- Pointer
- Posts
- Issue #559
Issue #559
Essential Reading For Engineering Leaders
Friday 18th October’s issue is presented by Knock
Building product notifications gets complicated fast. Knock abstracts away the complexity and gives you:
A single api to send multi-channel notifications (email, slack, in-app, etc).
Embeddable UIs to ship in-app feeds and inboxes quickly while keeping your design on brand.
Observability and analytics about message and user behavior, delivered to any tool of your choice (Datadog, etc).
— Will Larson
tl;dr: Will reflect on his shift from a 'company, team, self' framework to an eventual ‘quid pro quo' approach during his management tenure at Uber. His ‘quid pro quo' approach is: (1) Generally, prioritize company and team priorities over your own. (2) If you are getting de-energized, artificially prioritize some energizing work. Increase the quantity until equilibrium is restored. (3) If the long-term balance between energy and proper priorities can’t be balanced for more than a year, stop everything else and work on solving this issue e.g. change your role or quit. Will emphasizes the importance of remaining flexible and curious.
CarerAdvice Leadership Management
— Gergely Orosz
tl;dr: Gergely asked several software engineers and engineering leaders why they left the lure of big tech. He covers: (1) How big tech is less stable than it was. (2) Professional growth in a startup environment vs big tech. (3) Closed career paths. (4) Employees being forced out due to politics. (5) Scaleups becoming “too Big Tech.” (6) Steep compensation drops. (7) Raw feedback.”
CarerAdvice
— Sam Seely
tl;dr: A complete guide to evaluating a build vs. buy decision for products transactional notification system. This piece covers the challenges faced by teams evaluating whether to build or buy a notification system, what notification systems look like at scale and the requirements they share, how to use a framework to assess any build vs buy decision, how to apply that framework against the build decision for a notification system.
Promoted by Knock
Guide Management
— Dario Amodei
tl;dr: From the CEO of Anthropic: “The list of positive applications of powerful AI is extremely long, but I’m going to focus on a small number of areas that seem to me to have the greatest potential to directly improve the quality of human life. The five categories I am most excited about are: (1) Biology and physical health. (2) Neuroscience and mental health. (3) Economic development and poverty. (4) Peace and governance. (5) Work and meaning.
ThoughtPiece
“The production of too many useful things results in too many useless people.”
— Adam Bender
tl;dr: “The test pyramid is the canonical heuristic for guiding test suite evolution. It conveys a simple message - prefer more unit tests than integration tests, and prefer more integration tests than end-to-end tests. While useful, the test pyramid lacks the details you need as your test suite grows and you face challenging trade-offs. To scale your test suite, go beyond the test pyramid. The SMURF mnemonic is an easy way to remember the tradeoffs to consider when balancing your test suite.”
Tests
tl;dr: BlueOptima's study of 200,000+ enterprise developers uncovered surprising insights on the reality of Generative AI: (1) Only 12% of developers commit GenAI code without modification, suggesting limited real-world integration. (2) Modest productivity gains of only 4%, indicating marketing claims are premature. (3) A decline in quality with high AI usage.
Promoted by BlueOptima
Management Productivity AI
— Thorsten Ball
tl;dr: “How I use git is based on the last 12 years of working in companies with smallish (less than 50) engineering teams. In every team, we used git and GitHub exclusively; changes were made in branches, proposed as pull requests, and then merged into the main branch. In the last few years, after GitHub introduced squash-merging, we used that.”
Git
tl;dr: Netflix developed the TimeSeries Abstraction — a versatile and scalable solution designed to efficiently store and query large volumes of temporal event data with low millisecond latencies, all in a cost-effective manner across various use cases. “In this post, we will delve into the architecture, design principles, and real-world applications of the TimeSeries Abstraction, demonstrating how it enhances our platform’s ability to manage temporal data at scale.”
TimeData Architecture
— Fernando Hurtado
tl;dr: “If you've ever worked on refactoring or improving performance in a software system, you've probably run into a particular frustration: abstraction-heavy codebases. What looks like neatly organized and modularized code often reveals itself as a labyrinth, with layers upon layers of indirection. The performance is sluggish, debugging is a nightmare... This leads us to an important realization: not all abstractions are created equal. In fact, many are not abstractions at all—they're just thin veneers, layers of indirection that add complexity without adding real value.”
SoftwareDesign
Notable Reading
Workspaces is a free weekly newsletter that gives a behind-the-scenes tour of interesting and productive desk setups.
Join 14,000 other readers from companies like Meta, Snap, TechCrunch, Instagram, The New York Times, and more.
Most Popular From Last Issue
The Senior Shortcut — Camille Fournier
Notable Links
Clipscreen: Virtual monitor that mirrors a portion of your screen.
Friday Deploys: Apparel and accessories for work and leisure.
Ladybird: Truly independent web browser.
Manim: Animation engine for explanatory math videos.
Siyuan: OS personal knowledge management software.
How did you like this issue of Pointer?1 = Didn't enjoy it all // 5 = Really enjoyed it |