Greetings! I am a fresh new member to this site and group. I've been starting to work with A0 for the last week or so. It's a work related project, to ultimately build a local A0 deployment that can act as a Systems Admin essentially. With limits of course! I am also new to the world of AI, yes I know I'm late to the party. But its become clear that AI is here to stay. I'm looking to collaborate with other A0 engineers that are using local LLM's to host A0 (not paid cloud based API send all your data to a random company and hope for the best for privacy) that are working on similar types of "system admin" level use of A0 and creating guardrails. I mean I don't care if you use cloud models, I don't think that impacts the guardrails as much, maybe it does I dunno. Again I'm 2 weeks into this whole world of AI. It's information overload. But building out rules is where I would love to collab with people. Skills too. More about me below. Prior to about 2 weeks ago I knew nothing about AI, I used chatGPT once or twice for fun, then I used my employers enterprise Co-Pilot subscription we have to help me as basically a faster/better google search in my daily duties. That's it. I didn't know how anything worked. Sad I know especially not being new to tech which I've been nerding out on my whole life really, well since the internet got big anyways (I am part of the last generation to grow up as a kid without internet.) It wasn't until my mid teen's until the 90's boom happened and I was hooked. 20+ year veteran of being a Senior systems admin/architect worked for some of the biggest tech companies in silicon valley and some government work too. My employer has given me an NVIDIA DGX Spark 10 to use at home to build out a local deployment of A0, backed 100% by local LLM's. No internet access needed! I've been diving into AI to learn the fundaments and to say its overwhelming is an understatement. Having an engineering degree, I have the brain for complex tasks and puzzles so AI is just that to me. I first had to get a handle on the DGX Spark. I'm ok at Linux but no guru. I'm running the spark headless. As that's how it'll be used at work. I'm using A0 on my local laptop for testing via Docker desktop.

I keep getting this error after I upgraded to v1.5. Can you share how I might be able to troubleshoot this or is this is a bug in 1.5? I am running on a Hostinger VPS with Dokploy and Ubuntu.

I’m jumping back into A0 versus OpenClaw again. With all the new versions rolling out, I’m hoping things will work a little better this time… but so far it’s not looking great. Right now I’m just trying to get everything set up. The first step was connecting my Quo (OpenPhone) through the API. It says everything is linked and working correctly. But when I ask A0 to send me a test text, it doesn’t actually send one. Instead, it just responds with a list of terminal commands for running a test manually. No matter how many times I ask, I get the same output. At this point I’m not sure if this is a model issue or something else. I’m on the latest v1.4 and using the OpenRouter Qwen 3 Super Free model on my Hostinger VPS. Any advise?

I’m really enjoying these observability and memory plugins. Paired with the model switching system, they let me choose the right model for each job and monitor performance along the way. Thank you to the developers for all the effort you’ve put in. At a time when AI and agents are moving so quickly, your work in the Agent-Zero community helps people avoid depending on big tech and closed-source tools. I also want to give special thanks to everyone who contributed to safety and made the experience more convenient through thoughtful design.

I encourage plugin users to engage with the star system linked to the GitHub repository of the plugin developer. By starring the projects you use, you stay updated with the actual code of the plugins. This also helps all Agent Zero users identify the most frequently used plugins, which can contribute to reducing negative experiences. Some plugins are still in progress and may have bugs. Creating issues in the GitHub repository can assist developers and keep users informed about plugin performance.