𝐃𝐚𝐲 𝟒𝟖/𝟏𝟎𝟎 𝐨𝐟 𝐀𝐠𝐞𝐧𝐭 𝐌𝐞𝐦𝐨𝐫𝐲 🧠 I had the honour of speaking at the @PromptEngConf, where I explored the evolution from Prompt → Context → Memory Engineering — and why memory will define the next generation of intelligent systems. In my talk, I covered how↴ 1️⃣ Prompt Engineering taught us how to instruct models — turning language into a programmable interface. 2️⃣ Context Engineering introduced structure and retrieval, designing the environment an LLM reasons within — but it’s still bounded by the model’s finite attention span. 3️⃣ Memory Engineering extends both — creating persistent, evolving knowledge that preserves experience and coherence across time. It’s how we move from reactive systems to adaptive ones. I was surprised by the number of folks the talk resonated with. Memory Engineering isn’t marketing language; many developers are already implementing parts of it without realizing it — building retrieval layers, semantic caches, and reflection loops to make their agents more coherent over time. It’s an emerging technical discipline focused on persistence, retrieval, and adaptation — turning transient context into structured, retrievable experience that makes AI systems more reliable, believable, and capable over time. In the coming weeks, more talks on agent memory and memory engineering will be coming to a city near you. 😉 #100DaysOfAgentMemory #MemoryEngineering #ContextEngineering #PromptEngineering #LLM #AI #AgenticSystems #AIConferences #AIDevelopment #ThoughtLeadership