#633 – July 06, 2025
beyond the vibes
Augmented Coding: Beyond the Vibes
8 minutes by Kent Beck
Kent's exploration of implementing B+ Tree library in both Rust and Python using "augmented coding," where AI assists in code generation while maintaining high quality standards. His experience shows that while AI transforms programming, it enhances rather than diminishes the profession by eliminating tedious tasks and allowing developers to focus on important decisions.
OWASP Top 10 for LLMs
sponsored by Snyk
LLMs introduce new security challenges. In this live session, Snyk expert and OWASP Leader, Vandana Verma Sehgal, will present the OWASP Top 10 for LLMs, detailing key vulnerabilities and sharing actionable strategies for securing AI-assisted development in real-world environments. Avoid threats like prompt injection, model poisoning, and learn the best practices for handling AI-generated code securely. Join the webinar on July 15 11:00am ET.
Driving content delivery efficiency through classifying cache misses
12 minutes by Vipul Marlecha
In this post, Netflix team discusses one of the frameworks they use to evaluate efficiency and identify sources of inefficiencies. Specifically, they classify the causes of traffic not being served from local servers, a phenomenon that they refer to as cache misses.
Coding agents have crossed a chasm
11 minutes by David Singleton
Somewhere in the last few months, something fundamental shifted for me with autonomous AI coding agents. They’ve gone from a “hey this is pretty neat” curiosity to something David can’t imagine working without. Not in a hand-wavy, hype-cycle way, but in a very concrete “this is changing how I ship software” way.
The Heart of Software Engineering Still Beats
14 minutes by Annie Vella
Annie reflects on a colleague's ability to read and debug code without being able to write it, challenging assumptions about coding skills. She explores how programming is fundamentally about mental modeling and design rather than just syntax, and considers how AI coding tools are transforming the profession.
Bloom Filters by Example
5 minutes by Bill Mill
A Bloom filter is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set. The price paid for this efficiency is that a Bloom filter is a probabilistic data structure: it tells us that the element either definitely is not in the set or may be in the set.
And the most popular article from the last issue was: