{"id":14150,"date":"2026-04-07T05:26:35","date_gmt":"2026-04-07T09:26:35","guid":{"rendered":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=14150"},"modified":"2026-04-07T06:20:55","modified_gmt":"2026-04-07T10:20:55","slug":"escaping-the-prototype-mirage-why-enterprise-ai-stalls","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/escaping-the-prototype-mirage-why-enterprise-ai-stalls\/14150\/","title":{"rendered":"Escaping the Prototype Mirage: Why Enterprise AI Stalls"},"content":{"rendered":"Originally published on\u00a0Towards Data Science, March 4, 2026. Too many prototypes, too few products Software development has fundamentally changed in the GenAI era. With the ubiquity of vibe coding tools and agent-first IDEs like Google\u2019s Antigravity, developing new applications has never been faster. Further, the powerful concepts inspired by viral open-source frameworks like OpenClaw are enabling the creation of autonomous systems. We can drop agents into secure Harnesses, provide them with executable Python Skills, and define their System Personas in simple Markdown files. We use the recursive Agentic Loop (Observe-Think-Act) for execution, set up headless Gateways to connect <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/escaping-the-prototype-mirage-why-enterprise-ai-stalls\/14150\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Originally published on\u00a0Towards Data Science, March 4, 2026. Too many prototypes, too few products Software development has fundamentally changed in the GenAI era. With the ubiquity of vibe coding tools and agent-first IDEs like Google\u2019s Antigravity, developing new applications has never been faster. Further, the powerful concepts inspired by viral open-source frameworks like OpenClaw are [&hellip;]<\/p>\n","protected":false},"author":13468,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11,48],"tags":[],"class_list":["post-14150","post","type-post","status-publish","format-standard","hentry","category-industry-news","category-left-hand"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14150","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/13468"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=14150"}],"version-history":[{"count":4,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14150\/revisions"}],"predecessor-version":[{"id":14154,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/14150\/revisions\/14154"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=14150"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=14150"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=14150"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}