Alternatives
Products that do what ClawTrace: Orchestrate 1000+ AI Agents does
Sub-Millisecond Telemetry – Command Center for AI Swarms
- 1
- 2CO
We recently started to use agents to update some documentation across our codebase on a weekly basis, and everything quickly turned into cron jobs, logs, and terminal output. it worked, but was hard to tell what agents were doing, why something failed, or whether a workflow was actually progressing. We thought it would be more interesting to treat agents as long-lived workers with state and responsibilities and explicit handoffs. Something you can actually see and reason about, instead of just tailing logs. So we built Clawe, a small coordination layer on top of OpenClaw that lets agent…
Feb 2026 · github.com
- 32C
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
- 4
- 5
- 6
- 7AO
Hello Folks! Agentic Orchestrator is a terminal tool that takes complex feature requests and builds them by orchestrating coding agents through a series of phases that emulate a full-fledged engineering flow: requirements clarification, research, design, multi-phase planning, implementation, and review. It is a single pane of glass for all your features and exposes post-publish utilities such as resolving merge conflicts and responding to review comments. The key design choice is that this is deterministic orchestration on top of undeterministic agents: things like "human review gates",…
Jun 2026 · github.com
- 8
- 9
- 10
- 11RT
This project (Agents Observe) started as an exploration into building automation harnesses around claude code. I needed a way to see exactly what teams of agents were doing in realtime and to filter and search their output. A few interesting learnings from building and using this: - Claude code hooks are blocking - performance degrades rapidly if you have a lot of plugins that use hooks - Hooks provide a lot more useful info than OTEL data - Claude's jsonl files provide the full picture - Lifecycle management of MCP processes started by plugins is a bit kludgy at best The biggest takeaway is…
Apr 2026 · github.com
- 12DR
Hi HN, we build an open-source operating system extension for orchestrating robot swarms fully decentralized. This first beta version allows you to create fully decentralized robot swarms. The system will set up a wireless mesh network and run a p2p networking stack on top of it, such that nodes can interact with each other through various abstractions using our SDKs (Rust, Python, TypeScript) or a CLI. We hope this is a step toward better inter-robot communication (and a fun project if you have a few Raspberry Pis lying around). Our mesh network is created by B.A.T.M.A.N.-adv and we’ve…
2025 · docs.p2p.industries
- 13
- 14AO
I have spent a long time working in an XP/TDD style, so when AI coding tools became useful enough for real work, I adopted them quickly. The first bottleneck I hit was not code generation, it was verification: AI could write code and tests quickly, but I was still the person reviewing implementations, clicking through flows, checking logs, inspecting database state, and deciding whether the result was actually correct. That pushed me to move validation further left. Before implementation, AI had to produce test plans. After implementation, it had to execute those plans too: drive the…
Mar 2026
- 15TI
Hey HN! I built AgentMGMT.dev today to keep track of all those agent orchestration tools that keep popping up. I've tried a few and landed on Superset, which I'm extremely happy (and productive!) with - but I think this category of tools will be extremely important and interesting in the next couple years, so it's worth keeping an eye on all available tools and how they evolve. I will keep the site up-to-date, please help me by submitting new tools that are not yet in the list, or add any details that might help folks who are out shopping for their first/next agent orchestrator!
May 2026 · agentmgmt.dev
- 16
Deploy AI agents in 60 seconds. No servers. No DevOps.
Mar 2026 · clawdeploy.cuemby.io
- 17
Zero-config hosting to launch specialized AI teams instantly
Feb 2026
- 18
- 19
- 20
- 21
- 22RT
Mar 2026 · github.com
- 232O
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
- 24RA
Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…
Mar 2026 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →