Clarifying Differences

Before we dive in, let's clear up some confusion: AI tools and AI agents are not the same thing.

AI tools are what most people use today—ChatGPT, Claude, Gemini. You ask a question, you get an answer. The AI responds to your input, but it doesn't do anything in the real world. It exchanges information with you. That's it.

AI agents are different. They don't just answer—they act. An agent can browse the web, click buttons, fill out forms, book flights, send emails, and execute multi-step tasks on your behalf. They plan, they take action, they observe results, and they adjust. The AI becomes your assistant, not just your search bar.

This is exactly why I'm so excited about Notion's Custom Agents. I've been testing them for a few months now, and I'm certain they're going to upend how teams work.

It's not just about incorporating AI into daily workflows—it's about having agents that actually feel like real team members. They understand your workspace, your projects, your context. That's a fundamentally different experience than copying and pasting into a chatbot.

This distinction matters because the study we're about to discuss focuses specifically on agents—AI that takes action in the real world.

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If you haven't used Perplexity yet, here's the quick version: it's an AI-powered search engine and browser that gives you direct answers instead of a list of blue links. You can choose your AI model, create focused project workspaces, and get cited, verifiable responses. It's especially strong for topical and recent information—the kind of thing traditional search engines struggle with.

The study focuses on Perplexity's new product called Comet—a browser with an embedded AI agent called Comet Assistant that can actually do things across the web on your behalf.

Harvard and Perplexity analyzed hundreds of millions of interactions with Comet to understand how people are actually using AI agents. Here's what they found.

57% of all AI agent use falls into just two categories—productivity and learning.

Productivity and workflow tasks account for 36% of all queries. That includes document editing, email management, spreadsheets, and coding. Learning and research comes in at 21%, covering courses and research assistance. Media and shopping round out the rest, but they're not even close.

For creators and knowledge workers, this is validation that AI agents are being used primarily as work amplifiers—not just novelty tools.

The most common individual tasks are exercise assistance, research summarization, document creation, and product search. People are delegating the grunt work that eats up their day.

The study found clear patterns in early adopters. Digital technology workers represent 28% of agent adopters. Academia, finance, marketing, and entrepreneurship collectively account for over 70% of adopters and queries. Countries with higher GDP per capita and education levels show stronger adoption.

Knowledge-intensive, digitally-native roles are leading the way. If you're a creator or consultant, you're already in the right demographic to benefit.

If you're trying to adopt AI or work more productively, the data points in a clear direction. Start with productivity tasks—document editing, email management, and research are the highest-value use cases right now. Use AI for learning too. My favorite hobby as of late is dumping docs and heavy files into Notebook LM and getting a podcast-like summary. Wild times!

Here's the real unlock from this data: the top tasks involve multi-step actions—search, analyze, create. Not one-off questions.

The most effective way to use AI (tools or agents) is to start by breaking out every step of a given workflow. Map out what you actually do when you write a newsletter, research a topic, or manage your inbox. Then identify the specific areas that could be augmented or accelerated using AI. Maybe it's the research phase. Maybe it's the first draft. Maybe it's reformatting the output.

Once you see your workflow in steps, you'll know exactly where AI fits—and where it doesn't. This is how you stop using AI as a gimmick and start using it as infrastructure.

Once you've identified where AI fits in your workflow, the next question is: how do you actually communicate with it?

A good prompt has a few key elements.

First, give context—tell the AI who you are, what you're working on, and why.

Second, be specific about the output you want—format, length, tone, audience.

Third, include constraints—what should it avoid, what's non-negotiable. And fourth, provide examples when possible—show it what good looks like.

The more precise your input, the less time you spend fixing the output. Think of prompts like creative briefs: the clearer you are upfront, the better the result.

The productivity gains from leveraging AI agents are real, and the early adopters are already building habits that will compound.

The question isn't whether to adopt AI agents. It's which workflows to start with.

If you want to see the original research, check out "The Adoption and Usage of AI Agents: Early Evidence from Perplexity" (Yang et al., December 2025).

And if you want help writing better prompts and instructions for AI, check out my AI Personalization Guide—a free Notion resource with templates and frameworks you can start using today.

Until next time,
Dave

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ps. if you’ve noticed a different look, it’s because we’ve moved to Beehiiv! Primarily to streamline publishing across different newsletters.