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• Show HN: Tamper evident audit logs for LangGraph/CrewAI agents — I have running into the same problems recently instrumenting my LangChain and CrewAI agent pipelines. If something goes wrong with a tool call, there was no way to way to prove what the agent did, in what order, and whether the logs have been modified. Observability platforms like LangSmith and Langfuse are great at optimizing for agent behavior, tokens and costs but they do not produce legally defensible and auditable artifacts. That's the reason why I decided to build RootSign, an SDK that instruments your CrewAI and LangGraph agents and produces cryptograhic audit logs for CrewAI and LangGraph agents. RootSign adds a cryptographic hash chain to every tool call. If any record is modified after the fact, "rootsign verify" detects it.<p>What it does: - SHA-256 hash chain across every Action record in a session - Human-in-the-loop checkpoints with Approval records for certain agent actions - PII redacted before hashing (StandardPIIConfig out of the box) - Works with LangGraph and CrewAI — AutoGen coming soon - Local first (Postgres + Timescale) — no cloud dependency<p>What it doesn't do (yet): compliance dashboard, cloud backend, policy engine, all on the roadmap.<p>Please try it out on the Github repo, contributions and feedback are always welcome.

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• Show HN: Klaus – OpenClaw on a VM, batteries included — We are Bailey and Robbie and we are working on Klaus (<a href="https://klausai.com/" rel="nofollow">https://klausai.com/</a>): hosted OpenClaw that is secure and powerful out of the box.<p>Running OpenClaw requires setting up a cloud VM or local container (a pain) or giving OpenClaw root access to your machine (insecure). Many basic integrations (eg Slack, Google Workspace) require you to create your own OAuth app.<p>We make running OpenClaw simple by giving each user their own EC2 instance, preconfigured with keys for OpenRouter, AgentMail, and Orthogonal. And we have OAuth apps to make it easy to integrate with Slack and Google Workspace.<p>We are both HN readers (Bailey has been on here for ~10 years) and we know OpenClaw has serious security concerns. We do a lot to make our users’ instances more secure: we run on a private subnet, automatically update the OpenClaw version our users run, and because you’re on our VM by default the only keys you leak if you get hacked belong to us. Connecting your email is still a risk. The best defense I know of is Opus 4.6 for resilience to prompt injection. If you have a better solution, we’d love to hear it!<p>We learned a lot about infrastructure management in the past month. Kimi K2.5 and Mimimax M2.5 are extremely good at hallucinating new ways to break openclaw.json and otherwise wreaking havoc on an EC2 instance. The week after our launch we spent 20+ hours fixing broken machines by hand.<p>We wrote a ton of best practices on using OpenClaw on AWS Linux into our users’ AGENTS.md, got really good at un-bricking EC2 machines over SSM, added a command-and-control server to every instance to facilitate hotfixes and migrations, and set up a Klaus instance to answer FAQs on discord.<p>In addition to all of this, we built ClawBert, our AI SRE for hotfixing OpenClaw instances automatically: <a href="https://www.youtube.com/watch?v=v65F6VBXqKY" rel="nofollow">https://www.youtube.com/watch?v=v65F6VBXqKY</a>. Clawbert is a Claude Code instance that runs whenever a health check fails or the user triggers it in the UI. It can read that user’s entries in our database and execute commands on the user’s instance. We expose a log of Clawbert’s runs to the user.<p>We know that setting up OpenClaw is easy for most HN readers, but I promise it is not for most people. Klaus has a long way to go, but it’s still very rewarding to see people who’ve never used Claude Code get their first taste of AI agents.<p>We charge $19/m for a t4g.small, $49/m for a t4g.medium, and $200/m for a t4g.xlarge and priority support. You get $15 in tokens and $20 in Orthogonal credits one-time.<p>We want to know what you are building on OpenClaw so we can make sure we support it. We are already working with companies like Orthogonal and Openrouter that are building things to make agents more useful, and we’re sure there are more tools out there we don’t know about. If you’ve built something agents want, please let us know. Comments welcome!

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• Show HN: Resolve AI – Your AI Production Engineer — Hello. I am Madhu, a Software Engineer at Resolve AI. We launched our product today and we are thrilled to share it with you all and get feedback: <a href="https://resolve.ai/" rel="nofollow">https://resolve.ai/</a><p>Our team at Resolve AI comes with a wealth of experience in this space. I was an early contributor to Kubernetes at Google where I worked on Kubernetes and associated technologies for ~6 years. More recently, I was the tech lead for the Kubernetes-based compute platform at Robinhood where my teams were in a number of SEVs per year, not necessarily caused by the platform itself but still supported (pretty much the story of life for Infrastructure Engineers everywhere). Our co-founders, Spiros Xanthos and Mayank Agarwal co-created OpenTelemetry at their previous startup Omnition (acquired by Splunk). More recently, Spiros was the GM and Senior Vice President of Splunk Observability and Mayank was the lead architect for all of Splunk's observability product lines. We have all lived the problems we are trying to solve.<p>Resolve is AI for production engineers. Production systems are dynamic and complex. Addressing common production engineering concerns like incident troubleshooting, cloud operations, security, compliance and cost involves painfully piecing together information from many teams (service on-call rotations, Platform, SRE, etc) and multiple (routinely 10+) different tools (observability, CI/CD, infrastructure, paging, chat, etc). These tools were not designed to work together, pushing the complexity on humans.<p>Resolve AI is tackling this challenge by building an AI Production Engineer with the goal of automating the majority of tasks across incident management, cloud operations, security engineering, compliance, and cost management. As the first step in our ambitious journey, we are automating incident troubleshooting as it is the most direct way to prevent outages and improve reliability while relieving engineers from the most stressful part of their job. Our goal is to automate the resolution of 80%+ of alerts and incidents without human involvement.<p>Resolve AI automatically maps and keeps up-to-date a complete knowledge graph of any production environment, without needing any upfront training or user input. It builds knowledge of which tools and signals are relevant for any situation. It comes pre-built with models for various tool categories such as metrics, logs, traces, alerts, seamlessly connecting with category- and vendor-specific products like Prometheus, Splunk, GCP, AWS, Azure and others. These models automatically and continuously adapt to each customer's environment.<p>With the state-of-the-art reasoning engine that’s composed of multiple agents, Resolve AI is able to investigate novel incidents, accurately determine causality, learn and adapt as it encounters new situations and perform various complex actions.<p>Generative AI is inherently probabilistic and not always 100% accurate. Without full context, AI models may hallucinate, potentially misleading users. For an AI that takes actions, building user trust is paramount; it must present clear evidence for any decision or action. We address these challenges by building an interface that supports claims with evidence, present findings with context and allow humans to collaborate with the system so that they can guide the system when needed.<p>Our video demo is on the website. Please take a look. We really appreciate your feedback. We are also happy to hop on a call to show a demo live if you are interested (madhu@resolve.ai).

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