Inside Fluent: Why the Future of Mac AI Isn’t a Chatbot—An Interview with Developer Vadim

Most AI tools require constant copying and pasting between windows, creating a “context-switching tax” that slows you down. In our recent review of Fluent, we found a native solution that lives inside every Mac app via a Spotlight-style interface. To learn more about the philosophy behind the app, we sat down with its developer, Vadim Ermolin, to discuss his vision for a truly autonomous AI assistant on macOS.

TheSweetBits: Fluent feels different from many AI assistants because it focuses on system-wide integration rather than a standalone chat interface. What inspired you to build it?

Vadim: “Definitely, Fluent is quite different from the majority of chatbot AI apps. The initial idea was to create a quick companion that is accessible anywhere to help with text refinement.

I’m a big fan of Spotlight-style apps, specifically Alfred, which inspired me to build a quick access layer to AI. The Spotlight-style concept makes interaction with AI very seamless and performant, as you don’t have to switch the context from the work you do – which is actually very expensive for the brain!

Once you’re used to the way Fluent works, you would never want to get back to a fully-fledged AI app, because you finally feel the ease and simplicity of having AI answer your questions, or running your tasks, with a single shortcut anywhere on your Mac.”

Fluent works inside any Mac app with contextual awareness and shortcuts. How do you see Fluent redefining what an AI assistant should look like on macOS?

“I think the deeper context awareness and autonomous capability is the way to go.

Currently, Fluent has a great UX for simple & quick context selection, like apps or browser tabs, as well as documents and picture. You just call the Smart Panel and accumulate it all in a few clicks. Fluent also has Scheduled actions, which allow for independent, scheduled background tasks execution.

However, the perfect AI assistant I imagine of – is able to “see” and attach all that context intelligently and automatically. It also constantly learns and accumulates data in the background (of course, locally and securely). It is always aware of your yesterday’s and today’s important Emails, Calendar events, messages from your beloved ones, your location, and so on. Being autonomous is the key.

Such an AI assistant can proactively suggest tasks you need to do, run them in the background, and this is where you start to call it an assistant – like a real human, it would do the work by itself correctly, you don’t have to push it or correct it every time something gets wrong.”

One of Fluent’s most interesting capabilities is custom Actions with shortcuts and variables, which can turn prompts into repeatable workflows. What are some of the most creative or surprising ways you’ve seen users build Actions with Fluent?

“Some of the most powerful workflows users shared involve automating their replies on social media or email.

One user created an action with a simple prompt that pulled his LinkedIn example messages from Memory, assigned a shortcut, and enabled Auto Insert. With automatic app context enabled, he went straight to generating comments on various posts.

AI was basically ghostwriting for him, giving him valuable ideas that he could refine and edit. He expressed higher engagenement and reach to his social media profile overall, because his comments were always valuable and creative, not plain AI-generated. Not to mention how much time he saved on communication that is now almost entirely automated.”

Fluent supports hundreds of models across providers, including local MLX models. Why was it important to build Fluent around a model-agnostic approach rather than locking users into a single AI provider?

“BYOK and the ability to use local models is a very appealing setup. Many users prefer using different models for different tasks. They can also control their costs better this way and eventually use LLMs for free, as local models are becoming more prominent—especially with the latest releases and ever-increasing AI performance on Apple Silicon.

Model-agnostic Memory in Fluent allows for switching and using any model with the same knowledge, which is a game-changer for users who were previously locked into a specific provider.”

Recent versions introduced Model Context Protocol & Retrieval Augmented Generation. For users who aren’t developers, why should they care about MCP & RAG, and how do you see it changing their daily workflow?

“MCP & RAG enable more powerful actions and knowledge-aware tasks.

With MCP, users can connect thousands of external services and apps—like Telegram, WhatsApp, Obsidian, even Blender or Sketch—to Fluent to help run tasks and process data.

On the other hand, Memory (RAG) allows for organizing your own personal knowledge library or research materials for further AI processing. Users find this surprisingly appealing because once you’ve loaded your reports or blog posts into Fluent, it becomes the ultimate reference tool for your daily work.”

Fluent seems optimized for Mac power users rather than absolute beginners. What trade-offs have you made between power and simplicity in the product?

“While Fluent was initially aimed at power users, our goal is to make it simple for anyone. We are constantly working on user-friendly improvements, especially regarding context features and MCP setup.

Interestingly, many of our users don’t consider themselves ‘power users.’  They value Fluent for speed, UX, and intuitive simplicity. Regarding trade-offs, we put a lot of effort into keeping advanced capabilities ‘hidden’ so normal users aren’t overwhelmed, while power users can easily access the tools they need.”

You’ve moved very quickly from version 1.1 to 1.7. What is the “North Star” for Fluent for the rest of 2026?

“Making Fluent ‘the ultimate AI agent’ that assists the user autonomously is the North Star for this year. The idea of AI agents working on your tasks while you’re away is absolutely fantastic. While Fluent can already do some of this, we are still pushing toward our full vision of what an autonomous assistant should be. Stay tuned, and thank you for your brilliant questions!”

Final Words

We want to thank Vadim for sharing these valuable insights. His vision for Fluent goes beyond simple chat; he is building toward a future of autonomous AI agents that handle complex research and tasks in the background while you focus on the work that matters.

With its rapid evolution and commitment to native performance, Fluent is carving out a unique space for Mac users—which is why we recently mentioned it as one of the Mac apps that make your life and work easier. You can explore the latest features and follow the development roadmap at fluentmac.app.

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