🛠️ All DevTools

[Other] Reproducible C++ builds by logging Git hashes

[CLI Tool] CLI tool to check the Git status of multiple projects

[DevOps] AI-compatible Linux server management for macOS AI-compatible Linux server management app for macOS. Control your infrastructure through AI agents with integrated MCP server, or use traditional tools. Native Mac app with multitab terminals, real-time monitoring, SSH tunneling, and system administration.

[Other] Track incidents Incident tracking and public status pages for small teams. IncidentPulse is a self-hosted, open-source web app that helps developers log incidents, assign teammates, and publish real-time status updates—all from one clean dashboard.

[Testing] RegreSQL: Regression Testing for PostgreSQL Queries

[Database] Show HN: DBOS Java – Postgres-Backed Durable Workflows Hi HN - I’m Peter, here with Harry (devhawk), and we’re building DBOS Java, an open-source Java library for durable workflows, backed by Postgres.<p><a href="https:&#x2F;&#x2F;github.com&#x2F;dbos-inc&#x2F;dbos-transact-java" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;dbos-inc&#x2F;dbos-transact-java</a><p>Essentially, DBOS helps you write long-lived, reliable code that can survive failures, restarts, and crashes without losing state or duplicating work. As your workflows run, it checkpoints each step they take in a Postgres database. When a process stops (fails, restarts, or crashes), your program can recover from those checkpoints to restore its exact state and continue from where it left off, as if nothing happened.<p>In practice, this makes it easier to build reliable systems for use cases like AI agents, payments, data synchronization, or anything that takes hours, days, or weeks to complete. Rather than bolting on ad-hoc retry logic and database checkpoints, durable workflows give you one consistent model for ensuring your programs can recover from any failure from exactly where they left off.<p>This library contains all you need to add durable workflows to your program: there&#x27;s no separate service or orchestrator or any external dependencies except Postgres. Because it&#x27;s just a library, you can incrementally add it to your projects, and it works out of the box with frameworks like Spring. And because it&#x27;s built on Postgres, it natively supports all the tooling you&#x27;re familiar with (backups, GUIs, CLI tools) and works with any Postgres provider.<p>If you want to try it out, check out the quickstart:<p><a href="https:&#x2F;&#x2F;docs.dbos.dev&#x2F;quickstart?language=java" rel="nofollow">https:&#x2F;&#x2F;docs.dbos.dev&#x2F;quickstart?language=java</a><p>We&#x27;d love to hear what you think! We’ll be in the comments for the rest of the day to answer any questions.

[Other] Show HN: Agent-to-code JIT compiler for Z3-theorem-proving agents

[IDE/Editor] Cursor, but open-source and not spying on you. CortexIDE is an open source Cursor alternative. Full privacy. Fully-featured.

[Build/Deploy] Deploy Static Sites in Seconds PinMe is a lightweight CLI tool for deploying static sites to decentralized storage. Permanent, simple, and fast. Perfect for developers who want to publish instantly and keep their content forever.

[API/SDK] Customize powerful AI agents in seconds. Prompt Lyfe helps you customize and build AI agents without writing code. Define your agent’s role, experience, and task, and Prompt Lyfe generates a structured developer prompt ready for ChatGPT, Claude, and more. No prompt engineering skills required. Built by a Data Scientist specializing in AI, it also includes a unique traceability feature that explains why each prompt will be effective, helping users understand the logic behind every AI instruction.

[Other] Show HN: I made an open-source Rust program for memory-efficient genomics My cofounder and I run a startup in oncology, where we handle cancer genomics data. It occurred to me that, thanks to a recent complexity theory result, there&#x27;s a clever way to run bioinformatics algorithms using far less RAM. I built this Rust engine for running whole-genome workloads in under 100MB of RAM. Runtime is a little longer as a result - O(TlogT) instead of O(T). But it should enable whole-genome analytics on consumer-grade hardware.

[CLI Tool] Show HN: ChatExport Structurer – parse ChatGPT/Claude exports into queryable SQL I wanted to query my own chat history but the JSON exports were a mess to work with. Built a small parser that turns them into clean SQL databases. Parsed 70k+ messages across multiple models. Useful for analyzing chat history, building a personal knowledge base, or archiving conversations. Simple CLI, open source.

[Other] Run Windows Subsystem For Android on your Windows 10 and Windows 11 PC using prebuilt binaries with Google Play Store (MindTheGapps) and/or Magisk or KernelSU (root solutions) built in.

[Testing] Show HN: Tokenflood – simulate arbitrary loads on instruction-tuned LLMs Hi everyone, I just released an open source load testing tool for LLMs:<p><a href="https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood</a><p>=== <i>What is it and what problems does it solve?</i> ===<p>Tokenflood is a load testing tool for instruction-tuned LLMs hat can simulate arbitrary LLM loads in terms of prompt, prefix, and output lengths and requests per second. Instead of first collecting prompt data for different load types, you can configure the desired parameters for your load test and you are good to go. It also let&#x27;s you assess the latency effects of potential prompt parameter changes before spending the time and effort to implement them.<p>I believe it&#x27;s really useful for developing latency sensitive LLM applications and * load testing self-hosted LLM model setups * Assessing the latency benefit of changes to prompt parameters before implementing those changes * Assessing latency and intraday variation of latency on hosted LLM services before sending your traffic there<p>=== <i>Why did I built it?</i> ===<p>Over the course of the past year, part of my work has been helping my clients to meet their latency, throughput and cost targets for LLMs (PTUs, anyone? ). That process involved making numerous choices about cloud providers, hardware, inference software, models, configurations and prompt changes. During that time I found myself doing similar tests over and over with a collection of adhoc scripts. I finally had some time on my hands and wanted to properly put it together in one tool.<p>=== <i>What am I looking for?</i> ===<p>I am sharing this for three reasons: Hoping this can make other&#x27;s work for latency-sensitive LLM applications simpler, learning and improving from feedback, and finding new projects to work on.<p>So please check it out on github (<a href="https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood</a>), comment, and reach out at thomas@werkmeister.me or on linkedin(<a href="https:&#x2F;&#x2F;www.linkedin.com&#x2F;in&#x2F;twerkmeister&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.linkedin.com&#x2F;in&#x2F;twerkmeister&#x2F;</a>) for professional inquiries.<p>=== Pics ===<p>image of cli interface: <a href="https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood&#x2F;blob&#x2F;main&#x2F;images&#x2F;cli.png?raw=true" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood&#x2F;blob&#x2F;main&#x2F;images&#x2F;...</a><p>result image: <a href="https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood&#x2F;blob&#x2F;main&#x2F;images&#x2F;self-hosted_shorter_output_latency_percentiles.png?raw=true" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;twerkmeister&#x2F;tokenflood&#x2F;blob&#x2F;main&#x2F;images&#x2F;...</a>

[API/SDK] Show HN: DeltaGlider – Store 4TB of build artifacts in 5GB DeltaGlider is a CLI&#x2F;SDK similar to `aws s3` or `boto3`.<p>UPLOAD: It stores the first file in a S3 path as a full-size (reference), but saves next uploaded archives as deltas (tiny binary diffs) with respect to the reference.<p>DOWNLOAD: it reconstructs the original file on the fly, bit-perfect and verified with SHA256.<p>Why Xdelta3? It&#x27;s a compression-aware and block-level binary diff algorithm. Perfect for representing differences between archives, where small changes shift bytes but most content stays the same. It can efficiently delta compress ZIP&#x2F;JAR&#x2F;TAR archives up to 99.9% between versions, provided the difference in compressed content is overall small.<p>Killer use cases Software versioning, periodic db. backups, JAR, ZIP, TGZ.<p>The impact for us was &quot;2 orders of magnitude&quot; storage price reduction. I hope you can benefit from it too!<p>License: GPLv3<p>Feedback and contributions are super welcome!

[Database] Show HN: YaraDB – Lightweight open-source document database built with FastAPI

[Other] Project command center Open your entire project stack in one click

[CLI Tool] Your AI Git sidekick that executes commands and fixes errors Stop copy pasting Git commands from ChatGPT. SnapCommit sits in your terminal and executes Git commands for you. Just say what you want in plain English. It runs the command. If it fails, it auto-fixes. Merge conflicts? AI resolves them. • Natural language Git commands • AI commit messages • Auto-fixes errors • Resolves merge conflicts • GitHub integration (PRs, CI, issues) • Works in ANY terminal/IDE For developers who hate Googling Git commands. $9.99/month Same price as Copilot, but for Git.

[Other] Sync AI coding configs across Claude, gemini,Cursor & Codex Edit once, sync everywhere. Vibe Manager auto-syncs MCP servers, rules, and commands across Claude Code, Cursor, Codex CLI, and Gemini CLI. No more juggling JSON vs TOML formats. Local-first, one-time purchase, lifetime access.

[Other] Be a Backend Developer with Next.js & Relational Databases This course will teach you how to build scalable, server-side applications using Next.js and PostgreSQL, with a focus on SQL, APIs, and backend logic, a step in preparing you for a full-stack role. Programming and coding program that can be taken before or after the React frontend mini bootcamp.