--- title: Your AI agents aren't failing at reasoning, they're... description: A new arXiv paper argues that production AI agents fail primarily due to poor context management rather than reasoning limitations. It proposes 'Agentic... canonical: https://daily.dev/posts/your-ai-agents-aren-t-failing-at-reasoning-they-re-drowning-in-their-own-context-ptyshbifr twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Your AI agents aren't failing at reasoning, they're drowning in their own context | daily.dev og:description: A new arXiv paper argues that production AI agents fail primarily due to poor context management rather than reasoning limitations. It proposes 'Agentic... og:url: https://daily.dev/posts/your-ai-agents-aren-t-failing-at-reasoning-they-re-drowning-in-their-own-context-ptyshbifr og:image: https://api.daily.dev/og/posts/pTysHBIfr.png og:image:alt: Your AI agents aren't failing at reasoning, they're drowning in their own context og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Your AI agents aren't failing at reasoning, they're drowning in their own context **[Trends](https://daily.dev/sources/trends)** · 2 min read · 6 upvotes · 5 comments ## Summary A new arXiv paper argues that production AI agents fail primarily due to poor context management rather than reasoning limitations. It proposes 'Agentic Context Management' as a formal discipline built around five primitives: architecting, ingesting, scoping, anticipating, and compacting. Naive context accumulation causes token costs to grow quadratically; crude summarization reduces this to linear but risks silent accuracy loss. Only validated compaction — checking compressed context against the original — achieves linear cost without accuracy degradation. A reference implementation called Synap scores 92% on LongMemEval and 93.2% on LoCoMo. The five-primitive vocabulary is seen as practically useful for teams currently improvising context management by feel. ## Content There's a paper making the rounds this weekend that reframes a problem most agent builders have been solving wrong. The argument: production agents don't fail because they can't reason. They fail because their context is a mess. Conversation history, bloated system prompts, verbose tool definitions, and tool outputs that nobody trimmed — they pile up every turn. The standard fix is "add memory and retrieval." The paper says that's too narrow a frame. The proposed alternative is **Agentic Context Management**, a five-part discipline: architecting (what structure does context have), ingesting (what gets let in), scoping (what stays relevant), anticipating (what gets pre-loaded before it's needed), and compacting with consolidation (how you compress without losing facts). The compaction point is where it gets concrete. Naive accumulation means token cost grows with the *square* of conversation length. Crude summarization flattens that curve but quietly drops facts. Only compaction that validates fidelity against the original gets you linear cost growth without the accuracy cliff. The reference implementation — something called Maximem Synap — reportedly hits 92% on LongMemEval and 93.2% on LoCoMo categories 1-4. Multi-session reasoning was the weakest link, which is honest at least. Kent C. Dodds put the practitioner version bluntly: "Stop being a context shuffling manager and give your agent secure access to the services it needs to do its job." The framing shift here matters. Context management isn't a memory plugin you bolt on — it's an architectural concern that touches every layer of how an agent operates. If your agent is misbehaving in production, the context window is probably where you should look first. ## Community discussion Top comments from developers on daily.dev. **@rizzdev** · 0 upvotes > It's always always the context. (When there is a problem) **@nilasijayathilake** · 0 upvotes > Can we get the link to the paper? ## Similar posts on daily.dev - [What Makes 5% of AI Agents Actually Work in Production?](https://daily.dev/posts/what-makes-5-of-ai-agents-actually-work-in-production--szxct2pwg) · Hacker News · 4 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#prompt-engineering](https://daily.dev/tags/prompt-engineering), [#context-engineering](https://daily.dev/tags/context-engineering) [View this post on daily.dev](https://daily.dev/posts/your-ai-agents-aren-t-failing-at-reasoning-they-re-drowning-in-their-own-context-ptyshbifr) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Your AI agents aren't failing at reasoning, they're drowning in their own context","url":"https://daily.dev/posts/your-ai-agents-aren-t-failing-at-reasoning-they-re-drowning-in-their-own-context-ptyshbifr","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/your-ai-agents-aren-t-failing-at-reasoning-they-re-drowning-in-their-own-context-ptyshbifr"},"datePublished":"2026-07-25T08:29:35.748Z","dateModified":"2026-07-27T17:30:00.731Z","description":"A new arXiv paper argues that production AI agents fail primarily due to poor context management rather than reasoning limitations. 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(When there is a problem)","datePublished":"2026-07-31T04:49:31.721Z","url":"https://daily.dev/posts/pTysHBIfr#c-gdKz7tPti","author":{"@type":"Person","name":"Andrew","url":"https://daily.dev/rizzdev","image":"https://media.daily.dev/image/upload/s--35vRfXAA--/f_auto/v1785413727/avatars/avatar_fQ7ttCKtPuu6tDvcgQXv5?_a=BAMAMicg0"}},{"@type":"Comment","text":"Can we get the link to the paper?","datePublished":"2026-07-26T04:07:17.395Z","url":"https://daily.dev/posts/pTysHBIfr#c-0QaDSJzt2","author":{"@type":"Person","name":"Nilasi Jayathilake","url":"https://daily.dev/nilasijayathilake","image":"https://avatars.githubusercontent.com/u/136611590?v=4"}}]} ```