/Management

What Real Feedback Sounds Like

- Claire Lew tl;dr: Claire shares 7 of the most common situations where feedback often gets delayed, watered down, or avoided entirely. For each, she shares the vague or sugarcoated way it usually gets said, and how to communicate what real, respectful feedback actually sounds like instead.

featured in #619

Stuff I Learned At Carta

- Will Larson tl;dr: Will covers the following topics (1) Working in the details: Effective leadership requires diving deep into specifics, not just high-level abstractions. (2) Refining engineering strategy. (3) Extract the kernel: Teams gain power by actively clarifying executive communication. (4) Meaningfully adopting LLMs: Real business integration of AI involves balancing rapid adoption and uncertainty. (5) Multi-dimensional tradeoffs: Recognizing varying decision-making perspectives enhances clarity.

featured in #619

Why Query Caching Is the Most Cost-Effective Way To Scale Databases

- Gautam Gopinadhan tl;dr: Most teams try to scale databases by throwing hardware at the problem, duplicating data, or rewriting slow queries, often at great cost. But there's a quieter and far more efficient path: SQL-layer query caching. It cuts load, reduces tail latency, and simplifies scaling, without migrations or infrastructure sprawl.

featured in #619

When A Team Is Too Big

- Alex Ewerlöf tl;dr: “There’s a story for several years back that keeps back to my mind. What makes it interesting is the fact that there was no master plan. Yet with a few cultural elements, the story took such an interesting trajectory that it shaped my leadership model. Ever since, I have been an advocate of continuous improvement by preparing the environment instead of being the wise-ass who has the ultimate solution to all problems.”

featured in #619

A Technology Leader's Non-Technical Reading List

tl;dr: “I’ll share my personal favorite reading materials that have helped me think about leadership, management, people and technology.” There were a few main themes that drove the authors interest notably books that display different examples of management, people working together and those that challenge the author’s current world view. 

featured in #619

A Technology Leader's Non-Technical Reading List

tl;dr: “I’ll share my personal favorite reading materials that have helped me think about leadership, management, people and technology.” There were a few main themes that drove the authors interest notably books that display different examples of management, people working together and those that challenge the author’s current world view. 

featured in #618

Aim Small, Miss Small

- Mike Fisher tl;dr: "Aim small, miss small" is a phrase often used in marksmanship and sports. It means that by focusing on a small, specific target, your margin of error shrinks, if you miss, you still miss small. At its core, it’s a simple but powerful idea: the tighter you define your target, the more you minimize the consequences of a miss.

featured in #618

5 Strategies To Address Android Emulator Instability During Automated Testing

- John Gluck tl;dr: Android emulators are powerful, flexible, and essential for scaling mobile test automation — especially when you're running thousands of E2E tests across environments. But like any tool, they need the right setup.In this blog post, QA Wolf shares 5 key strategies that help you: Reduce flakiness, maximize emulator performance, keep tests running fast and reliably at scale. If you're running automated tests for Android, this is how to get the most out of your emulators.

featured in #618

What Causes Procrastination For Software Engineers?

- Lizzie Matusov 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?”

featured in #618

How Google Is Accelerating Code Migrations With AI

- Abi Noda tl;dr: “While migrations are one of the most necessary parts of software maintenance, they can be time-intensive, costly, error-prone, and unrewarding for developers, making them a great candidate for using AI. Google's system solves this by identifying code that needs changing, using an LLM to generate updates, validating the changes through several checkpoints, and routing successful modifications for human review. Today the system runs nightly, continually chipping away at the migration task until complete. In this paper, the authors describe how the system works, its results, and its benefits and challenges.”

featured in #617