Show HN: The Control and Memory Layer for AI Agents

We launched OpenSink after building AI Agents and noticing some painful patterns: the agents are doing work and it ends up somewhere in Slack, Email, or gets lost. If you use multiple platforms, the agents are scattered around, you can't make changes to them without redeploying and you have low to no visibility regarding what they do. Here are the building blocks: Memory (via Sinks): persistent and searchable memory for agents, that survives restarts. Sessions: see what an agent did during a run, with a structured timeline. Input Requests: the agent asks for human input, waits for a response, and continues the execution. Used to build human-in-the-loop agents with low effort. Configurations: Easily tweak your agent configuration without redeploying the code.

Works with any AI agent platform, or custom code. Launching with docs, examples, and two open-source OpenClaw skills for Memory and Activities.

Website: https://opensink.com Docs: https://docs.opensink.com

Any feedback is valuable at this point, and thank you for reading so far ^^