Alternatives
Products that do what HyperWorker does
Project management harness for AI agents
- 1
HarnessRouter▲238Bring the world's best AI agents into your app, with one API
Jul 2026 · harnessrouter.ai
- 2
Open-source unified interface for agent harnesses
22d ago · harnessrouter.ai
- 3
- 4
Deep Work Plan▲114Models matter. Context matters more. Give your agent a plan.
Jun 2026 · deepworkplan.com
- 52C
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
- 6
- 7
- 8
- 9AH
May 2026 · ahk.cardor.dev
- 10PM
I built a lightweight project management workflow to keep AI-driven development organized. The problem was that context kept disappearing between tasks. With multiple Claude agents running in parallel, I’d lose track of specs, dependencies, and history. External PM tools didn’t help because syncing them with repos always created friction. The solution was to treat GitHub Issues as the database. The "system" is ~50 bash scripts and markdown configs that: - Brainstorm with you to create a markdown PRD, spins up an epic, and decomposes it into tasks and syncs them with GitHub issues - Track…
2025 · github.com
- 11
- 12
- 13GA
Hey HN! Wanted to show our open source agent harness called Gambit. If you’re not familiar, agent harnesses are sort of like an operating system for an agent... they handle tool calling, planning, context window management, and don’t require as much developer orchestration. Normally you might see an agent orchestration framework pipeline like: compute -> compute -> compute -> LLM -> compute -> compute -> LLM we invert this so with an agent harness, it’s more like: LLM -> LLM -> LLM -> compute -> LLM -> LLM -> compute -> LLM Essentially you describe each agent in either a self contained…
Jan 2026 · github.com
- 14
- 15
- 16
- 17RT
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
- 18
Hey HN! We are building HarnessRouter, a canonical API for running Codex, Claude Code, Hermes, and other managed agent harnesses as your product backend. Before building HarnessRouter, I used to build our own agent harness for our products. I tried LangGraph, agent SDKs from different vendors, pydantic, LLM tool use / function call, and so on. It's a very heavy lifting engineering effort, and I am disappointed about the agent deliveries compared to what Codex, CC can deliver. That changed my mindset. The frontier labs and famous open source communities are already putting so much…
20d ago · github.com
- 19
AgentGrid▲77Hi HN, I’m Michael, I built AgentGrid with my friend Souren because we were tired of losing our coding sessions and couldn't keep track of what was actually being built across our many projects. Our approach was to use an infinite canvas desktop app for the TUIs we already know and love, mainly claude + codex. We drew inspiration from Figma and Railway. Overtime we added image nodes, notes, terminals, coding editors, source control, etc. I wasn't sure about it at first. It took me a month to give the first version Souren built a real try. What got me was an Apple System Update I've been…
Jul 2026 · agentgrid.sh
- 20MA
We built meta-agent: an open-source library that automatically and continuously improves agent harnesses from production traces. Point it at an existing agent, a stream of unlabeled production traces, and a small labeled holdout set. An LLM judge scores unlabeled production traces as they stream. A proposer reads failed traces and writes one targeted harness update at a time, such as changes to prompts, hooks, tools, or subagents. The update is kept only if it improves holdout accuracy. On tau-bench v3 airline, meta-agent improved holdout accuracy from 67% to 87%. We open-sourced meta-agent.…
Apr 2026 · github.com
- 21AO
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
- 22CS
We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
Feb 2026 · docs.continue.dev
- 23OA
We were both genuinely impressed by Claude Code after it helped each of us fix nasty CI problems overnight. Doing those fixes manually would have taken days. After that experience, we each found ourselves struggling through Ctrl+Tab through multiple Claude Code windows in our terminals. While we enjoyed having agents working for us in parallel, context switching and cycling through each terminal tab was a real pain. So we thought: Can we design a TUI dashboard that manages a large swarm of agents in one place? Even better, can agents manage agents hierarchically, like how companies work?…
May 2026 · omar.tech
- 24CA
I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
Ranked by how close each launch is in meaning, then by votes. Refine with a description →