Slowave

Living memory layer across your AI tools.

AI agents have large context windows, but that context ends with your current session. Open a new session, switch from Claude Code to Codex, and you have to restate the same decisions, constraints, and failed attempts.

Slowave gives your agents one local, shared memory, without requiring a separate LLM for memory maintenance.

Slowave is designed as an adaptive memory layer rather than a static retrieval or summarisation system; it approaches agent memory from a different angle:

An effective memory system should help an agent achieve its goals.

Agent memory is not only a retrieval problem. A useful memory system should retain what helps the agent, weaken what does not, and continuously adapt based on use.

Slowave addresses this with a continuous feedback loop between your agent and its memory:

remember → recall → use → feedback → reinforce / weaken → decay

Slowave adapts the salience of stored memories based on your agent's feedback.

Over time, your agent’s feedback shapes what Slowave returns without needing a separate LLM judge inside the memory layer.

Memory becomes something continuously shaped by use rather than a static collection of facts waiting to be retrieved.

• Keep context across tasks: Your agents can reuse recorded decisions, preferences, constraints, and lessons instead of making you repeat them.
• Improves with use: Useful memories strengthen, irrelevant ones lose priority, stale knowledge can be suppressed or superseded.
• Learns from experience: Decisions, outcomes, and multi-step solutions can become reusable memories and procedures.
• Runs locally: Slowave stores memory in SQLite and does not send it to a hosted memory service.
• No LLM API key: The memory core performs maintenance and retrieval without LLM calls or an LLM API key.
• Inspectable: Review memories, retrievals, feedback, procedures, and system activity in the local dashboard.

The first useful payoff is simply not having to repeat the same constraint in the next task.

Over time, the way you work becomes reusable context for your agent.

Supported integrations:

• Claude Code
• Codex
• Cursor
• Cline
• Windsurf / Devin Desktop
• OpenCode
• Claude Desktop

See platform coverage and manual steps.

Installation

Quick start

pipx install slowave
slowave setup --dry-run
slowave setup

The quick start configures every detected client. To configure just one client at a time, see the installation reference.

To remove Slowave, see the removal guide.

What changes in your workflow?

Slowave is transparent to your work.

You keep working with your agent as usual.

When your agent encounters a durable fact or decision, the installed lifecycle directs it to preserve that claim.

On a later task, Slowave can return a compact, scoped set of relevant recorded memories to your agent, so that it can act upon its own memories.

What you will see while working with your agent:

• your agent activating Slowave for the current task and goal,
• Slowave retrieving relevant context to your agent,
• your agent sending feedback to Slowave on what was retrieved.
• your agent committing a Slowave session.

Optionally you will see:

• your agent invoking Slowave to remember durable facts.
• your agent invoking Slowave to recall something critical for the current task or goal.

Slowave does not decide whether a claim is true or important. Your agent makes that judgment and reports whether retrieved memory helped, was irrelevant, or became stale. Slowave maintains the resulting local memory.

Dashboard

Start the local dashboard with:

slowave dashboard

Open the dashboard in your browser, where you can inspect: