# How to build a retrieval system for agents

DevFeed: [How to build a retrieval system for agents](<https://devfeed.tech/articles/how-to-build-a-retrieval-system-for-agents-5963.md>)

Original publisher: [Read original article](<https://turso.tech/blog/how-to-build-a-retrieval-system-for-agents>)

Author: Glauber Costa

Published: 2026-02-20T00:00:00Z

Content type: tutorial

Language: en

Sources: [Turso Blog](<https://devfeed.tech/sources/turso-blog.md>)

Topics: [AI search](<https://devfeed.tech/topics/ai-search.md>), [Turso](<https://devfeed.tech/topics/turso.md>), [ai-coding](<https://devfeed.tech/topics/ai-coding.md>), [Database](<https://devfeed.tech/topics/database.md>), [SQLite](<https://devfeed.tech/topics/sqlite.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [coding](<https://devfeed.tech/topics/coding.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [database](<https://devfeed.tech/tags/database.md>), [embedded](<https://devfeed.tech/tags/embedded.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [local](<https://devfeed.tech/tags/local.md>), [memory](<https://devfeed.tech/tags/memory.md>), [retrieval](<https://devfeed.tech/tags/retrieval.md>), [search](<https://devfeed.tech/tags/search.md>), [sqlite](<https://devfeed.tech/tags/sqlite.md>), [turso](<https://devfeed.tech/tags/turso.md>)

## AI overview

This tutorial presents Memelord, a fully local memory system for coding agents. It uses per-project SQLite databases powered by Turso, local embeddings, and vector similarity search to retrieve relevant memories across sessions. Memory usefulness is tracked through feedback, weighting, time decay, promotion, demotion, and deletion.

## Source excerpt

Build a local retrieval system for coding agents using Turso vector search. Memories rank by usefulness, decay over time, and persist across sessions.