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Every scheduled run starts its own chat, with outputs saved into the matching workspace so you can keep working from there.

A lot of automation tools leave you with a disconnected result and no easy path to revise it. Here, every run opens a fresh chat in context, so you can follow up, rework the output, and keep iterating right where it happened.

I didn’t have time to prepare, and the AI had already done it for me. Some of the best questions came from that prep.

It first evaluates whether the task is worth automating, then gives you the final say. If you have an interview in ten minutes, it can prepare a quick-use brief, scorecard, and note template before you even start. That feels less like a timer and more like an operator with judgment.

Finished automations can notify you in multiple ways, including chat tools, desktop notifications, and sound.

If an automation finishes early in the morning or late at night, you don’t have to keep checking whether it worked. You can see it on launch, sync it to team messaging, get a system notification, and even hear an audio cue. That peace of mind matters for people who set things in motion and walk away.

Scheduled agent runs can save directly into the folder you chose on your computer.

Automation doesn’t end as a one-off alert. The output lands in the folder structure you already use: a daily HTML report, a dated folder, or a nested archive when the task produces a lot. Even when you don’t look right away, it still ends up organized and traceable.

No copy-paste. The folder and the chat stay connected, and the file appears with a usable name.

When something is done, it can save directly into your current folder and name the file automatically. That removes a whole chain of small chores: copy, save, choose a directory, think of a filename. Want a safer iteration? Have it save as V2 and keep going.

I just described what I wanted and pointed out what felt wrong. The AI kept fixing it. That was when “everything is a file” finally clicked.

The thrill is not just that it can write code. It’s that the process stays visible, and the outputs are real files you can touch in your own folder. Even non-technical users can describe the goal in plain language, critique the result, and watch the app come together.

Dragging a folder into chat feels much more direct than opening a picker and hunting for it. Skills work the same way.

This becomes one of those tiny high-frequency moves you stop thinking about. Files, folders, and skills can be dropped straight into the conversation, which removes extra steps and makes the whole flow feel more physical.

Drop a folder and it inspects the contents. Drop a file and it reads it. Drop webpage text and it can turn into a Markdown file.

The input behavior adapts to what you give it: a folder means inspect its contents, a file means read it, text means use it as context, web snippets can become Markdown, and skills can load on the spot. You stop copying long paths around just to explain where things are.

Double-click a Markdown file and the left sidebar becomes the real file tree for that directory.

Open a document and the sidebar switches to the real folder it lives in. Browse the structure, switch files, and keep writing in one view, with grid or list layouts and eight ways to group what you see.

Folder tabs can sit side by side, and you can select files from different directories in one pass.

Open folder tabs side by side—up to eight panels at once—then select files across different directories and hand them to the AI together. Scattered source material no longer has to be reorganized before the work can begin.

Click once to preview. Markdown can be edited directly, and other formats can still be modified through natural-language instructions.

Images, audio, video, PDF, Office files, HTML, EPUB, and fonts can all be previewed inline. Markdown and code stay editable in the same environment, which replaces a whole stack of one-purpose preview tools.

Copy some text or drag in a file from the menu bar, and it becomes a Floatboat entry point.

You do not have to reopen the main window. Copy a passage or drop a file into the menu-bar Memo, and it is handed directly to Floatboat. It can suggest a fitting workflow and start it from there, catching the task the moment it appears.

A folder on the left, a browser in the middle, and chat on the right all stay visible and connected.

When those three surfaces stay open together, the agent can infer a lot from the way your workspace is arranged. The context becomes “what’s on your desk right now,” not another long explanation of which file or page you meant.

The browser can inherit your Chrome sign-in state, so when it visits a page it can often do so as you.

Floatboat can import browser state from Chrome, Edge, or Firefox, and workspaces can share that identity when needed. That helps it access the back-office tools, paid sites, and internal pages you already use—subject to the site, your permissions, and the workflow involved.

Drop in the link, say what you want done, and it can browse, extract, and organize from inside the built-in browser.

Instead of manually scraping a page and then pasting it into a model, you can often treat the link itself as the start of the task. The browser opens it, pulls what matters, and keeps moving into writing, analysis, or action.

AGENTS.md appears throughout the workspace, making each improvement to that memory explicit.

The memory is not trapped in a black box on someone else’s server. It can be written into AGENTS.md inside your folders, so the working preference stays visible, editable, and portable. Your memory remains yours.

Different agent spaces can remember different states, so reopening the app doesn’t mean starting from zero.

Each space stays separated, so work and life—or one project and another—don’t bleed into each other. Sessions persist, and coming back later feels like returning to a desk you never had to clean off.

In terminal-only tools, history often disappears behind commands and hidden logs.

Floatboat gives you a task overview where all chat history stays visible and browsable. Even if you’ve moved through many spaces, the old work is still there as something you can actually find and inspect.

Once the chat history gets large, the task overview becomes the easiest way to search across spaces and jump right back in.

As your history grows, the overview becomes a rescue tool: search across workspaces, find the right thread, and reopen it directly. The backlog gets larger without becoming unusable.

I often turn a successful run into a reusable skill.

This is one of the most concrete forms of accumulated experience: turn a proven run into a reusable skill or workflow and bring it back with one click later. That can be personal, shared, or refined with help from the product team.

IACT can nudge me into the right process, especially on longer tasks where structure matters.

You don’t need to be a prompt engineer. Floatboat can turn the next likely move into an inline action anchor, so the workflow itself helps you stay on a stronger path when the problem is still vague.

Load the vault directly, skip the plugin maze, and let the agent become the AI layer.

For heavy Obsidian users, the hook is simple: connect the vault and let the AI read, organize, and edit your knowledge base without rebuilding your workflow around a fragile plugin stack.

As you type in chat, related skills can appear automatically, and @ commands can search for the right one.

Chat is the central surface where many actions meet: editing files, creating new workflows, syncing to messaging tools, or switching models. The system can surface a fitting skill while you’re still describing the task.

It’s easier to experiment here because the browser and folder are already set up to receive the work.

No environment setup. No need to decide where the results should live before you begin. The idea appears, the folder and browser take the context, and it becomes much easier to try the small experiments that usually get postponed.

A skill only loads when you bring it in. That keeps irrelevant capabilities out of the context until you need them.

Load a connected workflow only when it is needed, keeping unrelated capabilities out of the working context. In one real use case, hundreds of image-and-text entries were structured and written into a Lark Base table—with the proven method saved for the next run.

Use the Floatboat agent from the places people already message: chat tools, work tools, and team channels.

Mention it in the team environment you already live in, and the same private agent—with memory, skills, and file access—can show up there to help. That closes the gap between “I’m on my phone” and “the work is still on my computer.”

Link-style access can place an agent into group conversation, and some workflows can be scheduled to appear on a cadence.

That means a configured agent doesn’t have to remain personal. You can place it where a team works together, so recurring tasks happen around one shared operating surface instead of scattered individual prompts.