Best-of-Agent-Harnesses – Ranked list of 167 AI agent harnesses, rescored weekly
An agent harness is the runtime that turns one into the other: the model thinks, the harness decides what that thinking is allowed to touch. Simon Willison's definition of the agent itself is the cleanest: "an LLM agent runs tools in a loop to achieve a goal." The harness is everything around that loop: which tools exist, what needs approval, what the model sees each turn, what survives a crash. Andrej Karpathy named the architecture back in 2023: the model is "the kernel process of a new Operating System", and the harness is the rest of that OS, its scheduler, permissions, and memory.
- ▪An agent harness is the runtime that turns one into the other: the model thinks, the harness decides what that thinking is allowed to touch.
- ▪Simon Willison's definition of the agent itself is the cleanest: "an LLM agent runs tools in a loop to achieve a goal." The harness is everything around that loop: which tools exist, what needs approval, what the model sees each turn, what
- ▪Andrej Karpathy named the architecture back in 2023: the model is "the kernel process of a new Operating System", and the harness is the rest of that OS, its scheduler, permissions, and memory.
Hacker News (AI / LLM) files mainly under ai. We currently carry 7,261 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/ryanalberts/best-of-agent-harnesses |
| Publication time | Fri, 02 Oct 2026 01:57:56 +0000 |
| Retrieval time | 2026-10-02T02:15:26.438Z |
| Last seen | 2026-10-02T02:15:26.438Z |
| 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 | Q3-DFo3ywrQi · 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
Best of Agent Harnesses and Harness Techniques 🏆 Curated list of AI agent harnesses, orchestration frameworks, and harness techniques for reliable agentic systems. 🌐 Browse the searchable site — one page per harness, filter by capability, autonomy & recovery. 🧰 Templates and Playbooks: copy-paste setup files and step-by-step guides for the harnesses in this list. 🤖 Agents can query this list — an MCP server (recommend, pick_harness, …), llms.txt & JSON, so your agent recommends harnesses too. What is an agent harness? A model answers; an agent acts. An agent harness is the runtime that turns one into the other: the model thinks, the harness decides what that thinking is allowed to touch.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.