A Simple Puzzle Reveals the Jagged Edge of AI's Abilities
Researchers describe the concept of "jagged intelligence" to explain how AI models possess powerful capabilities yet still commit basic errors. The article outlines a process where a large language model is taught to solve a simple puzzle from scratch to demonstrate this phenomenon. This exercise reveals the irregular boundary between what AI can and cannot do effectively.
- ▪AI models are characterized by "jagged intelligence," which indicates a jagged boundary between their abilities and limitations.
- ▪Despite significant advances, AI systems can still make basic blunders in their reasoning.
- ▪The article details a method for teaching a large language model to solve a simple puzzle starting from scratch.
- ▪This demonstration serves to illustrate exactly how jagged intelligence emerges in AI systems.
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Record
| Original publisher | Aatish Bhatia |
| Canonical URL | https://aatishb.com/blog/2026/ai-jagged-intelligence/ |
| Publication time | Sat, 26 Sep 2026 21:31:55 +0000 |
| Retrieval time | 2026-09-26T21:40:40.161Z |
| Last seen | 2026-09-26T21:40:40.161Z |
| 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 | PZp5BxyskmAW · 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
Aatish BhatiaBlogMediaAboutHow a Simple Puzzle Reveals the Jagged Edge of AI’s AbilitiesSept. 23, 2026 It’s undeniable that AI models have gained many powerful abilities. And yet, for all of their advances, they can still make basic blunders. Researchers call this “jagged intelligence,” a term suggesting that there’s a jagged boundary separating what AI can and can’t do. In this article, I’ll teach a large language model how to solve a simple puzzle, starting from scratch, and we’ll see exactly how this jagged intelligence emerges.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Aatish Bhatia.
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