Issue #619

Essential Reading For Engineering Leaders

Tuesday 27th May’s issue is presented by Readyset

Your engineers shouldn’t be stuck rewriting queries, tuning infra, or chasing latency spikes. Readyset is a drop-in cache for Postgres and MySQL that delivers:

  • 100K+ queries per second

  • Sub-millisecond latency

  • Effortless scale for launch days and traffic spikes

All without code changes, infra overhauls, or migrations. Cut database spend, reduce latency, and give your team time back to build.

— 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.

Leadership Management

— Will Larson

tl;dr: Will covers the following: (1) Working in the details - how 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.

Leadership Management

— 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.

Promoted by Readyset

Management Database

— 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.”

Leadership Management

"Followers who tell the truth, and leaders who listen to it, are an
unbeatable combination."
 

- Warren Bennis

— Gergely Orosz, Chip Huyen

tl;dr: The authors discuss: (1) Three layers of the AI stack. Application development, model development, infrastructure. (2) AI engineering versus ML engineering. Similarities and differences. (3) Application development in AI engineering. The three main focus areas: evaluation, prompt engineering, and AI interfaces. (4) AI Engineering versus full-stack engineering.

DeepDive AI

tl;dr: Postman’s new Spec Hub lets you design, lint, test, and document APIs - without jumping between tools or breaking developer workflow - providing end-to-end API design and governance, with BYOK encryption for full data control.

Promoted by Postman

Security API

— Alex Kladov

tl;dr: When asserting implications, common code patterns can be confusing. Alex shares a clearer alternative. 

BestPractices

— Jim Gumbley, Gayathri Mohan

tl;dr: At its heart, threat modeling is a risk-based approach to designing secure systems by identifying threats continually and developing mitigations intentionally. We believe effective threat modeling should start simple and grow incrementally, rather than relying on exhaustive upfront analysis. To demonstrate this in practice, we begin with outlining the core insights required for threat modeling. We then dive into practical threat modeling examples using the STRIDE framework.

SystemDesign

tl;dr: Uber’s online storage solutions hold 10s of petabytes to serve critical business operations. They also serve millions to billions of requests per second across Uber’s global business verticals. With that scale, close to 100 PB of data is backed up from databases at different intervals. TBs to PBs of data can be restored within a few minutes to a few hours. This blog describes recent developments in Uber’s robust backup recovery system for online databases.

Architecture

Defuddle: Extract the main content from web pages.

F2: Command-line batch renaming.

Prompt Kit: Components for AI applications.

Qlib: AI-oriented quantitative investment platform.

ToGo: Terminal-based to-do manager.


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