Show HN: Dreamer – Mine your agent sessions for corrections you keep repeating

Description and use

Here's a brief summary of the open-source project:

**Project Summary:** Dreamer is an open-source project that enables the mining of agent sessions for repeated corrections, allowing developers to leverage AI capabilities without building a model stack from scratch. This project is particularly useful for prototyping AI features, building Reinforcement Agent Graph (RAG) or agent workflows, and evaluating model tooling.

**Value:** The value proposition of Dreamer lies in its ability to add AI capability without the need for extensive model development, making it an ideal solution for proof-of-concepts, prototypes, or internal workflows.

**Practical Adoption Path:** To adopt Dreamer, developers should first manually inspect the project's metadata, as integration signals are sparse. This involves verifying the license, maintenance, documentation, issues, and release cadence to ensure the project's reliability and suitability for their needs. Once these checks are completed, developers can integrate Dreamer into their workflows.

**Production Readiness:** Dreamer is considered moderately production-ready, with a score of 45/100. While it can be useful for prototypes or internal workflows, developers should exercise caution before deploying it in production environments due to its limited quality signals and potential maintenance requirements.

Use in a workflow

Show HN: Dreamer – Mine your agent sessions for corrections you keep repeating helps add AI capability without starting from a blank model stack.

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Limitations and review notes

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.