Nicheloom

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Agent Orchestrator, a local-first Harness Engineering control plane

Details

External ID
47562440
Source
HN
Company
—
Product
—
Website domain
—
Launched
March 29, 2026
Cohort
—
Upvotes
15
Upvotes percentile
0.6845018450184502
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

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 browser, inspect logs, check DB state, create tickets for failures, fix them, and retest until the output converged. Auth9 (https://github.com/c9r-io/auth9) became the proving ground for that method. Once it was clearly working, I started building Agent Orchestrator so the process would not depend on me manually supervising every step.By mid-February, I was already using early Orchestrator-style automation inside Auth9. In mid-March, I used it during the highest-risk refactor so far: replacing the headless Keycloak setup with a native `auth9-oidc` engine. The core replacement landed over 3 days, and the same method and tooling helped converge the follow-up technical debt and complete the community OIDC Certification tests by the end of the month. That was the point where I became confident this was useful not only for greenfield work, but for governing high-risk change in a real system.At the time, "orchestration" was the word I cared most about, which is why the project got its name. Later, OpenAI's Harness Engineering framing gave me a better name for the broader shape of the work. The project today is a local-first Rust control plane for long-running agent workflows: YAML resources, SQLite-backed task state, machine-readable CLI output, structured logs, and guardrails around shell-based agents.- GitHub: https://github.com/c9r-io/orchestrator - Docs: https://docs.c9r.io - Auth9: https://github.com/c9r-io/auth9 - Install: `brew install c9r-io/tap/orchestrator` or `cargo install orchestrator-cli orchestratord` - License: MIT

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Workflow automation
Audience
B2B
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
local-first control plane for engineering
Manually corrected
False

Could you build this?

Yes This is a local orchestration and harness control plane for coordinating AI agents, running test suites, and collecting verification metrics, which is straightforward to build with standard scripting and UI frameworks.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 592 launches clear the similarity bar, closest 8 shown.

Attention rank: #232 of 593 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 146 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a workflow automation tool for Real estate yet.