Alternatives
Products that do what SolidState HQ does
A deterministic runtime for safe, controllable AI agents
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AgentState to solve a problem I kept running into: managing state for multi-agent AI systems is surprisingly hard. When you have multiple AI agents that need to coordinate, persist their state, and query each other's status, you typically end up with a mess of Redis/Postgres setups, custom queuing, and manual synchronization code. The whole thing is ~3MB, written in Rust for performance and safety, runs in Docker, and handles 1000+ ops/sec. I've been running it in production for AI workflows and it's been rock solid.
2025 · github.com
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May 2026 · tilde.run
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Agentic problem solving in its current state is very brittle. I fell in love with it, but it creates as many problems as it solves. I'm Ben Cochran, I spent 20+ years in the trenches with full-stack Engineering, DevOps, high performance computing & ML with stints at NVIDIA, AMD and various other organizations most recently as a Distinguished Engineer. For agents to work reliably you either need massive parameter counts or massive context windows to keep the solution spaces workable. Most people are brute forcing reliability with bigger models and longer prompts. What if I made the problem…
May 2026 · github.com
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We recently open-sourced Hive after using it internally to support real production workflows tied to contracts totaling over $500k. Instead of manually wiring workflows or building brittle automations, Hive is designed to let developers define a goal in natural language and generate an initial agent that can execute real tasks. Today, Hive supports goal-driven agent generation, multi-agent coordination, and production-oriented execution with observability and guardrails. We are actively building toward a system that can capture failure context, evolve agent logic, and continuously improve…
Feb 2026 · github.com
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Open-source AI agent runtime — build Agents in plain English
Jul 2026 · syntheticbrew.ai
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Hey HN, I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans. It boils down to two main goals: 1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating state changes or getting lost in long procedural scripts. I wanted a library that enforces that "Input -> Transform -> Output" flow by default. 2. Easing the transition to Python: For many…
Feb 2026
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Your agents. Your servers. Your keys. Your model.
May 2026 · platos.dev
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Hi HN, Over Thanksgiving weekend I wanted to build an AI agent. As a design exercise, I wrote it as a set of React components. The component model made it easier to reason about the moving parts, composability was straightforward (e.g., reusing agents/tools), and hooks/state felt like a reasonable way to model behavior that changes over time. As I kept experimenting, I realized I was more interested in the framework (and it was a good excuse to explore React’s internals) than in the agent I originally planned, so I built this project instead. In this framework: - Agents are React…
Dec 2025 · github.com
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Agentium brings models, memory, tools into one TS runtime.
May 2026 · agentium.in
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Hi HN, Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents. At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full privacy and no external data sharing. What makes it different • Fast & lightweight — Agents instantiate in ~3μs and use ~6.6 KiB of memory on average (tested on M4 MacBook Pro). • Runtime architecture — Async, stateless, horizontally scalable runtime built on FastAPI. • Integrated…
Oct 2025 · agno.link
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Love OpenClaw? Now ship it to production. Built in Rust.
Feb 2026
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Hi HN! Today me and qianli_cs want to share a new open-source project we've been working on called Durable Swarm. It's a drop-in replacement for OpenAI’s Swarm that augments it with durable execution to make your agentic workflows resilient to failures, so that if they are interrupted or restarted, they automatically resume from their last completed steps. https://github.com/dbos-inc/durable-swarm We believe that as multi-agent workflows become more common, longer-running, and more interactive, it's important to make them reliable. If an agent spends hours waiting for…
2024 · github.com
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Jul 2026 · github.com
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