WhatIsanAgenticBrowser?

An agentic browser is a web browser that can do work, not just show you pages. It reads what's on screen, operates tabs, uses the apps you're already logged into, and completes multi-step tasks - research a list of companies into a spreadsheet, prep a meeting brief, triage a support inbox - while you do something else.

That's the short version. This guide answers the longer questions: what makes a browser "agentic," how it differs from a normal browser and a chatbot, how the pieces work under the hood, and where the idea still falls short.

The short answer

A normal browser is a window: you do all the clicking, reading, and typing. A chatbot is a conversation: it answers, but it can't touch your tabs or your tools. An agentic browser sits between them and adds the missing piece - it can act. It observes a page, plans a few steps, takes them (click, type, extract, call an app), and remembers enough to do it again next week. The honest verdict: for one-off answers you don't need one, but for work that spans tabs, apps, and live sources, it removes the part where you become the copy-paste machine between AI and your real tools.

Where a normal browser and a chatbot still win

Being fair about this matters, because an agentic browser is not the right tool for everything.

A normal browser wins on speed and control

If you just want to read an article, check a score, or fill in one form you know by heart, a plain browser is faster. There's no agent deciding anything, no waiting for a plan, no review step. You're in full control of every click, and for simple, fast, manual tasks that control is the feature, not the friction.

A chatbot wins when the work lives in the conversation

If the whole task is contained in text - rewrite this paragraph, explain this concept, brainstorm names, summarize something you pasted in - a chatbot is often the cleaner tool. It's quick, it's cheap, and there are no tabs or accounts to coordinate. Asking an agent to spin up a browser session for a job that's really just "give me a better sentence" is overkill.

Both win on predictability

The web is messy, so acting on it means an agent can misread a page or take a path you wouldn't. When the cost of a wrong action is high and the task is trivial, the simpler tool is the safer one.

Where Strawberry wins

Strawberry is a browser with built-in AI where agents do real work across your actual tabs and connected apps. Here's where that changes the math.

It works where your context already lives

Most knowledge work is already in the browser - CRM, LinkedIn, Gmail, Sheets, analytics, dashboards, internal admin panels. A chatbot makes you move that context into a chat and move the output back out. Strawberry runs inside the browser you're logged into, so it can read the live page and act on the same accounts you use. No exporting, no pasting, no re-describing what's on your screen.

It finishes multi-step work, not just answers

A real example: "research these 20 companies and build me a sheet with funding, headcount, and a one-line summary each." Strawberry opens the sources, extracts the facts, and writes the rows. Another: read a calendar invite, look up the attendee and their company's recent news, and hand back a one-page brief. Another: scan a support inbox, group the recurring bugs, and draft replies for review. These aren't single answers - they're finished outputs.

It remembers and repeats

Companions are persistent AI teammates that keep your preferences and project context between sessions. Skills are saved workflows, so a process you set up once can run again with one line. Routines run those skills on a schedule - briefs prepped overnight, a competitor-changes summary every Monday. With Team share, one bill covers shared companions and skills across your team, so the workflow one person builds, everyone runs.

It's measurably good at the acting part

Strawberry scores around 78% on GAIA, a benchmark for real-world agent tasks - the top result among downloadable agentic browsers, and ahead of Comet and Atlas on real-world benchmarks. That's the hard part of being agentic: not talking about the work, but actually completing it on a live, messy web.

How it actually works

Under the term, an agentic browser is doing four things in a loop.

Page context

It reads the structure of the page you're on - text, tables, forms, links, navigation - so it understands what's in front of it, not just a screenshot. That's how it can pull the right rows out of a table or find the actual "next" button instead of guessing.

Actions

It can click, type, scroll, navigate, and extract, the same way you would. This is the line between an assistant and an agent: without the ability to act, it's just a smarter sidebar.

Apps and MCP

Beyond the page, it connects to the tools you use - Gmail, Calendar, Sheets, Slack, your CRM - and to other systems through MCP, an open standard for plugging tools into AI. So it can both operate a website and update a record in an app, in the same workflow. See the MCP integration guide for how that wiring works.

Companions, skills, and routines

The loop above runs inside a companion that remembers context, can be saved as a skill, and scheduled as a routine. That's what turns a clever one-off into something repeatable and shareable.

The practical way to decide if you need one: if your task is "answer a question" or "do one quick manual thing," a chatbot or a normal browser is fine. If your task ends in a CSV, an updated record, a sourced brief, or a workflow you'll want again next week, that's agentic-browser territory.

Keep going

• browser agents vs chatbots - the clearest side-by-side on why acting beats answering for real work.
• MCP integration guide - how the browser connects to your apps and tools through the open MCP standard.
• getting started - the fastest way to run your first agentic workflow in Strawberry.