**Build Agentic Memory That Keeps Your Loops Alive and Sharpens Them Every Run**

> A hands-on course on agentic memory: first make your loop survive long runs, then make it compound across them. Every step ships with copy-paste Memanto commands - typed remember/recall, session handoffs, structured failure records, and a reuse loop that makes each run start smarter than the last. ← Back to all posts Tutorials July 9, 2026 18 min read The Practical Course: Build Agentic Memory That Keeps Your Loops Alive And Sharpens Them Every Run A hands-on course on agentic memory: first make your loop survive long runs, then make it compound across them. Every step ships with copy-paste Memanto commands - typed remember/recall, session handoffs, structured failure records, and a reuse loop that makes each run start smarter than the last. DM Dr. Majid Fekri CTO Copy link Share AGENT MEMORY ON THIS PAGE What Agentic Memory Actually Is The Mistake Almost Everyone Makes Step 1: Map The Loop Before You Build Any Memory Step 2: Draw The Line Between Working Memory And Persistent Memory Step 3: Engineer Within-Run Memory — Keep The Loop Alive Step 4: Add The Handoff — So The Loop Survives Across Context Windows Step 5: Capture The Right Things — Especially The Failures Step 6: Build The Reuse Loop — Feed Yesterday&\#x27;s Memory Into Today&\#x27;s Run Step 7: Test Your Memory Before You Trust It Step 8: Measure The Compounding, And Maintain It Loop Archetypes You Can Build Today The Advanced Layer: The Reuse Flywheel Your Week-One Checklist CATEGORY Tutorials PUBLISHED July 9, 2026 READ TIME 18 min Most people build agents like goldfish. Every run starts the same way: the agent gets a goal, gathers context from scratch, reasons forward, takes a few actions and somewhere around tool call thirty, it starts forgetting what it already did. It re-runs a finished step. It contradicts a decision it made at the top of the run. And when the task ends, the entire hard-won trace of what worked and what failed evaporates. Tomorrow the same agent wakes up knowing nothing and walks into the exact same wall it hit yesterday. That is not an agent. That is a very expensive way to start from zero, forever. Memory fixes this, and almost nobody sets it up correctly. Most people bolt a vector store onto their agent, dump raw transcripts into it, and wonder why the loop still breaks and still doesn&\#x27;t get any smarter. This is the practical edition of that course — every principle followed immediately by the exact memanto commands that implement it, so you finish with a working memory architecture and not just a mental model. Two goals, in order. First, make your loop work — survive long runs without rotting or blowing your token budget. Second, make your loop sharpen — reuse what it learned so every run starts smarter than the last. “ Within the loop, memory is what makes your agent functional. Across loops, memory is what makes your agent get better. Most people accidentally solve neither, because they never separated the two. What Agentic Memory Actually Is Strip away the marketing and agent memory is not one thing. It&\#x27;s four, operating on two different clocks. Getting this taxonomy straight is most of the battle, because almost every memory mistake comes from treating all of it as one undifferentiated bucket. Working memory is the live context window — the agent&\#x27;s RAM, the scratch space for the step it&\#x27;s on right now. Fast, small, and where rot happens. Episodic memory is specific past events. "Last Tuesday&\#x27;s deploy failed because the migration ran before the feature flag flipped." Individual runs, with their outcomes. Semantic memory is distilled, durable facts and preferences. "The payments service requires idempotency keys." "This client hates em-dashes." Timeless t...

**来源信息**
- **来源**：Hacker News：AI 热帖
- **分类**：tip
- **发布时间**：2026-09-12 09:25（北京时间）
- **原文**：[打开原文](https://memanto.ai/blog/agentic-memory-course-keep-loops-alive)