{"id":35245,"date":"2025-07-20T02:26:41","date_gmt":"2025-07-20T02:26:41","guid":{"rendered":"https:\/\/www.duck9.com\/blog\/?p=35245"},"modified":"2025-07-19T22:28:55","modified_gmt":"2025-07-20T02:28:55","slug":"context-engineering","status":"publish","type":"post","link":"https:\/\/www.duck9.com\/blog\/context-engineering\/","title":{"rendered":"Context Engineering"},"content":{"rendered":"
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Context engineering is increasingly the most critical component for building effective AI Agents in the enterprise right now. This will ultimately be the long pole in the tent for AI Agents adoption in most organizations. <\/div>\n
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We need AI Agents that can deeply understand the context of the business process that they\u2019re tied to. This means accessing the most important data for that workflow, using the appropriate tools at the right moment, having proper objectives and instructions, and understanding the domain that they\u2019re in.<\/div>\n
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Some of the big open items for anyone building enterprise agents are:<\/div>\n
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* Narrow vs. General agents. The smaller the task, the easier it is to give the AI Agents the right context to be successful. But the smaller the task, the less value there will be. Finding the optimal task size for value generation will be an important factor for the next few years. <\/div>\n
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* Getting data into an agent-ready system. Enterprise data is often fragmented between dozens or hundreds of systems, many of which are not prepared for a world of AI. Most companies will still need to modernize their data environments to get the full benefit of AI Agents.<\/div>\n
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* Accessing the *right* data for the task is paramount. Even when you have data in a modern environment, getting access controls perfectly aligned to what the AI Agent is going to need access to is critical. Further, deciding what to do RAG on vs. just a general search vs. what to put fully into the context window will matter a ton per task.<\/div>\n
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* Choosing what should be deterministic vs. non-deterministic. If you demand too much from the models, you\u2019re likely to see some drop off in quality. Yet, if you have the model do too little, then you\u2019re dramatically underutilizing what\u2019s possible with AI. This of course is a moving target because the models themselves are improving at an accelerating rate. <\/div>\n
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* The right user interface to get the AI Agents context deeply matters. Half of the problem for getting context to agents doesn\u2019t look like an AI problem at all. It\u2019s all about where the agents show up in the workflow and how the user interacts with them to provide them the context necessary to do the task.<\/div>\n
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The race for the next few years in AI in the enterprise is to see who best to deliver the right context for any given workflow. This will determine the winners and losers in the AI race.<\/div>\n
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Aaron Levie<\/a><\/b><\/td>\n<\/tr>\n
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Context engineering is increasingly the most critical component for building effective AI Agents in the enterprise right now. This will ultimately be the long pole in the tent for AI Agents adoption in most organizations. <\/p>\n

We need AI Agents that can deeply understand the context<\/td>\n<\/tr>\n

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7\/19\/25, 6:09\u202fPM<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/td>\n <\/td>\n<\/tr>\n
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Steve Jobs Texted me on 650-283-8008 in the same way that Mr Jobs called Bill Hewlett <\/span><\/span>https:\/\/x.com\/superSaiyanSkai\/status\/1941392367304761636\/video\/1<\/a><\/div>\n

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<\/span><\/span><\/div>\n
Larry Chiang<\/span><\/span><\/div>\n
Fund of Founders<\/div>\n
Founding Stanford EIR<\/div>\n
@duck9 alum, Deeply Understood Capital Credit Chinese Knowledge 9<\/div>\n
Solo Founder Uber API<\/div>\n
650-566-9600 Office<\/div>\n
650-566-9696 Direct<\/span><\/div>\n
Cell: 415-720-8500 <\/span><\/div>\n
650-283-8008 (cell)<\/span><\/div>\n

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9:59<\/span><\/span> video sums up 14 chapters of a book coming out 11-11-2039 “What They Will NEVER Teach You at Stanford Business School”<\/span>
http:\/\/www.youtube.com\/watch?v=ejeIz4EhoJ0<\/span><\/p>\n


Fashion Week’s front row
http:\/\/www.youtube.com\/watch?v=QXIaNZi3mHQ<\/span><\/span><\/div>\n

What A Super Model Can Teach a Harvard MBA About Credit www.slideshare.net\/larrychiang\/what-a-super-model-can-teach-a-harvard-mba-about-credit<\/a><\/span><\/p>\n

American Express hosts me mentoring you about FICO scores at New York Fashion Week
t.co\/inxTmZAj<\/a><\/span><\/p>\n

My video boils down 20,000 hours and moves you to the right on the entrepreneur bell curve 
http:\/\/www.youtube.com\/watch?v=eudADPfTWiE<\/span>
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Editor of the widely syndicated “What They Don’t Teach at School”
whattheydontteachyouatstanfordbusinessschool.com\/blog<\/a><\/span><\/p>\n

CNN Video Channel: ireport.cnn.com\/people\/larrychiang<\/a><\/span><\/p>\n

Read my last 10 X posts at www.X.com\/LarryChiang<\/a><\/span><\/p>\n

Author of #WTDTYASBS a NY Times Bestseller released 09-09-09 at #NYFW on a runway under the tents
whattheydontteachyouatstanfordbusinessschool.com\/blog\/?s=Ny+times+bestseller<\/a><\/span><\/p>\n

www.fastcompany.com\/embed\/c0d4562ea2049<\/a><\/span><\/p>\n

52 Cards. Two Jokers. What They DO Teach You at Stanford Engineering
http:\/\/www.youtube.com\/watch?v=vDBY0GkI3-g<\/span><\/p>\n

Emergency swings and cutting deals as an 9 year old
http:\/\/www.youtube.com\/watch?v=OFGY7v9C4G0<\/span><\/p>\n

Hunter Pence shared thoughts before winning WORLD SERIES’ Game #7
http:\/\/www.youtube.com\/watch?v=usu0luYy9pw<\/span><\/span><\/p>\n


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Context engineering is increasingly the most critical component for building effective AI Agents in the enterprise right now. This will ultimately be the long pole in the tent for AI Agents adoption in most organizations.  We need AI Agents that can deeply understand the context of the business process that they\u2019re tied to. This means […]<\/p>\n","protected":false},"author":1,"featured_media":35246,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-35245","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\/35245","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=35245"}],"version-history":[{"count":0,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/posts\/35245\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/media\/35246"}],"wp:attachment":[{"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/media?parent=35245"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/categories?post=35245"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.duck9.com\/blog\/wp-json\/wp\/v2\/tags?post=35245"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}