VEKTOR shipped v1.9.8, described as local-first memory for AI agents. The release adds ingestion of personal books and documents and more scrutiny of what an agent reads. The post is a Medium release note.
VEKTOR is a memory layer for LLM agents, updated in v1.9.4 with tool use in its Desk Chat interface and a reasoning upgrade to its Faraday component. It aims to give agents persistent, usable memory across conversations. Target users are developers building AI agents.
VEKTOR is a memory layer for LLM agents, updated in v1.9.4 with tool use in its Desk Chat interface and a reasoning upgrade to its Faraday component. It aims to give agents persistent, usable memory across conversations. Target users are developers building AI agents.
A fully local memory and retrieval engine that indexes personal files (PDFs, notes, screenshots, code) using embeddings and vector search. It solves the problem of finding information in personal files when the user cannot recall the filename or exact wording. The system runs entirely on-device, prioritizing privacy and offline capability.
A fully local memory and retrieval engine that indexes personal files (PDFs, notes, screenshots, code) using embeddings and vector search. It solves the problem of finding information in personal files when the user cannot recall the filename or exact wording. The system runs entirely on-device, prioritizing privacy and offline capability.
Friday is a self-hosted, open-source memory layer that lets AI coding agents like Cursor, Claude, and Copilot remember across sessions. It stores architecture decisions, schemas, and preferences via the Model Context Protocol. This solves the problem of coding assistants losing context between sessions.
Friday is a self-hosted, open-source memory layer that lets AI coding agents like Cursor, Claude, and Copilot remember across sessions. It stores architecture decisions, schemas, and preferences via the Model Context Protocol. This solves the problem of coding assistants losing context between sessions.
A developer launched Scribe, a command-line tool that constructs AI agent memory from code repositories and terminal sessions. The tool aims to help agents maintain context across interactions by ingesting local development data.
A developer launched Scribe, a command-line tool that constructs AI agent memory from code repositories and terminal sessions. The tool aims to help agents maintain context across interactions by ingesting local development data.
A local-first, review-first memory layer that lets coding agents pick up where they left off by storing facts, decisions, and state in a SQLite database with BM25 search. It solves the problem of long-running agent projects losing context or mixing state between projects, targeting developers building agentic coding workflows.
A local-first, review-first memory layer that lets coding agents pick up where they left off by storing facts, decisions, and state in a SQLite database with BM25 search. It solves the problem of long-running agent projects losing context or mixing state between projects, targeting developers building agentic coding workflows.