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Most GPG documentation I could find was outdated -- O'Reilly 1995, No Starch 2006, countless websites from the mid 00s -- or scattered across dozens of blog posts that each covered one piece. I wanted a single reference that covered the full workflow with current tools and practices, so I had been keeping a bunch of text files in my homedir for a while. Recently I realized it was getting close to 60k words and I decided I should share it.

The guide covers GnuPG 2.5.x and Sequoia sq, defaults to Ed25519, and has three reader tracks: a minimal Git + SSH setup, a full YubiKey identity, and a high-assurance path for FOSS package maintainers and the like. 377 pages across 16 parts, with platform-specific instructions for Linux, macOS, and WSL.

Parts I–III are available as a sample download. I'd be really grateful for any feedback, as I have never written a book before and, frankly, have no business doing it.

The article explores the importance of memory allocators in computer systems, discussing their role in managing dynamic memory, the trade-offs between different allocation strategies, and the challenges involved in designing efficient and robust allocators.

The article discusses the concept of permanent links, also known as permalinks, which are URLs that remain consistent over time, allowing users to reliably access content. It explores the historical development and importance of permalinks in the evolution of the web.

The article explores the process of chipping away at data to uncover insights, highlighting the importance of careful analysis and identifying meaningful patterns in complex datasets.

The article discusses how vehicle automation could transform the traditional concept of rush hour traffic. It explores how autonomous vehicles could optimize traffic flow, reduce congestion, and change commuting patterns, potentially leading to a more efficient and less stressful transportation system.

The article proposes a novel neural network architecture, called the Transformer, that uses self-attention mechanisms to achieve state-of-the-art performance on various natural language processing tasks, including machine translation, text summarization, and language modeling.

The article provides technical details on the American Fuzzy Lop (AFL) tool, which is a coverage-guided, compile-time instrumentation fuzzer for finding security vulnerabilities in software. It discusses the tool's architecture, instrumentation process, and its effectiveness in uncovering hard-to-find bugs.

Hi HN, I’m the developer of HZ Chat.

HZ Chat is a simple session-based chat tool for quick conversations. It’s designed for moments where you just need to talk and move on.

Chats are tied to active sessions and automatically end after inactivity.

Happy to answer any questions or hear feedback.

The article explores the ongoing investigation into the SolarWinds cyberattack, which involved a sophisticated supply chain compromise affecting numerous organizations. It delves into the complexity of the attack and the challenges faced by security researchers in unraveling the mystery behind the incident.

The article discusses issues with the setuptools library in Python, specifically related to problems with zip file support and the inability to install packages from local directories. The main focus is on addressing these technical problems and improving the overall user experience for developers working with setuptools.

I built VibeDB, a tiny local database for small end-user tools and side projects: store whatever object shape you want, without setting up a DB or designing schemas upfront.

Why

When building small utilities (CLI tools, desktop scripts, lightweight web apps), I often need “a bit of persistence” (settings, history, cached results, user data), but I don’t want to stop and set up Postgres/Mongo, write migrations, or keep switching to ad-hoc SQL. I wanted persistence to feel like “just store objects” and keep everything in one local file.

What it is

Zero config: one local file

Document-style: store nested objects / mixed shapes (schema-later)

Query without SQL: simple dict filters or a small query builder

Optional Studio UI to inspect/edit/query data locally

The article discusses how the availability of cheap and abundant computational power has led to a lack of judgment and critical thinking, as people rely heavily on algorithms and automation to make decisions. It emphasizes the importance of maintaining human judgment and decision-making skills in an era of abundant execution capacity.

A massive data breach at the Dutch financial firm Odido has led to the exposure of personal and financial information of millions of customers, which has now fallen into the hands of criminal elements.

The Trump administration is working to expand the effort to strip citizenship from foreign-born U.S. citizens, a process known as denaturalization. This move represents a significant escalation in the administration's crackdown on immigration.

I built mem, a deterministic CLI-first memory sidecar for dev workflows.

It stores append-only JSONL events (commits, agent runs, decisions) and deterministically compacts to state.json + MEMORY.md so humans/agents can recover context quickly.

Design constraints: - local files only - no network access at runtime - no daemon - POSIX sh + jq tooling

I’d love feedback on: 1) data model / event schema 2) compaction strategy 3) where this breaks in real team workflows

Hey HN, I'm Kristiyan. I previously led Redis Insight (the official Redis GUI). When I started working with Valkey, I found the observability tooling lacking — so I started building BetterDB.

The core problem: Valkey and Redis expose useful operational data (slowlog, latency stats, client lists, memory breakdowns), but it's all ephemeral. Restart your server and it's gone. Existing tools show real-time charts but can't tell you what happened at 3am when your p99 spiked.

BetterDB persists this ephemeral data and turns it into actionable insights:

- Historical analytics for queries (slowlog and commandlog patterns aggregated by type), clients (commands, connections, buffers), and ACL activity - Anomaly detection and 99 Prometheus metrics - Cluster visualization with topology graphs and slot heatmaps - Automated latency and memory diagnostics - AI assistant for querying your instance in plain English (via local Ollama) - Sub-1% performance overhead

On that last point — I wrote up our interleaved A/B benchmarking methodology in detail: https://www.betterdb.com/blog/interleaved-testing. Most tools claim "minimal overhead" without showing their work. We open-sourced the benchmark suite so you can run it on your own hardware and verify.

You can try it right now:

    npx @betterdb/monitor

    docker run -d -p 3001:3001 betterdb/monitor

We're building this in public — the benchmark suite, the technical blog posts, and the roadmap are all out in the open. Would love feedback from production users of Valkey or Redis on what observability gaps you're still hitting.

GitHub: https://github.com/BetterDB-inc/monitor Blog: https://www.betterdb.com/blog

The article explores the historical development of barbed wire fence telephone networks, tracing their origins and evolution as a communication tool in rural areas during the late 19th and early 20th centuries.

Hey HN. I built a financial intelligence skill for OpenClaw that turns your AI agent into a stock analyst.

Ask your agent 'how's $NVDA looking?' and you get back: momentum score (0-100), RSI, EMA alignment, coil breakout detection, bull/bear cases, and what to watch for. Not a price quote — a full intelligence briefing.

ClawHub has 5,700+ skills but zero equities intelligence. 672 financial skills were excluded for malware. I wanted to build something legitimate and transparent.

The data: 900+ days of backtested signals. 12,450+ total. 80% 5-day win rate, +4.51% average return. Win rate improves with holding period (76.5% at 1 day to 80.1% at 1 month). Every win and every loss tracked.

Technical: 7 Python scripts, zero pip dependencies (stdlib only). MIT licensed. VirusTotal verified clean.

Free tier available, no credit card. For comparison: Polygon.io charges $79-199/mo for raw data with no intelligence layer.

Would love feedback on the skill structure or scoring methodology. Happy to answer technical questions.

The Mexican government has seized a large quantity of powerful .50 caliber ammunition, with the defense minister stating that nearly half of it came from a U.S. Army plant. This raises concerns about the flow of illicit weapons from the U.S. to Mexico, where drug cartel violence remains a major issue.

A party line is a telephone line shared by multiple subscribers, allowing them to communicate with each other. This technology was commonly used in rural areas before the widespread adoption of individual telephone lines.

The article discusses the resurgence of CDs in the music industry, analyzing industry data and trends. It examines the factors driving the comeback of CDs, including nostalgia, audiophile demand, and limitations of streaming services, and explores the potential implications for the future of music consumption.

The article discusses the reaction of amateur internet detectives to a high-profile kidnapping case, highlighting their belief that they can solve the mystery using unconventional methods, despite a lack of evidence or official involvement.

The article discusses the Web Media Capture and Playback (WebMCP) Encrypted Playback Proposal (EPP), a new web standard that aims to enable secure playback of encrypted media on the web without requiring additional plugins or third-party software. The proposal aims to provide a consistent, cross-browser solution for encrypted media playback that enhances user privacy and security.