Alternatives
Products that do what Herd – A Go sidecar to stop stateful processes Puppeteer/LLMs from OOM does
Hey HN. I'm an engineering student at Waterloo building stateful AI agents, and I kept hitting the same wall: whenever my Python scripts crashed or dropped a connection, the underlying Puppeteer or Ollama processes would just sit there orphaned, eating RAM until the node OOM-killed itself. Standard load balancers break sticky sessions, and passive HTTP timeouts are too slow for cleanup. I couldn't find a good local process pool that actually cleaned up dead stateful sessions reliably, so I built Herd in Go. It uses a persistent stream (gRPC/Unix sockets) strictly as a dead-man's switch.…
- 1LA
I built LocalGPT over 4 nights as a Rust reimagining of the OpenClaw assistant pattern (markdown-based persistent memory, autonomous heartbeat tasks, skills system). It compiles to a single ~27MB binary — no Node.js, Docker, or Python required. Key features: - Persistent memory via markdown files (MEMORY, HEARTBEAT, SOUL markdown files) — compatible with OpenClaw's format - Full-text search (SQLite FTS5) + semantic search (local embeddings, no API key needed) - Autonomous heartbeat runner that checks tasks on a configurable interval - CLI + web interface + desktop GUI - Multi-provider:…
Feb 2026 · github.com
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- 3SV
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
- 4IR
I do fullstack dev for work and side projects and recently moved everything to a couple VPSs on hetzner. Great setup, low cost, but one thing kept bugging me, how do I know if something is down without manually sshing in all the time? I tried the grafana + prometheus stack but the configuration time and seeing it use more resources than my actual apps was rough. Tried some smaller solutions too but nothing felt right. So I said screw it and built exactly what I wanted. tori is a single go binary that runs on your server, reads host metrics from /proc and /sys, monitors containers…
Feb 2026 · github.com
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- 6OA
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
- 7GA
Hey folks, wanted to show this off and get feedback. Still early/experimental but there are quite a few concepts I'm excited about here. This project came about while writing a program in Go and loving its approach to concurrency. Being a long-time Rubyist I immediately started to think about what similar concepts might look like in Ruby. I set out with two main design constraints: 1. Lightweight: I didn't want routines to be backed by fibers or threads. Having been involved some in the async project (https://github.com/socketry/async), I had some experience using…
2023 · github.com
- 8HA
Hi HN — I just open-sourced Hibana and hibana-agent. Hibana is an Affine MPST runtime for Rust: - global choreography -> compile-time projection -> role-local execution - core is no_std / no_alloc-oriented - deterministic route/offer/recv/decode model Repo: https://github.com/hibanaworks/hibana Demo (AI control with session-typed branching): https://github.com/hibanaworks/hibana-agent
Feb 2026 · hibanaworks.dev
- 9AS
Doors: Server-driven UI framework + runtime for building stateful, reactive web applications in Go. Some highlights: * Front-end framework capabilities in server-side Go. Reactive state primitives, dynamic routing, composable components. * No public API layer. No endpoint design needed, private temporal transport is handled under the hood. * Unified control flow. No context switch between back-end/front-end. * Integrated web stack. Bundle assets, build scripts, serve private files, automate CSP, and ship in one binary. How it works: Go server is UI runtime: web application runs on a…
Apr 2026 · github.com
- 10
Love OpenClaw? Now ship it to production. Built in Rust.
Feb 2026
- 11CS
I got tired of AI agents forgetting what they were doing the moment their context window filled. The current industry solution is to write massively bloated agent harnesses full of defensive spaghetti just to stop models from drifting. The problem is treating chat history as project state. A conversation is not a ledger. Castra is a compiled Go binary that strips orchestration rights from the LLM. State lives in an encrypted, local SQLite database (castra.db). The LLM is just a stateless executor — it reads the DB, executes a highly constrained task, and the result is written back subject to…
Apr 2026 · github.com
- 12OI
Hey HN, I've been using OpenClaw for a few months as my local LLM gateway. It was genuinely fun — the convenience of routing multiple models through a single endpoint is hard to beat. But along the way, I stumbled upon a few surprises that made me uncomfortable: - Config files scattered in unexpected places (~/.openclaw, ~/.clawdbot, and more) - Background processes that respawn after termination - Logs that quietly accumulate without rotation - Cached data persisting long after I thought I'd removed it None of this is necessarily malicious, but when I decided to move on, I wanted…
Feb 2026 · github.com
- 13
Gomaa — Autonomous Agent Memory OS. Persistent memory system for AI agents with Obsidian vault integration, hybrid RRF search, knowledge graphs, security gates, and MCP server. - M4F-S/gomaa
14d ago · github.com
- 14GA
What it does: A Postman/Insomnia-like TUI for building, sending, and organizing HTTP/GraphQL/gRPC/WebSocket requests. Supports saved collections stored as YAML/JSON files, environment variables, auth presets, response diffing, and request history. Why it's needed: This is the single largest gap in the Go TUI ecosystem. The abandoned wuzz (10.5k stars) proved massive demand for terminal HTTP inspection, but it's been dead for years. Posting (Python, ~6k stars) and ATAC (Rust, ~2k stars) are thriving alternatives in other languages. The Go options — gostman and go-gurl…
Feb 2026 · github.com
- 15AD
I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
- 16TO
I built DevClaw, an OpenClaw plugin that turns each Telegram group into an isolated, autonomous dev team: planner/orchestrator, DEVs, and QA all running on their own. I use it for all my development now. Issues on GitLab/GitHub are the single source of truth, and three things compound to save around 70% on tokens: model tiering (Haiku for typos, Opus for architecture), session reuse across tasks, and token-free scheduling that burns zero LLM calls for orchestration. Please try it and give some feedback. Also keen to hear from anyone running autonomous coding agents, especially what…
Feb 2026 · github.com
- 17LL
Some time ago I built a simple app to run swarms of coding agents — I call it fleet (https://news.ycombinator.com/item?id=48256389). It's based on centralized beads with a Python orchestrator and can run any coder (Claude, agy, Codex). Recently I added a UI to manage the whole agent lifecycle: adding new tasks, monitoring running ones, and a chat interface built on MCP with a centralized SQLite DB. From the UI I can spawn agents to run in any directory, define dependencies on other tasks, and specify which coder/model should do the job. Today I can run 10–15 agents…
Jun 2026
- 18IB
Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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- 20MY
LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!
2023 · github.com
- 21AC
Built an AI code reviewer using Letta (Python) that I can call natively from Rust applications. The interesting part: real-time streaming works perfectly across the language boundary with zero hassle using RunAgent. The agent runs in Python with persistent memory, leverages the best in house agentic memory management with Letta (Pythonic AI agent framework), and my rust code just uses it (kinda) natively, though Letta has no Rust bindings. And, streaming works like magic. No FFI, no complex bridges - just native async/streaming that feels like calling any Rust librar, but without…
2025 · medium.com
- 22IB
Hey HN, I'm Daniel, solo dev from Germany. I built ClawHosters (https://clawhosters.com), a managed hosting platform for OpenClaw, the open-source AI agent framework. Quick timeline: domain registered February 5th. First paying customer six days later. I probably should have spent more time on it, but it works. If you haven't seen OpenClaw, it lets you run a personal AI assistant that connects to Telegram, Discord, Slack, and WhatsApp. Self-hosting it is absolutely possible, but it's a pain. You're dealing with Docker setup, SSL certs, port forwarding, security hardening, keeping…
Feb 2026 · clawhosters.com
- 23WB
Over the past few months, as we scaled our internal AI Agents, we hit a dead end: Running LLM-generated arbitrary code in Docker is basically running naked on security due to container escape risks. But using full traditional VMs takes minutes to boot and eats too much memory to support high-density concurrency. We loved the developer experience of SaaS sandboxes on the market, but they are closed-source, expensive, and have too high a barrier to entry for self-hosting. So, our team decided to build our own. After months of grinding, using RustVMM and KVM, we built a blazing-fast,…
Apr 2026 · github.com
- 24CR
Clawbernetes turns OpenClaw into an AI-native infrastructure manager. Instead of YAML, Helm charts, and kubectl — you have a conversation. "Deploy Llama 70B on the node with the most VRAM" → agent selects the best node, pulls the image, starts the container with GPU passthrough, sets up health monitoring. "Why is inference slow?" → checks GPU temps, VRAM, CPU load. "GPU 0 at 89°C — thermal throttling. Want me to reduce batch size?" 23 crates, 74K lines of Rust, 1,866 tests, zero unsafe in core. Supports CUDA, Metal, ROCm, Vulkan, and CPU SIMD. Components: - clawnode: node agent with 80+…
Feb 2026 · github.com
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