Building Memory in Multi-Agent Systems: New Chapter Explores Core Mechanisms
_nerdai_ · x · 2026-08-05
Chapter 7 of Build a Multi-Agent System (From Scratch) is now live. The author notes that unlike MCP tools or skills, there is no standard protocol or consensus on what constitutes memory for an agent.
The author defines memory strictly as what an agent learns from its own past task executions. This chapter introduces several core components:
- Episode: Captures completed task executions.
- BaseMemoryStore: A common interface across different storage backends.
- Memory: Recalls past episodes and records new ones.
- Three memory recipes: Recency-based, similarity-based, and reflective memory (inspired by the Reflexion paper).
Upcoming chapters will cover Human-in-the-Loop (HITL) and assembling multi-agent systems using subagents.
More from coding & agent
- Cerebras Brings World's Fastest AI Inference to Lovable — AlexandrePesant · 2026-08-05
- Google Open-Sources Gemini API Skills, Boosting Agent Code Generation to 96% — patloeber · 2026-08-05
- Malicious GitHub Repo Disguised as Crypto Exploit Exposed via LLM-Assisted Review — RSync25 · 2026-08-05
- AI Agents Automate Competitor Analysis and Influencer Marketing Strategy — fekdaoui · 2026-08-05
- Opinion: AI Coding is Manageable, but AI Workflows Risk Becoming Slop Without QA — oran_ge · 2026-08-05
- /human-review: Give AI Feedback Like Editing a Google Doc — petergyang · 2026-08-05