Alternatives
Products that do what AirymaxAgentOS does
200K++ context & 10M memory，1000h tasks at 99.10% accuracy
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The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol. Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day. A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship…
Mar 2026 · georgelarson.me
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
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Powers faster, efficient reasoning for long-running agents
Jun 2026 · developer.nvidia.com
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
Sep 2025 · github.com
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
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Zero-config hosting to launch specialized AI teams instantly
Feb 2026 · yourclaw.cloud
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Hey HN! We're Lucas and Soheil, the founders of Praxos (https://praxos.ai). Praxos is a context manager for AI Agents, providing everything you need to build stateful agents that don't break in production. Praxos can parse any data source, from unstructured PDFs and API streams to conversational messages, to structured databases, and transform them into a single Knowledge Graph. Everything in this graph is semantically typed and its relationships are made explicit, turning data into a clean, queryable universe of understanding that AI can use without making mistakes. Whether you…
2025
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Hi HN, We're the engineering team at Peakflo (B2B fintech). We built 20x internally because we kept copy-pasting Linear tickets into Claude, manually setting up branches, and babysitting agent output across terminals. Eventually we just built the infrastructure to connect task systems to agents directly — and decided to open source it. 20x is an open-source desktop app (macOS only — Linux and Windows on the roadmap) that orchestrates AI coding agents against your existing task systems. In practice: a Linear ticket gets pulled in → the triage agent assigns Claude Code + relevant skills → a…
Feb 2026 · github.com
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Agentium brings models, memory, tools into one TS runtime.
May 2026 · agentium.in
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A self-hosted ReAct agent with 12 tools and real memory
Jul 2026 · phinn.github.io
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We’ve published a set of open-source reference implementations on how to build production-grade Agentic AI applications on AWS. What’s in the repo: • Agentic RAG, memory, and planning workflows with LangGraph & CrewAI • Strands-based flows with observability using OTEL & Arize • Evaluation with LLM-as-judge and cost/performance regressions • Built with Bedrock, S3, Step Functions, and more GitHub: https://github.com/aws-samples/sample-agentic-frameworks-on-... Would love your thoughts — feedback, issues, and stars welcome!
2025 · github.com
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I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…
Jan 2026 · fabceolin.github.io
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