{"id":8833,"date":"2025-12-04T07:02:22","date_gmt":"2025-12-04T07:02:22","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/12\/04\/how-to-turn-your-llm-prototype-into-a-production-ready-system\/"},"modified":"2025-12-04T07:02:22","modified_gmt":"2025-12-04T07:02:22","slug":"how-to-turn-your-llm-prototype-into-a-production-ready-system","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/12\/04\/how-to-turn-your-llm-prototype-into-a-production-ready-system\/","title":{"rendered":"How to Turn Your LLM Prototype into a Production-Ready System"},"content":{"rendered":"<p>    How to Turn Your LLM Prototype into a Production-Ready System<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>The most famous applications of LLMs are the ones that I like to call the \u201cwow effect LLMs.\u201d There are plenty of viral LinkedIn posts about them, and they all sound like this: \u201cI built [x] that does [y] in [z] minutes using AI.\u201d Where: If you notice carefully, the focus of the sentence is [\u2026]<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/how-to-turn-your-llm-prototype-into-a-production-ready-system\/\">How to Turn Your LLM Prototype into a Production-Ready System<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Piero Paialunga<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/how-to-turn-your-llm-prototype-into-a-production-ready-system\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>How to Turn Your LLM Prototype into a Production-Ready System The most famous applications of LLMs are the ones that I like to call the \u201cwow effect LLMs.\u201d There are plenty of viral LinkedIn posts about them, and they all sound like this: \u201cI built [x] that does [y] in [z] minutes using AI.\u201d Where: [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,69,67,71,1930,1771,157],"tags":[7,4354,163],"class_list":["post-8833","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-artificial-intelligence","category-deep-dives","category-large-language-models","category-llm-applications","category-prompt-engineering","category-python","tag-how","tag-turn","tag-your"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/8833"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=8833"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/8833\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=8833"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=8833"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=8833"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}