{"id":4938,"date":"2025-06-28T07:02:19","date_gmt":"2025-06-28T07:02:19","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/06\/28\/a-developers-guide-to-building-scalable-ai-workflows-vs-agents\/"},"modified":"2025-06-28T07:02:19","modified_gmt":"2025-06-28T07:02:19","slug":"a-developers-guide-to-building-scalable-ai-workflows-vs-agents","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/06\/28\/a-developers-guide-to-building-scalable-ai-workflows-vs-agents\/","title":{"rendered":"A Developer\u2019s Guide to Building Scalable AI: Workflows vs Agents"},"content":{"rendered":"<p>    A Developer\u2019s Guide to Building Scalable AI: Workflows vs Agents<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>A practical guide to choosing between AI agents and workflows for production systems, covering the hidden costs, architectural trade-offs, and decision framework that can save you thousands in deployment mistakes. Includes real-world examples and a scoring system to determine which approach fits your specific use case.<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/a-developers-guide-to-building-scalable-ai-workflows-vs-agents\/\">A Developer\u2019s Guide to Building Scalable AI: Workflows vs Agents<\/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    Hailey Quach<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/a-developers-guide-to-building-scalable-ai-workflows-vs-agents\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A Developer\u2019s Guide to Building Scalable AI: Workflows vs Agents A practical guide to choosing between AI agents and workflows for production systems, covering the hidden costs, architectural trade-offs, and decision framework that can save you thousands in deployment mistakes. Includes real-world examples and a scoring system to determine which approach fits your specific use [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2499,62,69,67,240,71,87,160,3087,3088],"tags":[98,100,3036],"class_list":["post-4938","post","type-post","status-publish","format-standard","hentry","category-ai-agents","category-aimldsaimlds","category-artificial-intelligence","category-deep-dives","category-editors-pick","category-large-language-models","category-llm","category-programming","category-software-architecture","category-workflows","tag-ai","tag-guide","tag-workflows"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/4938"}],"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=4938"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/4938\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=4938"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=4938"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=4938"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}