Uploaded August 2026 | Updated September 2026, 2 weeks ago
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
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Memory engineering is not a new technique. It has just picked up a new name. This lesson covers what memory actually means inside an AI agent, so you can answer it properly at work or in an interview.
We start with where memory sits between context engineering and harness engineering, then go through short-term versus long-term memory, the three types people usually miss (semantic, episodic and procedural), and the one that actually bites you in production: a retrieved memory is only as good as the memory you wrote. Store the wrong things and your agent quietly gets worse. This is a concept lesson, so there is no code.
Get the full ppt here:
slideshare.net/slideshow/mastering-memory-engineering-in-genai-for-banking-finance/289052319
⏱ Chapters:
0:00 Memory engineering is not a new technique
0:27 Where memory fits in agentic AI engineering
1:44 Short-term vs long-term memory
2:58 Semantic memory: storing facts about the user
3:32 Episodic memory: how memory evolves over time
3:55 Procedural memory: agents that edit their own prompt
4:36 Why bad memory makes a bad agent
5:04 Use a confidence threshold, do not dump everything
5:44 Wrap up
📺 Watch next:
What is Graph Engineering? Agentic AI Engineering Explained
youtu.be/S1vqM0aTRFc
What is Loop Engineering? Agentic AI Engineering Explained
youtube.com/watch?v=VTLeQLn-Vn8
🎓 Go deeper with my Udemy course:
Master LangGraph v1 and Ollama - Build Gen AI Agents
kgptalkie.com/langgraph
If this made memory click, leave a like. Got a question, or want a lesson on a related topic? Put it in the comments. Subscribe and hit the bell to catch the rest of this series.
#MemoryEngineering #AgenticAI #AIAgents #LangGraph #GenAI
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
----------
Memory engineering is not a new technique. It has just picked up a new name. This lesson covers what memory actually means inside an AI agent, so you can answer it properly at work or in an interview.
We start with where memory sits between context engineering and harness engineering, then go through short-term versus long-term memory, the three types people usually miss (semantic, episodic and procedural), and the one that actually bites you in production: a retrieved memory is only as good as the memory you wrote. Store the wrong things and your agent quietly gets worse. This is a concept lesson, so there is no code.
Get the full ppt here:
slideshare.net/slideshow/mastering-memory-engineering-in-genai-for-banking-finance/289052319
⏱ Chapters:
0:00 Memory engineering is not a new technique
0:27 Where memory fits in agentic AI engineering
1:44 Short-term vs long-term memory
2:58 Semantic memory: storing facts about the user
3:32 Episodic memory: how memory evolves over time
3:55 Procedural memory: agents that edit their own prompt
4:36 Why bad memory makes a bad agent
5:04 Use a confidence threshold, do not dump everything
5:44 Wrap up
📺 Watch next:
What is Graph Engineering? Agentic AI Engineering Explained
youtu.be/S1vqM0aTRFc
What is Loop Engineering? Agentic AI Engineering Explained
youtube.com/watch?v=VTLeQLn-Vn8
🎓 Go deeper with my Udemy course:
Master LangGraph v1 and Ollama - Build Gen AI Agents
kgptalkie.com/langgraph
If this made memory click, leave a like. Got a question, or want a lesson on a related topic? Put it in the comments. Subscribe and hit the bell to catch the rest of this series.
#MemoryEngineering #AgenticAI #AIAgents #LangGraph #GenAI
