Show HN: Raven – The harness of harnesses, built for RSI
Technical Report · Website · Documentation · 中文 What is Raven One Surface, All Agents: Raven generates DAGs and orchestrates multiple specialized agents for complex tasks. Raven is the harness of harnesses, built for recursive self-improvement (RSI). As a Host Agent, it brings built-in and third-party agents together to carry out complex tasks.
- ▪Technical Report · Website · Documentation · 中文 What is Raven One Surface, All Agents: Raven generates DAGs and orchestrates multiple specialized agents for complex tasks.
- ▪Raven is the harness of harnesses, built for recursive self-improvement (RSI).
- ▪As a Host Agent, it brings built-in and third-party agents together to carry out complex tasks.
Hacker News (Front Page) files mainly under programming. We currently carry 2,264 of its stories. Top-voted stories on Hacker News.
Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/EverMind-AI/Raven |
| Publication time | Tue, 29 Sep 2026 09:58:24 +0000 |
| Retrieval time | 2026-09-29T12:41:21.848Z |
| Last seen | 2026-09-29T12:41:21.848Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | W0t029HWvwhu · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Technical Report · Website · Documentation · 中文 What is Raven One Surface, All Agents: Raven generates DAGs and orchestrates multiple specialized agents for complex tasks. Raven is the harness of harnesses, built for recursive self-improvement (RSI). As a Host Agent, it brings built-in and third-party agents together to carry out complex tasks. Its modular architecture supports iterative improvement of Raven's own harness: proposing changes to how agents plan and act, evaluating those changes, and adopting improvements that pass validation. Powered by EverOS, Raven carries memory and context across sessions to support this process. Built-in Agents: Raven-Research, Raven-Code, Raven-Design, and Raven-Oncall support research, coding, visual design, and unattended workflow automation.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.