This New AI Browser Just KILLED Comet & ChatGPT Atlas: A Deep Dive into Flowith

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AI browsers have evolved from clever search assistants to true automation platforms. Flowith is the latest entrant that moves beyond search and chat. It acts, executes, and automates multi-step workflows inside the browser—with hands-off execution, local privacy, and reusable skills. If you build content, run marketing campaigns, manage product research, or ship software, Flowith deserves attention.

Table of Contents

Why Flowith matters: the rise of agentic browsers

Traditional AI browsers and browser plugins let you ask questions, summarize pages, or generate content. Flowith shifts the paradigm by combining three capabilities that matter in production workflows:

  • Action — it controls the browser and desktop to click, type, download, and interact autonomously.
  • Reasoning — it performs multi-step planning, visual analysis, and deep web reasoning for higher-quality outcomes.
  • Execution — it runs end-to-end tasks, stores the steps as repeatable skills, and can run multiple agents at once.

That combination is what makes Flowith an agentic browser. Instead of just answering a question, it can go out, gather data, act on websites, and produce deliverables automatically.

This actually thinks, acts, and executes tasks that other browsers simply can’t.

Core features that set Flowith apart

Autonomous agents and multi-tasking

Flowith runs agents that can be started for specific goals and left to complete those goals while you continue working in other tabs. Agents show an action history, perform visual analysis on pages, and can operate in multiple modes:

  • Fast mode — prioritize speed, finish tasks quickly without relying on extended memory or skills.
  • Pro mode — prioritize accuracy and step-by-step reasoning, using both skills and memories for better outcomes.

Skills, memories, and presets

Instead of repeating manual steps each time, Flowith can learn routines and save them as reusable skills. It also stores memories that agents can reference during execution. Presets allow one-click automation for common workflows—everything from research templates to holiday shopping assistants.

Teach mode: record once, reuse forever

Teach mode lets you record a workflow by performing it once while Flowith observes and logs your actions. The system then converts that recording into a skill that can be replayed by an agent. Teach mode tracks cursor movement, clicks, and input fields in real time and produces a written skill description that you can edit and reuse.

Local-first privacy and storage

Flowith stores agent execution history, browsing history, memories, skills, and credentials locally on your device. Nothing gets synced to a cloud server by default. For anyone concerned about data privacy and local control, this design reduces attack surface and keeps sensitive automation on your machine.

How Flowith works in practice: three powerful use cases

The best way to evaluate an automation platform is by real workflows. Below are concrete examples that showcase the kinds of tasks Flowith can handle hands-free.

1. Large-scale data collection and job automation

Imagine needing a list of recent job postings across LinkedIn for outreach, hiring research, or market intelligence. Flowith can:

  1. Start an agent with a clear goal, for example find positions posted in the last month with a specific title.
  2. Navigate LinkedIn, crawl search results, and extract job title, company, and URL for each listing.
  3. Compile results into a clean, paginated web view or export as a file for downstream use.

This isn’t limited to a handful of results. Flowith has demonstrated crawling and compiling 100 positions across 50 unique companies and presenting those results as a browsable document—all without manual intervention. You can then add a follow-up agent to automatically apply, message recruiters, or create outreach campaigns.

2. Hands-off developer workflows: clone, run, and play

Developers and creators routinely copy repositories, build projects, and preview demos locally. Flowith can take over those repetitive tasks. Example workflow:

  1. Navigate to a GitHub repository, find the clone link or code button, and copy the URL.
  2. Open a terminal, run git clone, install dependencies, and start a local server or open an HTML file.
  3. Verify the project has launched and provide a browser preview so you can interact with it immediately.

All of that can happen with your hands off the keyboard. Flowith’s ability to control local terminals, detect successful loads, and surface the result in the browser turns time-consuming setup into a single command. For creators who demo interactive projects, this is a huge time saver.

3. Automated research, analysis, and content generation

Research tasks that once took hours can be compressed into minutes. Flowith can:

  • Scan Product Hunt or other feeds, identify the top products by popularity or category, and classify them.
  • Generate an executive summary, market position assessments, and product-by-product analysis.
  • Compile the results into a document, save it locally, and make it ready for sharing or publication.

This is not limited to product research. The same approach works for competitive intelligence, content ideation, trend analysis, and social listening. Agents can watch live streams, post comments, and interact in real time—useful for marketing experiments, audience engagement, or community moderation.

Presets and templates: plug-and-play automations

Flowith ships with a set of helpful presets for common tasks. A few examples:

  • TikTok hype preset — detects live streams that meet viewer thresholds, posts context-aware comments in the chat, and can keep participating in a live session.
  • Holiday overhaul — searches ecommerce sites, fills carts with curated gift bundles, and streamlines holiday shopping.
  • Research templates — gather top lists, categorize products, and produce formatted reports.

Presets are editable, so you can customize the logic, change thresholds, or add company-specific rules. Once you refine a preset, save it as a skill and reuse it across projects or team members.

Teach mode: turning expertise into reusable automation

Teach mode is where non-engineering users can capture repeatable processes without writing code. Use cases include:

  • Onboarding a new hire by recording a routine task like weekly reporting.
  • Capturing a sales outreach workflow to be run on multiple prospects.
  • Documenting internal QA flows so an agent can execute them across builds.

The flow is simple: Name the goal, start recording, perform the task while Flowith logs your clicks and inputs, and stop when done. Flowith then synthesizes the recording into a textual skill and a replayable automation. That skill can be run manually or scheduled, and it can use stored memories for personalization.

Security and privacy: how Flowith keeps data local

Automation that interacts with accounts, messages, or private dashboards requires trust. Flowith emphasizes local-first architecture:

  • Agent execution history, skills, memories, and credentials are stored locally.
  • No default cloud syncing of sensitive data reduces exposure to third-party servers.
  • Users remain in control of what to share—cloud integrations can be chosen explicitly.

For teams with strict compliance or individuals who want to avoid cloud storage of credentials, this design is a key differentiator.

Practical tips for getting the most from Flowith

  • Start small. Record a simple two- or three-step task in Teach mode to learn how Flowith interprets actions.
  • Use Pro mode for critical jobs. When accuracy matters, use Pro mode so agents leverage skills and memories for higher-quality reasoning.
  • Keep sensitive tasks local. If you’re automating credentialed actions, prefer local storage and explicitly opt into cloud sync only when necessary.
  • Build a skills library. As you accumulate reusable skills, you’ll compound productivity gains across projects and team members.
  • Monitor action history. Review the agent action history to validate steps and catch edge cases before running automations at scale.

Real-world outcomes and a surprising anecdote

People are already using Flowith for tasks that used to require manual supervision. Examples span job scraping, automated outreach, research reports, and even live stream participation. One reported anecdote involves an automated agent playing online poker and winning over $1,000 without human intervention. Whether for marketing experiments, developer setup, or revenue-generating automations, the ability to execute complex browser workflows autonomously opens new opportunities.

Suggested integrations and content to add on your site

To make this article more actionable, consider adding these assets:

  • Annotated screenshots of Teach mode recording a workflow. Alt text: Screenshot of Teach mode showing cursor tracking and recorded steps.
  • A short demo video of cloning a GitHub repo, running it locally, and previewing the demo. Alt text: Demo video showing Flowith cloning and running a repository automatically.
  • An infographic comparing Flowith, Comet, and ChatGPT Atlas across features like execution, local storage, and skills. Alt text: Feature comparison chart of AI browsers highlighting Flowith’s agentic capabilities.

Meta description and tags

Meta description: Flowith is a new agentic AI browser that automates web workflows, runs local-first agents, records teach mode skills, and outpaces Comet and ChatGPT Atlas.

Suggested tags:

  • Flowith
  • AI browser
  • automation
  • teach mode
  • local privacy
  • agentic AI

Internal and external linking recommendations

Internal links to include on a site could be pages on automation best practices, a product walkthrough, or a case study showing time saved by automations. External links to authoritative resources might include browser automation standards, GitHub documentation, and Product Hunt for product discovery context.

Call to action

Try Flowith at try.flowith.io to experience an agentic browser that executes workflows, learns routines, and keeps your data local. Build a skills library, automate repetitive tasks, and reclaim hours of manual work.

What is Flowith and how does it differ from other AI browsers?

Flowith is an agentic AI browser that not only answers questions but performs multi-step browser and desktop actions autonomously. It differs from other AI browsers by executing tasks, recording and replaying skills via Teach mode, supporting local storage for sensitive data, and running concurrent agents across tabs.

Is Flowith safe to use with private accounts and credentials?

Flowith stores agent history, skills, memories, and credentials locally by default. Nothing is synced to a cloud server unless you explicitly choose to integrate cloud services. This local-first approach reduces cloud exposure, but best practices still include limiting access and auditing agent actions for highly sensitive workflows.

Can Flowith automate interactions on dynamic sites like TikTok or live streams?

Yes. Flowith can navigate to live streams, monitor viewer thresholds, and post context-aware comments. Agents can also continuously observe a live stream and interact in real time, which makes it suitable for marketing experiments and audience engagement automation.

What is Teach mode and who should use it?

Teach mode records a user performing a task and converts those actions into a reusable automation skill. Non-technical users, operations teams, marketers, and developers can all use Teach mode to capture repeatable processes without writing code.

Can Flowith run terminal commands and interact with local files?

Yes. Flowith can interact with local terminals, clone repositories, open files, and run local servers as part of an automated workflow. That capability enables hands-off developer setups and instant previews of web projects.

How do I get started building skills in Flowith?

Start with Teach mode: define a goal, record yourself completing the task, stop the recording, and review the generated skill. Adjust the skill if needed and save it for future reuse. Try a simple workflow like copying text to a document first to learn how Flowith interprets actions.

Final thoughts

Flowith represents a shift from passive AI assistance to active, repeatable automation inside the browser. For creators, marketers, developers, and knowledge workers, the ability to record routines, run agents locally, and produce tangible deliverables without manual supervision is a productivity multiplier. The agentic approach—combining reasoning, action, and reuse—changes how we think about browser tooling. If you manage workflows that repeat, require coordination across sites, or involve complex multi-step tasks, Flowith is worth testing.

Suggested next steps: record one routine with Teach mode, save it as a skill, and run it in Pro mode to validate results. Track time saved and iterate on the skill library to compound productivity gains.

 

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