RESEARCH & ENGINEERING BLOG

Insights on AI Agent Memory, Postgres & Benchmarks.

Technical deep dives and architecture patterns on building production memory layers for AI agents. The evaluations are open and reproducible.

WHAT YOU'LL FIND HERE

  • Fundamentals: core concepts of agent memory.
  • Architecture: design patterns for building memory layers.
  • Benchmarks: open, reproducible evaluations and their results.
  • Engineering: running agent memory in production.
  • Research: new ideas and findings on agent memory.
FEATURED POST7 min read

Is a Vector Database Actually a Memory System?

Dropping your chat history into a vector database feels like giving an agent memory. What you actually get is fuzzy search over old messages. The gap between that and real memory is where production agents break.

LS
Laxman Sharma
Oct 12, 2026
FUNDAMENTALS · AI AGENT MEMORY

A vector database does similarity search over embeddings. That is a retrieval primitive, not a memory system. Here is what memory needs that it does not do alone.

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Fundamentals•Oct 12, 2026•7 min read

Is a Vector Database Actually a Memory System?

A vector database does similarity search over embeddings. That is a retrieval primitive, not a memory system. Here is what memory needs that it does not do alone.

#Vector Database#Memory#pgvector#AI Agents
Fundamentals•Sep 21, 2026•7 min read

RAG vs Memory: What Is the Actual Difference?

RAG and memory both feed text into the prompt, so they get confused. RAG grounds answers in shared documents; memory tracks what changes about one user over time.

#RAG#Memory#Retrieval#AI Agents
Fundamentals•Sep 11, 2026•6 min read

Why Do AI Agents Forget?

AI agents forget between sessions because language models are stateless. Here is why resending the chat transcript only works for a while, and what real memory takes.

#AI Agents#Memory#LLM Context#Fundamentals

PRODUCTION AI MEMORY ENGINE

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Bi-temporal facts, Postgres-native pgvector storage, and sub-50ms hybrid recall for enterprise agent workloads.

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