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    Recently I've been running more and more agents in parallel however I noticed that they have no task context of what the other agents are doing even when a lot of work is interconnected It's like taking Slack away from a team. Agents duplicate work, make conflicting changes, and step on each others' toes simply because they can't talk to each other. Concord is an MCP + CLI that lets coding agents claim work, see what other agents are doing, and message each other live.

    9d ago · github.com

  20. 20RA

    I built a local-first UI that adds two reasoning architectures on top of small models like Qwen, Llama and Mistral: a sequential Thinking Pipeline (Plan → Execute → Critique) and a parallel Agent Council where multiple expert models debate in parallel and a Judge synthesizes the best answer. No API keys, zero .env setup — just pip install multimind. Benchmark on GSM8K shows measurable accuracy gains vs. single-model inference.

    Mar 2026 · github.com

  21. 21PS

    I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.

    27d ago · pacslate.com

  22. 22CA

    TL;DR: we built a framework-agnostic agent runtime that uses gVisor for isolation and runs on k8s. It’s open-source under AGPLv3 Recently we’ve been working on a customer support “AI assistant” - essentially an interactive knowledge base/L1 support but with an option to touch resources that belong to a customer it’s talking to. We found existing tools to be lacking in these aspects: 1. Fully intercepted i/o. We wanted to trace out LLM calls as well as any other networking calls attempted by the harness so that guardrails and audit trails apply to all current and future systems…

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  23. 23

    Stop AI agents from doing things they shouldn't.

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  24. 24OS

    I built an open source desktop AI assistant after getting frustrated with how brittle most tools feel once questions go beyond basic Q and A. The goal was to explore whether an assistant could reliably handle interview style interactions such as system design discussions, multi step coding problems, and deeper follow up questioning without hiding behavior behind a closed SaaS. The assistant supports both cloud and local LLMs, uses a bring your own API key model, and is intentionally opinionated so behavior stays predictable under pressure. Most of the work went into managing context, follow…

    Feb 2026 · github.com

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