Retain the right context
Study persistent memory when a workflow needs information from earlier sessions, with a way to correct or retire it.
Use Hermes Agent as a reference for workflows that continue across sessions. Study how memory, procedural Skills, tool connections, and scheduling can help organize reusable task knowledge and recurring work in your own environment.
Hermes Agent is an open-source agent system from Nous Research. Its official documentation brings together persistent memory, reusable Skills, tools, context files, and scheduling. These capabilities place it in the category of an independent agent application rather than a single prompt or Skill.
The value for a Floatboat user is in deciding what a continuing workflow needs to retain: facts, preferences, decisions, or a procedure. Hermes provides a reference for separating those concerns and combining them with tools and schedules. The design still needs task-specific review and an independently verified integration path.
Hermes also documents MCP integrations, execution controls, and scheduled tasks. Each connected tool or delivery channel adds its own setup and permissions. The MIT license covers the source, while models, remote systems, and hosted services remain separate choices.
Understand what the project demonstrates, then decide which mechanism addresses a real gap in your own workflow.
Study persistent memory when a workflow needs information from earlier sessions, with a way to correct or retire it.
Use procedural Skills as a reference for storing how a task should be done separately from facts about a particular user or project.
Evaluate how recurring work should receive context, use tools, and deliver a result at a planned time.
Use these scenarios as design references for work organized in Floatboat. Any software integration needs its own compatibility and permission checks.
Design how a repeated research task obtains fresh inputs while retaining its scope, sources, and output requirements.
Turn an established procedure into reviewed task knowledge, with an owner and a way to update outdated assumptions.
Identify the minimal decisions and evidence a later session needs instead of preserving an entire conversation without structure.
Start with a task and a small testable change, whether that means better instructions, a new tool connection, or a runtime component.
Separate temporary context, durable facts, decisions, and procedures before adding a memory mechanism.
Give stored knowledge an update process and recurring tasks an explicit schedule, output destination, and failure path.
Check whether the workflow stays accurate as inputs change, rather than judging it from one successful run.
Compare independent agents through their interfaces, extension models, and approach to carrying work forward.