you an opportunity to improve your engineering teams as well.
We’ll be off for the rest of 2024 — wishing you a wonderful holidays, and of course…✨ Happy Research Tuesday! ✨
Lizzie