🛠️ All DevTools

[Other] Show HN: Secs-man, a secrets manager you can (not) rely on This is a tool to manage encrypted local backups of secrets. The core idea is that it aims to be usable without depending on it, meaning that even if the software disappeared from the face of Earth tomorrow, your data would still be recoverable.<p>It also integrates nicely with NixOS (which is what I use, though it does not require NixOS to be used).<p>I have summed up a bit of explanation and some answers to reasonable questions in a blog post: <a href="https:&#x2F;&#x2F;baldino.dev&#x2F;blog&#x2F;secs-man&#x2F;" rel="nofollow">https:&#x2F;&#x2F;baldino.dev&#x2F;blog&#x2F;secs-man&#x2F;</a>

[Other] Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS

[Other] Show HN: Visual Workspace for Agents Based on Unix Hey HN,<p>Thijs here! I&#x27;m the founder of Prototyper and today we&#x27;re launching the first visual canvas built for agents.<p>Couple of interesting lessons from building the product that I think are worth sharing:<p>For the agents, everything is a file. In Prototyper, everything from plans, to apps, and diagrams, can be read as a file.<p>We found that a filesystem is the most natural way for an agent to navigate: it discovers new content and functionality just by traversing the tree.<p>We kept this layer deliberately thin and unopinionated, because it&#x27;s the substrate, not the experience. It&#x27;s the foundation that makes everything work on top.<p>It essentially operates as a distributed, web-based unix kernel.<p>Because of that it&#x27;s built for the agents you already use. People run all kinds of models and harnesses, often several at once.<p>With this architecture, we don&#x27;t try to lock you into one, it&#x27;s built to work with any agent that you like. That means that any agent can read from and write to your workspace.<p>It&#x27;s fast. File writes land in under a millisecond. That&#x27;s not a bogus metric, it&#x27;s what makes the whole thing feel seamless and like a real extension of your thinking. Thanks to our custom unix kernel.<p>Visual first. Every file in your workspace can be opened on the canvas. Whether you&#x27;re an engineer working on a new frontend or a PM building a product roadmap.<p>It&#x27;s a real visual workspace for the actual work, not a description of it. As said, it&#x27;s not a blank canvas with a box of primitives: the canvas represents a real unix system, which is the kind of purpose-built, opinionated experience that makes a product.<p>In essence, the substrate is generic so the things you build on it don&#x27;t have to be.<p>What&#x27;s most interesting is that by this architecture we found that we can decouple system prompt length from agent capability.<p>I&#x27;m happy to get feedback from the community and see what you all think of it :).

[Other] Show HN: ParseHawk – 100% Local Document AI with API, CLI, and Web UI I just released ParseHawk v0.1.0: Apache-2.0 licensed 100% local document AI platform that extracts JSON from PDFs, images etc. It builds on top of NuMind&#x27;s NuExtract3 but additionally enforces a provided JSON schema with constrained decoding. It works on Apple Silicon with pre-bundled vllm-metal as well as Linux + NVIDIA with vllm. Looking forward to your feedback!

[DevOps] Zero-Downtime Deployments with Docker Compose – No Kubernetes Required

[Other] GitHub shouldn't be a dependency for publishing Rust on crates.io

[Other] Show HN: Lelu – gate OpenAI agent actions on confidence and prompt injection

[Other] I rewrote PostHog's SQL parser, 70x faster, while barely looking at the code

[DevOps] Show HN: Forte – Cloud infra to get startups to production faster Forte is an opinionated cloud platform that gets developers to production faster. Developers bring their code and Forte containerizes it with autoscaling and no cold starts, securely configures auth, and provides logging insights and monitoring out of the box.<p>I used to help lead service development at AWS, and even before AI coding was widespread, our biggest bottleneck was rarely feature development. We would spend months on security prep, observability tooling, on-call optimization, and other overhead before launching new features. When I worked in startups, every team hit a surprisingly similar set of problems and spent weeks rebuilding auth, logging, monitoring, and payments.<p>Platforms like Heroku, Render, and Railway are helpful for getting a container running but don&#x27;t provide the rest of the tooling the teams need to go to production -- auth, secure defaults, and request-level logging. We built Forte to solve that entire stack of problems.<p>You can check out Forte at <a href="https:&#x2F;&#x2F;forteplatforms.com" rel="nofollow">https:&#x2F;&#x2F;forteplatforms.com</a> (it&#x27;s free to sign up and doesn&#x27;t require a payment method). We&#x27;d love to hear your questions and feedback!

[Other] RubyLLM: A Ruby framework for all major AI providers

[Other] Show HN: Nub – A Bun-like all-in-one toolkit for Node.js Colin here, creator of Nub. I’ve had the general shape of this in mind for years. Nub runs your code with stock `node`, augmented with a `--require` preload hook[0] that adds a transpiler (oxc-powered, packaged as a Node-API add-on), registers a module resolution hook[1], and injects polyfills as needed for APIs like `Worker`, `Temporal`, etc. All purely additive, your code ultimately runs using Node’s actual engine &amp; stdlib implementations.<p>[0] <a href="https:&#x2F;&#x2F;nodejs.org&#x2F;api&#x2F;cli.html#-require-module" rel="nofollow">https:&#x2F;&#x2F;nodejs.org&#x2F;api&#x2F;cli.html#-require-module</a><p>[1] <a href="https:&#x2F;&#x2F;nodejs.org&#x2F;api&#x2F;module.html#moduleregisterhooksoptions" rel="nofollow">https:&#x2F;&#x2F;nodejs.org&#x2F;api&#x2F;module.html#moduleregisterhooksoption...</a>

[DevOps] Systems optimization should be part of CI/CD

[Other] Flutter makes it easy and fast to build beautiful apps for mobile and beyond

[Other] Minimus container images are now free

[Other] Haystack: Open-Source AI Framework for Production Ready Agents, RAG

[Other] Show HN: Y – A malleable coding-agent desktop app built with Electron

Anthropic updates their terms to verify age or identity

[Testing] Show HN: RLM-based local debugger for AI agent traces We built HALO (Hierarchal Agent Loop Optimizer), an open-source tool for debugging and optimizing AI agents using their execution traces.<p>It’s a loop. Run your agent, feed the traces to HALO, get the report, apply the fixes, then re-run your agent.<p>HALO takes in OTEL compliant traces from AI agents using tracing frameworks such as Langfuse, Arize&#x2F;OpenInference, or even just plain JSONL. It uses an RLM (Recursive Language Model) to more efficiently break trace analysis into smaller subproblems in order to find recurring patterns across large amounts of data and fix systemic issues that regular LLMs might typically miss.<p>You can also optionally provide a path to where your agent code lives to give the engine more context so it can more concretely provide useful insights.<p>The repo also includes a desktop app that you can run locally without having to sign up for anything or configure anything complex.<p>Check out the readme in the repo for more in depth information on what HALO is and how you can use it to your benefit :)

Fired by Google for creating the Google workspace CLI <a href="https:&#x2F;&#x2F;xcancel.com&#x2F;JPoehnelt&#x2F;status&#x2F;2069482265953087602" rel="nofollow">https:&#x2F;&#x2F;xcancel.com&#x2F;JPoehnelt&#x2F;status&#x2F;2069482265953087602</a>

San Diego photologs from the 1970s