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  15. 15IB

    Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…

    Jan 2026 · github.com

  16. 16IB

    Inspired by the success of OpenClaw, I built Comrade, which is an open-source AI workspace for teams focused on security. It provides a premium interface for AI-powered workflows, built with transparency, extensibility, and local-first principles. Check it out here: https://github.com/LaurentiuGabriel/comrade

    Apr 2026

  17. 17

    Scans AI agent skills for malicious code

    10d ago · github.com

  18. 18ET

    Hey Hacker News, For the last 2 months, I've been working on a testing agent to free developers from the endless maintenance of end-to-end tests. You just push up a PR, and our agent analyzes the code changes and automatically visits the preview to test things out like a real human! We also support describing tests in English (or even in the PR description), and we'll go through your site whenever you want via a GitHub action to test and make sure various core flows continue to work as expected. We are looking for early testers and are giving out a generous free tier! Just sign up on the…

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  19. 19AC

    Hey HN! I’m Julien, the founder of Code Inspector, a platform that helps developers and managers produce better code and reduce technical debt. We would love to get some feedback from the Hacker News community. Our platform inspects code, looks for defects (security, vulnerability, design, performance, lack of documentation), automates code reviews and reports on team activity. You can customize violation alerts to reduce false positives. We currently support GitHub, Bitbucket and Gitlab. I’d love to hear your thoughts on what you would expect from such a platform (what you like, dislike)…

    2021

  20. 20AO

    Hey HN! I've been wanting to use something like OpenClaw for a while but couldn't get myself to give it access to anything important due to all the risks involved. Prompt injection is still a problem (even though some people seem to ignore it) and so are hallucinations and mishaps that cause agents to do things like delete production data [1]. Even harnesses like Claude Code and Codex are subject to this, particularly since we're getting progressively looser about how we run them e.g. Conductor is really popular and runs agents without any sandboxing. That means we're in a bit of an…

    Apr 2026 · agentport.sh

  21. 21AT

    Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.

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    Hey HN! I'm one of the cofounders of Sourcebot, an open source alternative to Sourcegraph. Sourcebot lets you index thousands of repos across multiple platforms (GitHub, GitLab, Bitbucket), and gives you a powerful interface to search across them. You can learn more in our original HN launch post: https://news.ycombinator.com/item?id=41711032 We just added an AI code review agent that reviews your PRs and automatically detects issues that a human reviewer may have missed. We've been using an AI code review agent for a few weeks now, and it regularly catches issues that we…

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  23. 23FA

    Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…

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  24. 24IS

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    2025

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