{"id":6126,"date":"2026-10-19T16:49:09","date_gmt":"2026-10-19T16:49:09","guid":{"rendered":"https:\/\/i10xnews.kinsta.cloud\/?p=6126"},"modified":"2026-10-19T17:18:25","modified_gmt":"2026-10-19T17:18:25","slug":"agentswe-coding-agents-building-agents","status":"publish","type":"post","link":"https:\/\/i10x.ai\/news\/agentswe-coding-agents-building-agents","title":{"rendered":"Coding Agents Can&#8217;t Build the Agent You Actually Want \u2014 Yet"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">\u26a1 Quick Take<\/h2>\n\n<ul class=\"wp-block-list\"><li><strong>The finding:<\/strong> Across Creation, Editing and Optimization of agents, no coding-agent builder comes close to delivering what a requirement asks for.<\/li><li><strong>The demo\u2013delivery gap:<\/strong> In Optimization, candidates gain 13.1 points on development cases but only 1.8 on held-out cases.<\/li><li><strong>Hard failures:<\/strong> In Creation, 58.1% of traced held-out executions fail a validity gate \u2014 usually by erroring or timing out.<\/li><\/ul>\n\n\n<p class=\"wp-block-paragraph\">Coding agents are increasingly asked to build other agents for a user&#8217;s workflow. Beijing Academy of Artificial Intelligence and collaborators introduce AgentSWE to test whether the delivered agent actually meets the requirement \u2014 not whether it demos well on a few examples.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1344\" height=\"768\" src=\"https:\/\/i10xnews.kinsta.cloud\/wp-content\/uploads\/2026\/10\/agentswe-coding-agents-building-agents-stages.webp\" alt=\"Column chart: strongest Creation average 19.1, Editing 31.6, Optimization closes at most 5 percent of the remaining gap.\" class=\"wp-image-6125\" srcset=\"https:\/\/i10x.ai\/news\/wp-content\/uploads\/2026\/10\/agentswe-coding-agents-building-agents-stages.webp 1344w, https:\/\/i10x.ai\/news\/wp-content\/uploads\/2026\/10\/agentswe-coding-agents-building-agents-stages-300x171.webp 300w, https:\/\/i10x.ai\/news\/wp-content\/uploads\/2026\/10\/agentswe-coding-agents-building-agents-stages-1024x585.webp 1024w, https:\/\/i10x.ai\/news\/wp-content\/uploads\/2026\/10\/agentswe-coding-agents-building-agents-stages-768x439.webp 768w\" sizes=\"auto, (max-width: 1344px) 100vw, 1344px\" \/><figcaption class=\"wp-element-caption\">i10X chart based on data from Wang et al. (2026), arXiv:2610.13361, main comparison (CC BY 4.0).<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udd2c What the study shows<\/h2>\n\n\n<p class=\"wp-block-paragraph\">25 tasks across Creation (agent from a natural-language requirement), Editing (production agent codebases) and Optimization (toward a measurable target). Builders iterate on illustrative cases; acceptance runs the frozen submission on held-out cases with requirement-derived rubrics.<\/p>\n\n\n<ul class=\"wp-block-list\"><li><strong>Low averages:<\/strong> Strongest builders average 19.1 on Creation and 31.6 on Editing.<\/li><li><strong>Optimization barely moves the needle:<\/strong> No builder closes more than 5% of the remaining gap to the target on average; only 13 of 25 runs beat their starter.<\/li><li><strong>Overfitting playbooks:<\/strong> On PinchBench, DeepSeek-V4-Flash and Pro gained 8.1 and 59.4 on development cases via keyword playbooks, then lost 15.2 and 15.1 on held-out cases.<\/li><li><strong>Cases matter:<\/strong> Going from zero to two development cases raises mean Result by 34.3 points on PDF translation and 29.3 on PPTX generation; without any case, all three PDF deliveries score zero.<\/li><\/ul>\n\n\n<h2 class=\"wp-block-heading\">\u2705 Why it matters: commissions are not exams<\/h2>\n\n\n<p class=\"wp-block-paragraph\">Passing a few demo cases is how agents get greenlit. AgentSWE shows that pattern systematically overstates delivery.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83e\uddea Method in brief<\/h2>\n\n\n<p class=\"wp-block-paragraph\">Held-out acceptance with hard pass\/fail gates or source-benchmark objectives for Optimization.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u2753 What remains open<\/h2>\n\n<ul class=\"wp-block-list\"><li><strong>25 tasks:<\/strong> Early benchmark; coverage will grow.<\/li><li><strong>Builder set:<\/strong> Results reflect current coding agents and harnesses.<\/li><\/ul>\n\n\n<h2 class=\"wp-block-heading\">\ud83e\udded Context<\/h2>\n\n\n<p class=\"wp-block-paragraph\">Related coding-agent evals in <a href=\"\/news\/category\/studies\/agent-research\">Agents<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udee0\ufe0f What it means for teams commissioning agents<\/h2>\n\n<ul class=\"wp-block-list\"><li><strong>Hold out acceptance cases:<\/strong> Never grade only on what the builder saw.<\/li><li><strong>Require validity gates:<\/strong> Many submissions never even run.<\/li><li><strong>Watch keyword playbooks:<\/strong> Huge train gains can reverse on held-out work.<\/li><\/ul>\n\n\n<h2 class=\"wp-block-heading\">\u270d\ufe0f About the analysis<\/h2>\n\n\n<p class=\"wp-block-paragraph\">This article is based on the full text of the preprint &#8220;AgentSWE: Can Coding Agents Build the Agent You Actually Want?&#8221; (arXiv:2610.13361v1, submitted October 9, 2026). All numbers are taken from the paper&#8217;s text, tables and figures; i10X did not rerun the experiments. The chart was redrawn by i10X from main comparison of the paper, which is published under a CC BY 4.0 license.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\ud83d\udd2d i10x Perspective<\/h2>\n\n\n<p class=\"wp-block-paragraph\">AgentSWE&#8217;s core claim is almost moral: a commission is a promise about unseen work. Today&#8217;s coding agents still deliver demos. Until Creation clears validity gates and Optimization generalizes, &#8220;build me an agent&#8221; remains an aspirational prompt.<\/p>\n\n","protected":false},"excerpt":{"rendered":"<p>AgentSWE&#8217;s 25 commission-style tasks: strongest builders average 19.1 on Creation and 31.6 on Editing. Optimization closes under 5% of the remaining gap; 58.1% of held-out Creation runs fail validity gates.<\/p>\n","protected":false},"author":2,"featured_media":6276,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"paper_title":"AgentSWE: Can Coding Agents Build the Agent You Actually Want?","paper_url":"https:\/\/arxiv.org\/abs\/2610.13361","pdf_url":"https:\/\/arxiv.org\/pdf\/2610.13361v1","doi":"","arxiv_id":"2610.13361","authors":"Jiahao Wang, Hongjin Qian, Yuyang Hu, Jiajun Zhang, Zheng Liu","institutions":"Beijing Academy of Artificial Intelligence; Institute of Automation, CAS; Renmin University of China","paper_date":"2026-10-09","venue":"arXiv (cs.SE), version 1","peer_reviewed":false,"code_url":"https:\/\/github.com\/VectorSpaceLab\/AgentSWE","data_url":"","funding_coi":"See paper.","figure_license":"Chart drawn by i10X from main comparison (CC BY 4.0)","paper_license":"CC BY 4.0","replication":"no","study_models":"Range of coding agents across models and harnesses incl. DeepSeek-V4 variants","study_sample":"25 AgentSWE tasks (Creation, Editing, Optimization)","footnotes":"","_yoast_wpseo_primary_category":""},"categories":[55,52],"tags":[],"companies":[46],"products":[],"class_list":["post-6126","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agent-research","category-studies","company-deepseek"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AgentSWE: Can Coding Agents Build the Agent You Want? - i10X News<\/title>\n<meta name=\"description\" content=\"AgentSWE: coding agents fail to deliver commissioned agents. 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