{"id":38387,"date":"2026-05-17T19:29:23","date_gmt":"2026-05-17T19:29:23","guid":{"rendered":"https:\/\/www.duck9.com\/blog\/?p=38387"},"modified":"2026-05-17T15:29:35","modified_gmt":"2026-05-17T19:29:35","slug":"native-model-knowledge-only-short-term-chat-history-long-term-persisted-files-and-external-tools-like-web-search","status":"publish","type":"post","link":"https:\/\/www.duck9.com\/blog\/native-model-knowledge-only-short-term-chat-history-long-term-persisted-files-and-external-tools-like-web-search\/","title":{"rendered":"native model knowledge only, short-term chat history, long-term persisted files, and external tools like web search."},"content":{"rendered":"
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\u2022  @mobileraj shares a teaching framework for LLMs that layers knowledge access: native model knowledge only, short-term chat history, long-term persisted files, and external tools like web search.<\/div>\n
\u2022  The approach demonstrates how these elements combine to build a complete AI \u201charness,\u201d making abstract concepts like context windows and tool use easier to understand for learners.<\/div>\n
\u2022  This progressive structure mirrors real-world AI system design, highlighting how restricting or enabling memory\/tools reveals the boundaries and strengths of large language models.\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b<\/div>\n<\/div>\n
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Thought this framing for teaching was neat: 1. Can you research X, you’re not allowed to use any memory or other (demonstrates what the LLM natively knows) 2. You can use short term memory (the chat history) 3. You can use long term memory (any files persisted that contain<\/div>\n<\/td>\n<\/tr>\n
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Raj Singh (@mobileraj)<\/font><\/a><\/div>\n
x.com<\/font><\/a><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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http:\/\/www.youtube.com\/watch?v=QXIaNZi3mHQ<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

\u2022  @mobileraj shares a teaching framework for LLMs that layers knowledge access: native model knowledge only, short-term chat history, long-term persisted files, and external tools like web search. \u2022  The approach demonstrates how these elements combine to build a complete AI \u201charness,\u201d making abstract concepts like context windows and tool use easier to understand for […]<\/p>\n","protected":false},"author":1,"featured_media":38388,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-38387","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"post_mailing_queue_ids":[],"_links":{"self":[{"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/posts\/38387","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/comments?post=38387"}],"version-history":[{"count":0,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/posts\/38387\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/media\/38388"}],"wp:attachment":[{"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/media?parent=38387"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/categories?post=38387"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/tags?post=38387"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}