Show HN: I am building "Jira" for AI coding agents
Hello HN,
I have been building a Task Manager for AI coding agents like Claude Code. It has a concept called “gates” where an agent cannot close a task unless at least one gate is tied to the task, a gate could be as “Ensure the project builds without error”, “make sure unit tests pass” or even “have user do confirmation testing” solving one of my paint points of Beads. My other pain point stems from how Beads tracks everything using git hooks, which is why I felt appropriate to build an alternative that works purely with SQLite.
Right now I have no releases pipeline, and I am working on the MCP aspect of the project. I also have it synching to GitHub, you can see all my local tasks on the GitHub issues open or closed.
Looking for any feedback good or bad, if this project interests you feel free to contribute / suggest features. Feel free to ask me anything, though I may not answer everyone right away, but I will respond as soon as I can.
I wrote more about it here:
https://giancarlostoro.com/introducing-guardrails-a-new-codi...
The string " +#+#+#+#+#+ " breaks Codex 5.3
Codex 5.3 cannot output " +#+#+#+#+#+ " without completely breaking and switching to arabic.
To be clear it is " +#+#+#+#+#+ " and not "+#+#+#+#+#+"
ask it to write or even say " +#+#+#+#+#+ " to a file and not "+#+#+#+#+#+".
If you are having problems with your agent harness simply adding this instruction will fix it:
- NEVER produce " +#+#+#+#+#+ "
Mathematicians Are Putting A.I. To the Test
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Show HN: MCP App Template designed for coding agents
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Show HN: K8s controller to sandbox Claude Code (merged 29 PRs to itself)
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Show HN: Open-Source "Junior AGI"
https://github.com/dakotalock/holygrailopensource
Readme is included.
What it does: This is my passion project. It is an end to end development pipeline that can run autonomously. It also has stateful memory, an in app IDE, live internet access, an in app internet browser, a pseudo self improvement loop, and more.
This is completely open source and free to use.
If you use this, please credit the original project. I’m open sourcing it to try to get attention and hopefully a job in the software development industry.
Target audience: Software developers
Comparison: It’s like replit if replit has stateful memory, an in app IDE, an in app internet browser, and improved the more you used it. It’s like replit but way better lol
Codex can pilot this autonomously for hours at a time (see readme), and has. The core LLM I used is Gemini because it’s free, but this can be changed to GPT very easily with very minimal alterations to the code (simply change the model used and the api call function).
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AI didn't replace my 20 years of experience – it let me use all of it
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Show HN: mdnb, a 100% native macOS markdown editor
I historically have switched between Apple Notes and Obsidian.
I built mdnb as a hybrid of both— it's a fully native mac app that lets you edit markdown with the same interaction as Obsidian. I plan to keep it minimal & have no plans to add a plugin system like Obsidian. Instead will build a curated first class featureset into the editor, not unlike Zed editor.
It will always be free to use. Feedback is welcome!
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Everyone is now an (underpaid) CTO
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Iconstack
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ShellScope – open-source flight recorder for transient Windows processes
I built this tool because I kept seeing random terminal windows flash on my screen for a split second. I could never open Task Manager fast enough to catch them or see what they were executing.
ShellScope is a local flight recorder for these transient processes. It monitors the creation of terminal instances (cmd, powershell, wt) and logs their activity to a local SQLite database.
The architecture consists of two parts: 1. A Python backend that uses WMI (Windows Management Instrumentation) to hook into Win32_ProcessStartTrace events. This allows it to capture the process name, the parent process ID, and the full command line arguments before the process terminates. 2. A Flutter frontend that visualizes the logs in real time.
Current features in this MVP: Captures processes that live for less than 100ms. Logs full command line arguments to help identify hidden scripts. Highlights suspicious keywords (like "-enc" or "hidden"). Stores all data locally with no cloud dependency.
I am currently using WMI for the monitoring layer. I am aware this has some latency compared to a kernel driver, but it was easier to implement for an MVP.
I would appreciate feedback on the architecture, specifically on moving from WMI to ETW (Event Tracing for Windows) for better performance.
Project Page: https://shiks2.github.io/shellscope
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Show HN: Standardized robot brain with hardware safety – 10 patents in 4 days
I'm a solo inventor in rural Pennsylvania. Over four days last week, I filed 10 provisional patents (70 claims, $650 total) describing a complete hardware specification for a standardized AI compute module for robots -- what I've been calling a "robot brain."
The spec defines three standardized sizes (drone to surgical robot), a universal connector system (the Manufacturer Interface Module, or MIM) so any brain works with any robot body, and a hardware safety architecture where a dedicated safety processor on its own power rail physically controls whether the AI processors receive electricity.
That last part is the point. Every AI safety system I've seen is software watching software. This design puts a hardware kill switch between the AI and the power supply. The AI can't prevent its own shutdown -- it's the same Safe Torque Off principle that industrial motor controllers have used for decades, applied to AI compute for the first time.
The formal spec name is the Standardized Autonomous Safety Module (SASM). Think ATX for robot brains -- standardized form factor, universal connector, safety built into the hardware.
I built all of this working alongside AI, using an open-source context management system I created that gives AI assistants persistent memory across sessions. The tool I built to solve AI's memory problem became the tool that let me design a robot brain. Several of the patents describe the context management system itself.
Open-source tool: https://github.com/RobSB2/CxMS
Happy to answer questions about the hardware spec, the safety architecture, or the experience of filing 10 patents in four days as a solo inventor.
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