Parse notes
This article goes over how to build a key-value database from scratch. It starts with a simple file-based approach for storing data, but explains its inefficiency for updates and deletes. It then introduces append-only files, compaction strategies to manage file size, and indexing to improve search performance. Finally, it explains how these techniques combine to form a Log-Structured Merge Tree (LSM Tree), used in many real-world key-value databases.
Idealist reduced its Heroku costs by switching its staging environments to a single, cheaper server. By sharing a single Postgres instance across multiple isolated staging environments, it avoided Heroku's per-environment pricing model and expensive add-ons.
This is a system for measuring engineering productivity effectively, with an emphasis on visibility and context over strict numerical evaluation. Solid productivity happens by starting small, being explicit with expectations, and being open to feedback to ensure the system serves as a tool for improvement rather than a weapon for punishment.
Businesses often try to eliminate developers, believing they can achieve software benefits without them, but this approach consistently fails. The core issue is that software development isn't just about production, it's about understanding and adapting to complex business needs, which cannot be outsourced, automated, or abstracted away.
AI-assisted coding, despite its impressive capabilities, may be addressing the wrong problem in software development. AI agents often recreate existing code due to the nature of LLMs and training data. Furthermore, AI is primarily benefiting less experienced developers and masking underlying issues like inadequate software engineering education and a focus on speed over quality.
The rise of AI and LLMs threatens the core identity of programmers as craftspeople. Vibe-coding and specification engineering have turned programmers into operators rather than creative problem-solvers. This shift removes a lot of the joy and fulfillment of programming.
OpenAI has released a new browser, ChatGPT Atlas. It allows users to open a ChatGPT sidebar for content summarization, data analysis, and product comparison on any website. It remembers user preferences and browsing history (with privacy controls) to provide relevant and personalized details. It also allows ChatGPT to interact with sites to complete tasks like research and shopping.
Next.js 16 is now available, with improvements to Turbopack, caching, and the Next.js architecture. This release introduces Cache Components for more explicit caching, Next.js DevTools MCP for AI-assisted debugging, and proxy.ts to clarify the app's network boundary. Turbopack is now the default bundler, offering faster builds and refreshes, and the update also has better routing, improved caching APIs, and React 19.2 features.
Katakate is an open-source platform for creating and managing secure, lightweight VM sandboxes for executing untrusted code at scale. It uses Kubernetes, Kata, and Firecracker. It offers a CLI, API, and Python SDK for managing sandboxes, and caters to use cases such as AI agents, custom serverless functions, and hardened CI/CD runners.
Continuous exposure to low-quality, "junk" web data can cause a lasting cognitive decline in LLMs. Through controlled experiments, researchers found that pre-training LLMs on data from X selected for high engagement or sensationalism negatively impacted reasoning, long-context understanding, and ethical behavior. The primary error was identified as "thought-skipping," where models truncated reasoning steps, and standard fine-tuning methods only partially mitigated the damage, showing a persistent change in the models' representation.
Power over Ethernet (PoE) delivers both data and power over standard Ethernet cables to devices like IP cameras and VoIP phones. This article explains the difference between endspan (PoE-enabled switches) and midspan (PoE injectors) devices, along with the evolution of PoE standards (IEEE 802.3af/at/bt) to support higher power levels.
Claude Code can be used to get DeepSeek-OCR running on an NVIDIA Spark by automating the process within a Docker sandbox. Initially, Claude Code struggled to do this due to PyTorch and CUDA compatibility issues, but after being suggested different PyTorch versions, Claude Code found a compatible version and completed the task. Claude Code generated notes, scripts, and documentation, including a performance comparison of different prompts for OCR.
A Linux kernel maintainer used AI to generate code and backports, resulting in vulnerabilities, bugs, and sloppy commits in Linux LTS kernels.
Wikipedia's human page views are declining due to the rise of AI search summaries and the increasing reliance on social video platforms for information.
Just use cURL for making HTTP requests, instead of using bloated and unnecessarily complex GUI-based alternatives.
Data processing has shifted away from thread-per-core models due to increasing core counts, improved IO speeds, and the need to handle skewed data distributions effectively at the data processing layer itself.