LLM models are not ready for orchestrating many agents
Current LLM models are not equipped to manage multiple agents effectively. They tend to prefer completing tasks independently rather than delegating. Improvements in training are necessary for these models to function as managers rather than individual workers.
- ▪Current LLM models are not trained for orchestrating or managing multiple agents.
- ▪The main agent often performs tasks itself instead of allowing sub-agents to work.
- ▪Claude swarms feature does not work seamlessly, leading to issues with merging pull requests.
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| Original publisher | Ycombinator |
| Canonical URL | https://news.ycombinator.com/item?id=48163477 |
| Publication time | Sat, 16 May 2026 20:24:22 +0000 |
| Retrieval time | 2026-05-16T20:40:19.047Z |
| Last seen | 2026-05-16T20:40:19.047Z |
| 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 | X1CBzpSVOeCv |
| 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 |
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| 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
Hi, i have been experimenting with many coding agents distributed in a tree like heirarchy. here is what i found: 1. current LLM models are not trained for orchestrating or managing multiple agents, they prefer doing the work by themselves instead of outsourcing it. 2. you can prompt them to follow the given heirarchy but it is not perfect, main agent will stop the sub agent and perform the work by itself. 3. claude swarms was a feature, but it just does not work seamlessly, i don't want 10 agents to give me a single PR, i want a merged final PR, but you have to ask the main agent to give that, and most of the times, the main agent messes things up while merging all the PRs.and the only solution is to include these things in the training of the models, current models are individual…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.