Macro AI Review 2025: The 30-Year Document Problem, Solved?

What is Macro?

Macro is a secure document management system integrated with AI that combines several built-in tools into one workspace.

The core features of the platform are as follows:

By centralizing these functions and leveraging AI to develop an understanding of one’s sources, Macro aims to reduce the friction of switching between different apps, contributing toward more efficiency.

If Macro works as advertised, it’s not just saving time—it’s changing the nature of knowledge work itself.

The bottleneck shifts from finding and processing information to asking the right questions and making creative connections.

That’s the promise, anyway.

Whether it delivers is what we’ll explore in this review.

Getting Started with Macro

Signing up for new software always reveals something about the product. The onboarding flow is like a handshake—it tells you a lot about what’s to come.

I went to Macro’s homepage and clicked the sign-up button. They offer the standard Google and Apple authentication options, plus email if you prefer.

After signing up, you land on the dashboard.

I wanted to test the full capabilities, so I navigated to Settings (bottom left corner) and then Subscription.

The 7-day free trial of Macro Pro seems generous enough to evaluate whether Macro actually delivers on its promises.

When you click “Start Free Trial,” you’re taken to a Stripe checkout page. This is where most people would just proceed, but there’s an “Add promotion code” option that’s easy to miss.

Use my exclusive coupon code “DZ10” for a 10% discount.

There’s no lengthy tutorial and no annoying coach marks pointing at every feature.

Macro seems to trust that you’ll figure it out, or that the interface is intuitive enough that you won’t need to.

Interface and user experience

Macro’s dashboard is minimalist. Almost zen-like.

There’s a file browser on the left, a central workspace, and a prompt to create something new.

That’s it.

What’s surprising is what’s missing. There are no flashy demos, no animated tutorials showing you where to click.

Just a simple suggestion to type ⌘K to search.

Macro assumes you’re smart enough to figure it out.

The creation options reveal Macro’s true ambitions. Each option pairs a traditional document function with AI augmentation:

The pattern becomes clear.

Macro isn’t trying to replace your existing workflow, it’s trying to reduce the friction within it.

The most valuable thing about Macro’s interface is what it doesn’t do: it doesn’t make you think about the interface itself.

Of course, the real test isn’t how it looks, but how it works. Interfaces are promises.

Does Macro keep its promises?

That’s what we need to find out.

How effective is Macro’s AI Chat?

The true test of any AI tool isn’t its promises but what happens when you press “Enter”.

Macro’s AI chat is accessible from two places: the dashboard itself or the plus icon in the top left corner.

Using it feels natural.

Type your prompt, attach documents if needed, select your AI model, choose your output format, and hit enter.

You can attach documents in three ways:

1. Click the attach icon and upload files
2. Press @ to reference documents you’ve already uploaded
3. Highlight text on the document and click AI Chat. The selected text (and document) will be attached to the chat

The available AI models tell you something about Macro’s approach:

Macro offers each of the state-of-the-art, foundational LLMs, including AI web search.

What’s more interesting is the structured output option:

This is where Macro starts to separate itself.

Most AI interfaces let you generate text. Some let you create images. Few integrate these outputs directly into a document workflow.

I decided to break the conventional wisdom about simple prompts and stress-tested the system with a complex request:

<prompt>

I’m planning a data analysis project on climate change trends over the past decade. Could you help me with the following:

– List the key factors affecting global temperature changes
– Create a table showing average temperature increases by continent
– Provide sample CSV data of monthly global temperatures for the last year

Please format each section appropriately to help me understand and potentially use these resources in my project. I want you to output a bulleted list, a table, and a CSV format.

</prompt>

The results were surprising.

Macro didn’t just generate each output—it formatted them correctly and made them immediately usable.

Text generation was nearly instant.

Clicking the notes option converted the entire chat into an editable markdown file.

This ability to seamlessly move from generation to use is subtle but powerful.

The traditional workflow goes: generate content in an AI tool → copy → paste into another tool → format → use.

Each step introduces friction and opportunities for error.

Macro collapses this into: generate → use.

There’s also a lightning icon beside the attachment button that lets you save frequently used prompts as templates.

However, it is mot merely a prompt saver. The purpose of that feature is to automate workflows (or “prompt chaining”).

LLMs are much more reliable when the prompt focuses on one task at a time, so it’s an easy and an efficient method to stitch common prompts together, step-by-step.

The text output from Macro’s AI is accurate, the diagrams are clear, and the Python code works.

Can Macro really help you speed read PDFs with AI?

The PDF is an archaic format.

Designed in 1993, it’s a fossil from an era when documents were meant to be printed. Yet we still use PDFs everywhere.

They’re the lingua franca of formal knowledge.

The real test of Macro is whether it can make this ancient format work better for us.

I uploaded a 97-page document on “HOME HYDROPONICS FOR LEAFY GREENS” to find out.

The first thing that strikes you about Macro’s PDF reader is what’s missing. No cluttered toolbars. No tiny icons with cryptic functions. Just the document front and center.

This reflects a deeper philosophy: tools should disappear when you’re using them, as I also repeat. The best hammer is the one you forget you’re holding.

The primary interactions are simple. You can add text, signatures, and comments.

You can even use “@” to tag someone in the comment, insert tabs to navigate (i.e. return to where you left off, or leave yourself a reminder).

When you click “AI Notes,” something unexpected happens. The system begins digesting the entire document and creating structured notes (in a new markdown file) in the sidebar.

The notes are hierarchical, with clear headings and concise bullet points. The structure emerges naturally from the content.

This inverts the traditional reading process. Instead of you extracting structure from the document, the AI does it for you.

The “AI Chat” feature takes this further. You can ask questions about the document, and Macro answers based on the content.

There’s a profound shift happening here.

Reading has traditionally been linear—you start at the beginning and work through to the end. Macro makes the process more personalized, similar to a research companion.

When information becomes accessible through questions rather than page numbers, you interact with documents differently.

Selecting any text reveals another layer of functionality: you can ask the AI about specific passages, get explanations, translate text, highlight, or comment.

The most interesting option is “Share.” It generates a link to that specific passage, not just the page, but the exact selection.

You can also share the file via a private link, where the privacy setting can be adjusted. For instance, you can set it as a public link, or share with specific individuals (Keyboard shortcut: Command + S).

This solves a problem as old as documents themselves: “Look at page 47, third paragraph.”

Now it’s just a link.

How powerful is Macro’s note-taking functionality?

So far, we have seen what Macro can do with its AI chat feature (including top AI LLMs available) and with your PDFs.

You might have noticed that it’s all interconnected.

Specifically, you might have seen that almost any kind of text generated using AI inside Macro can effortlessly be exported to a separate markdown file for advanced note-taking.

Now let’s see how note-taking from scratch works inside Macro.

To put simply, notes capture what seemed important at the moment you wrote them.

But traditional notes have a fatal flaw: they’re disconnected from their source.

When you review notes months later, the context is gone. You’re left with fragments that once made sense.

Macro’s approach is different.

The notes interface is simple. A blank page with formatting options at the top—nothing you haven’t seen before.

What makes it different is what’s underneath.

Notes in Macro are connected to their source documents. They know where they came from.

This changes everything.

When you create a note from a PDF, Macro preserves the connection. Click on a reference, and you’re taken to the exact passage.

The interface follows the same minimalist philosophy. No cluttered toolbars. No feature overload. Just a clean space for thinking.

Press ‘/’ for commands, ‘@’ to reference files, ‘space’ for AI writing.

Most note-taking apps are digital paper. Macro’s notes are alive.

The templates are telling. They’re not just formatting—they’re use cases:

Each represents a different type of knowledge work.

In my experience, Macro isn’t trying to be Roam or Obsidian. It’s not building a second brain.

It’s trying to make your first brain work better.

The most powerful feature isn’t obvious until you’ve used it for a while. Notes in Macro aren’t just static text—they’re queries.

When you write “@PDF.name” and ask a question, the note becomes an interface to the document.

This inverts the traditional relationship between notes and sources. Instead of notes summarizing sources, sources inform notes.

How good is Macro at generating and editing code?

Most AI tools can generate code, but few integrate it into a document workflow.

This distinction matters.

Macro supports Python, Rust, JavaScript, Go, React, SolidJS, C, C++, and VBA.

From the dashboard, you write your prompt, select an AI model, and choose your programming language.

I tested it with React.

My prompt asked for a personal finance dashboard with specific components: a summary section, interactive charts using Recharts, a filterable transactions list, and budget progress bars.

I included technical requirements like functional components, responsive design with Tailwind, and proper state management.

<prompt>

I need help creating an interactive dashboard for a personal finance tracker in React. The dashboard should include:

1. A summary section showing total income, expenses, and savings rate
2. An interactive chart visualizing monthly spending patterns using the Recharts library
3. A transactions list component with filtering and sorting capabilities
4. A budget progress component showing spending categories as progress bars

Technical requirements:
– Use functional components with React hooks
– Implement responsive design using Tailwind CSS
– Include proper state management for user interactions
– Add smooth transitions and animations for a polished feel
– Implement at least one custom hook for reusable functional­ity

Pleas­e provide clean, well-commented code with a component-based architecture. Explain any complex parts of the implementation and how the components interact with each other.

Also, include a sample data structure I can use to test the dashboard. I want you to output React code.

</prompt>

What happened next reveals something about where code generation tools are heading.

Macro didn’t just spew out code.

It organized it by component, with a coherent architecture. The code wasn’t perfect—AI-generated code never is—but it was surprisingly usable.

The real limitation is that you can’t run the code within Macro itself. You have to export it to an IDE for testing. This creates a boundary between generation and use that feels unnecessary.

But the output itself is robust.

And like everything else in Macro, you can edit the generated code in markdown notes, creating a kind of conversational programming experience.

I’d encourage you to try this with a language you know well.

For experienced developers, Macro might be most valuable not for generating new code but for editing and debugging existing code.

The ability to say “fix this function” or “optimize this algorithm” in natural language collapses the distance between intention and implementation.

That might be the more profound shift.

What can you create with Macro’s AI-powered canvas?

Ideas live in different forms. Some belong in text. Others need to be seen.

Macro’s canvas is where visual thinking happens. But it’s also where the boundary between thinking and drawing starts to blur.

The canvas interface is almost aggressively minimal. A blank slate with a subtle toolbar at the top.

The basic tools are what you’d expect: hand tool, zoom, move, rectangle, pencil, connector, text, and image.

Nothing revolutionary so far.

But notice what’s sitting alongside these traditional tools: an AI Chat button.

This changes everything.

The standard way to create a diagram is to start with a blank canvas and manually add each element. First, a box. Then another. Connect them. Add text. Resize. Align.

It’s tedious.

Macro inverts this. You can start with language.

Describing a flowchart in words is faster than drawing it. Especially if you’re not a designer.

When you use the AI Chat on Canvas, you’re essentially programming with natural language. The description becomes the diagram.

For example, I prompted the following (using Claude 3.7 Sonnet as an output model):

<prompt>

Create a flowchart diagram showing the process of making coffee using a drip coffee maker.

Please think through this step by step:

1. First, identify the 5-7 main steps in the coffee-making process
2. Then, explain the logical flow and any decision points
3. Finally, create a clear visual flowchart with:

– Rectangular boxes for actions/steps
– Diamond shapes for any decisions
– Arrows showing the flow direction
– Clear, concise labels for each step

After creating the diagram, briefly explain your design choices and why you organized the steps in that particular sequence.

</prompt>

Within seconds and some back and forth, it generated a complete diagram with proper structure, relationships, and visual hierarchy.

The surprising thing is that starting with language actually creates better diagrams than starting with shapes.

Why?

Because you think about the relationships first and the visual representation second. Which is the right order.

Of course, you can still use it the traditional way. The standard drawing tools work as expected.

You can create rectangles, use the pencil for freehand drawing, add connectors between elements, and insert text and images.

The formatting options are what you need, not more: colors, line weight, corner rounding, and font size.

But the canvas becomes most interesting when you combine traditional drawing with AI generation.

You can start with an AI-generated diagram, then modify it manually. Or start manually and ask the AI to extend or refine your work.

This creates a conversation between you and the tool. Less like using a pencil, more like collaborating with a designer who immediately understands what you’re trying to express.

The canvas also integrates with the rest of Macro’s ecosystem. You can reference documents using the @ symbol, pulling in content from PDFs or notes.

Canvas in Macro isn’t trying to replace specialized diagramming tools like Figma or Miro. It’s not for creating production-ready designs or facilitating collaborative whiteboarding sessions.

It’s for thinking.

For exploring ideas that don’t fit neatly into linear text.

For making connections visible.

How does Macro handle AI image generation and editing?

This is one of those features where the name suggests more than it delivers.

Macro doesn’t actually generate or edit images at all. What it does is let you upload images and then ask questions about them.

That’s it.

You can’t transform one image into another. You can’t tell Macro “make this logo blue” or “remove the background.”

When you upload an image, all you get back are words, not new images.

There is one exception: you can convert images into Canvas diagrams. But that’s a specialized use case most people won’t need.

I expected more. I assumed it would leverage ChatGPT’s image generation capabilities right inside the platform.

It doesn’t.

This feels like a missed opportunity. For a tool positioning itself as a complete AI document workspace, the ability to generate images would make documents richer and more expressive.

Text and diagrams are powerful, but sometimes you need an actual image.

It’s a curious limitation in an otherwise comprehensive system.

But again, not everyone would want a document management platform to generate new images.

So, I leave it up to you to decide whether this is a feature worth adding or something you would probably be better off without.

How much does Macro cost?

Macro offers three tiers: Free, Pro, and Enterprise.

The free version gives you access to advanced AI models but caps you at 25 documents.

Pro costs $20 per month.

You get unlimited storage and all features. It’s aimed at individuals who value their time. People who see documents as means, not ends.

The Enterprise tier doesn’t list pricing.

Macro’s three-tier approach follows a pattern we’ve seen succeed repeatedly in software:

The real question isn’t whether $20 is expensive. It’s whether the friction Macro removes from your document workflow is worth more than $20 a month to you.

That moment, when you hit document 26, is when you truly decide what your time is worth.