Author: Google Cloud Tech – Duration: 00:10:05

White Paper on Context Engineering → https://goo.gle/3QiKYbT

More info on context engineering → https://goo.gle/43fII8c

Context engineering: Why writing bigger prompts won't fix your AI, and what to do instead. In this video, Smitha Kolan explains what contextual engineering is, how it differs from rapid engineering, and gives you a practical, step-by-step framework for creating smarter, more reliable AI agents. Models continue to have larger context windows, but longer context is not always better. When windows are filled with everything, accuracy decreases and errors creep in. Contextual engineering is the discipline of curating the smallest set of high-level information the model needs at each step: the right instructions, the right tools, the right facts, and nothing more. In this video you will learn: * 📌The 7 components of a well-designed context stack. * ⚠️ The 4 failure modes that break AI agents. * 🛠️ The 4 steps of context engineering. Chapters: 0:00 – Bigger prompts don't solve bad AI 0:47 – What is context engineering? 1:39 – Why context size isn't everything 2:18 – Four failure modes: poisoning, distraction, confusion, conflict 2:58 – Context engineering vs. prompt engineering 4:16 – The seven components of a context stack 5:02 – Creating LogLook: an example of a realistic agent 7:00 – The 4 steps of context engineering 7:08 – Step 1: writing 7:50 – Step 2: Select 8:34 – Step 3: Compress 9:14 – Step 4: Isolate 9:50 – Organize, don't dump More resources: MCP explained → https://goo.gle/3QY4Hhw

MCP vs. API → https://goo.gle/4ffLPCF

Watch more modern AI agents: from theory to production → https://goo.gle/Learn-with-Smitha

🔔 Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech

#ContextEngineering #PromptEngineering #AIAgents #GoogleCloud #Gemini #ArtificialIntelligence #MachineLearning Speaker: Smitha Kolan Products Mentioned: AI Infrastructure