Parse notes
Scalability is a system's ability to handle increasing workloads by adding resources, preventing slowdowns as it grows. Systems grow through increased users, features, data, complexity, and/or geographic locations. To make a system scalable, devs can use techniques like vertical and horizontal scaling, load balancing, caching, and CDNs.
An iOS app has sophisticated anti-debugging techniques, such as preventing debugger attachment, causing phone reboots, and crashing upon code injection. To tackle these problems, the developer first identified the use of the ptrace(PT_DENY_ATTACH) function and then showed two methods to bypass it: a simpler method involving breakpoints, and a more involved approach analyzing the app's assembly code to locate and skip the relevant system call. The phone reboot was actually caused by an infinite loop continuously taking screen snapshots, easily bypassed by using `thread return` in LLDB to skip the offending function. Finally, the code injection crash is from the app's reliance on an app group that gets removed during resigning, which was fixed by avoiding resigning or using a jailbroken device.
Working on a legacy project challenges your current knowledge and provides important insights into why today's best practices are the way they are. Seeing outdated practices in old codebases enforces the value of current ones.
Generative AI is full of hype and misleading marketing, despite massive investment. Many of the products coming out of the industry are often poorly executed and overly expensive. It's possible that the current generative AI boom is a bubble.
Platform teams struggle when balancing roadmap progress with constant ad hoc requests, leading to burnout and lost trust. To escape this cycle, they must set strict constraints, track time spent, and deliver small, tangible improvements consistently.
VimLM is a Vim plugin with a LLM-powered coding assistant similar to GitHub Copilot. It uses local MLX-compatible models, therefore working completely offline. It provides contextual code understanding and AI-assisted features through Vim keybindings, where users can interact with the LLM via prompts (with context included).
Scira is an AI-powered search engine that uses various APIs (including Anthropic, Tavily, and several others) for web search, code execution, map integration, and more. It's built with Next.js, Tailwind CSS, and the Vercel AI SDK, and instructions for setting it as a default search engine are provided.
Small, independent software companies are viable alternatives to the "grow or die" mentality of Silicon Valley. For example, SQLite, Pinboard, Tarsnap, Sublime Text, and Zig are all examples of how small teams, even solo developers, can build successful, sustainable businesses.
Vite is a fast and lightweight way to start a React project, while Astro is better for content-focused websites. Next.js is a full-stack framework with built-in features like SSR, RSC, and file-based routing, which makes it well-rounded and powerful, but also more complex.
The core part of a web extension is its `manifest.json` file, which helps define extension components like popups and content scripts. Extensions can also have content scripts and background scripts to interact with web pages and run tasks.
Frames of Mind allows you to visualize the "thought process" of a language model (DeepSeek R1) by converting its chains of thought into embeddings, plotting them using t-SNE, and analyzing the distances between consecutive thoughts to identify phases like "search," "thinking," and "concluding."
This is a free online guide to SQL performance optimization, focusing on indexing for developers by explaining index structure, efficient query writing, and common pitfalls.
A privacy advocate argues against the "privacy is dead" and "all-or-nothing" mindsets, instead encouraging incremental improvements in personal data privacy.
After installing a washing machine in a new house, which unexpectedly took four hours instead of ten minutes due to unforeseen complications, this dev found it similar to how difficult it is to accurately estimate software development effort due to “unknown unknowns.”