tl;dr:“As engineering teams spread across time zones, coordination becomes a balancing act between responsiveness and deep work. With Slack threads piling up and meetings crossing time zones, the real challenge isn’t communication—it’s coordination. This week we ask: What does effective coordination look like in globally distributed teams—and how should teams balance meetings and async tools like Slack?”
tl;dr:“Code reviews are foundational to modern software development—but how do experienced developers actually read, understand, and evaluate changes? What mental models do they use, and how can we better support those strategies across teams and tools? This week we ask: How do experienced engineers comprehend code during review, and what can leaders do to support more effective, scalable review practices?”
tl;dr:“Code reviews are foundational to modern software development—but how do experienced developers actually read, understand, and evaluate changes? What mental models do they use, and how can we better support those strategies across teams and tools? This week we ask: How do experienced engineers comprehend code during review, and what can leaders do to support more effective, scalable review practices?”
tl;dr:“Software development is full of friction points—vague tickets, shifting priorities, and cognitively demanding tasks that are hard to start.But what causes those delays, and what can teams do to mitigate the impact without killing momentum? This week we ask: Why do developers procrastinate—and how can teams mitigate its negative impacts?”
tl;dr:“Researchers conducted a study inside the software division of Beko, a multinational electronics company. Over 10 months, 238 developers used an AI-based code review tool powered by GPT-4. The study analyzed 4,335 pull requests across three projects, comparing automated vs. manual review patterns, survey feedback, and developer behavior.”
tl;dr:“Researchers conducted a 10-day field experiment with 260 elite software engineers. Participants were randomly assigned to 52 globally distributed five-person teams on a crowdsourcing platform. Each team collaborated asynchronously to solve a real-world software problem — designing an algorithm to optimize medical kits for spaceflight. The researchers analyzed communication patterns and outcomes to identify which behaviors predicted the most success outcomes.”
tl;dr:“Researchers from Microsoft and the Institute for Work Life ran a three-week randomized controlled trial of GitHub Copilot with 228 engineers at a large global software company. Engineers were randomly assigned to one of three groups: those newly given access to GitHub Copilot and instructed to use it (treatment), those asked not to use any AI tools (control), and those who were already using Copilot (continuing). Over three weeks, participants in all groups completed daily diary entries. Researchers also collected telemetry data to observe behavioral patterns alongside shifts in beliefs and attitudes.”
tl;dr:Key findings include: (1) Performance and productivity are impacted by interruptions, in nuanced ways. (2) The type of task, and type of interruption, changes the stress associated with an interruption. (3) Perception and physiological data don’t always align. Lizzie elaborates on each.
tl;dr:(1) Agency: Developers have the ability to voice disagreements and influence how their work is measured, which empowers them to take ownership of their contributions. (2) Motivation and Self-Efficacy: A developer’s motivation to work on code they are passionate about, confidence in their problem-solving abilities, and the sense of making tangible progress. (3) Learning Culture: A thriving environment encourages continuous learning and sharing of knowledge among team members, fostering growth and innovation. (4) Support and Belonging: The feeling of being supported by their team and accepted for who they are.
tl;dr:Consider these tips to more effectively ramp up new teammates: (1) Structure early learning opportunities. New engineers can more quickly ramp up to the context and domain knowledge required to do their work. (2) Be clear about role expectations. Establishing clear expectations for the role is often overlooked in the chaos of growing a team. (3) Prepare the first few tasks ahead of time. Give engineers a series of tasks that build on organizational and system context so they can apply their knowledge more directly and build confidence.