A New AI Agent Oriented Programming Language
Grenat Ruby's syntax, Rust's speed, agents as first-class citizens. Typed prompts, and answers that must be checked A prompt is a function a model implements. Its return type becomes a JSON schema, and the ## comments describe the fields to the model.
- ▪Grenat Ruby's syntax, Rust's speed, agents as first-class citizens.
- ▪Typed prompts, and answers that must be checked A prompt is a function a model implements.
- ▪Its return type becomes a JSON schema, and the ## comments describe the fields to the model.
Hacker News (AI / LLM) files mainly under ai. We currently carry 7,824 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
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/itsmedit/grenat |
| Publication time | Wed, 07 Oct 2026 20:09:43 +0000 |
| Retrieval time | 2026-10-07T20:53:59.990Z |
| Last seen | 2026-10-07T20:54:09.677Z |
| 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 | sXfDX51r5QJ8 · 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
Grenat Ruby's syntax, Rust's speed, agents as first-class citizens. Grenat is a compiled programming language for building AI agent systems: typed prompts, tools, supervised actor agents, budgets, durable workflows, and an effect system that turns prompt injection into a compile-time error. prompt summarize(article: String) -> ~Summary using :fast user "Summarize: #{article}" end agent Researcher model :smart tools search_web, read_url budget usd: 2.00, time: 10.min on Research(topic: String) -> ~Report run "Investigate #{topic}" end end Specification: SPEC.md A compact reference for LLMs writing Grenat: llms.txt Examples: basics.grn, reviews.grn (native statistics + validated LLM analysis), explorer.grn (a real agent), support_desk.grn (multi-agent, human approval), triage.grn (tests…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.