I ran into one of those boring tasks that is exactly where I want AI to help: updating a Kit.co page for my everyday carry setup where several products had titles and links, but no descriptions.
The job was simple for a person, but repetitive. Open the product, grab the useful description, summarize it, go back to Kit.co, paste it into the product description field, save it, and repeat. That made it a good real-world test for AI browsers like Comet and Atlas.
Quick Answer
Comet handled this workflow better than Atlas. It was able to work through multiple products, open links, summarize descriptions, return to Kit.co, and fill in the missing fields. It was not perfect, and it eventually needed guidance, but it actually moved the task forward.
Atlas could not handle the same kind of chained agent workflow in the way I needed. From my testing, Atlas feels useful for summarizing, browsing, and regular ChatGPT-style work, but it is not yet where I would trust it for multi-step browser automation.
The Task I Tested
I was building a Kit.co page for the products in my everyday carry backpack. Kit.co lets you group affiliate links into kits, which is useful when people ask what gear I use.
The problem was that some products imported with a title and link, but not a description. To clean that up manually, I would need to open each product page, copy or summarize the description, return to the Kit.co editor, paste it into the right field, save it, and then do the same thing again for the next product.
That is not hard work, but it is repetitive work. And that is where I think AI is most useful. I do not want AI doing things I do not understand. I want it taking over the mundane jobs that I can easily check afterward.
What I Asked Comet To Do
I gave Comet a clear workflow instead of a vague request. I asked it to identify the products in the 2025 everyday carry kit, open each product link, summarize the main description and key features, return to the Kit.co page, add the summary to the product description field, and save the changes when needed.
I also told it to wait for me to confirm before starting. That matters because with browser agents, I want control before they begin editing anything live.
Once I confirmed, Comet started working through the products. It opened items, moved between product pages and Kit.co, and began adding summaries into the missing description fields.
Comet Worked, But It Was Not Instant
One thing that stood out is that browser agents often do not feel faster than doing the task yourself, at least not at first. They have to figure out the page, understand the workflow, and repeat the steps carefully.
The benefit is not always raw speed. The benefit is that I can let it work while I do something else. Since this was a low-risk, mundane task, I could check its work and fix anything that went wrong without much trouble.
Comet made it through several products, including gear like an iPhone case, a MagSafe charger, a cable tester, and other everyday carry items. It was doing the kind of repetitive browser work I wanted it to do.
Where Comet Hit Trouble
Comet eventually ran into an error. I saw a red warning pop up earlier, let it continue, and then it stopped and needed direction.
Instead of forcing it to keep going the same way, I asked what it suggested. It recommended doing the remaining products in smaller batches of two or three, which made sense. Smaller batches reduce the chance of the agent losing track or running into page issues.
By the time I stopped the test, Comet had completed eight products. That was enough to prove the point for me: it was not flawless, but it could actually perform the workflow.
Why Atlas Fell Short
I want to like Atlas because I already use ChatGPT heavily for everyday AI work. I use it for mundane tasks, GPTs, projects, notes, and even dictation from my phone. Having more of that inside a browser sounds useful.
But Atlas is not there yet for this kind of agent task. The biggest issue I ran into is that it does not handle chained agent tasks the way I need. It can do one agent-style task, but then it falls back into regular ChatGPT behavior instead of continuing the agent workflow.
This Kit.co cleanup was really one repeated task across many products. That is exactly where chaining matters. Comet could keep repeating the workflow. Atlas could not do that reliably in my testing.
I also ran into an agent task cap on the Plus plan. It looked like I only had 20 agent tasks per month available, which is a problem if I want to use this for real production work.
My Current Take
Right now, Comet still feels ahead for agentic browser work. It may not be perfect, and it may need guidance, but it has already taken the first real steps for this kind of workflow.
Atlas, to me, feels more like a good browser for summarizing, consuming information, and doing lighter ChatGPT-style tasks. For heavier automation, it feels like it has its toes in the water but has not fully stepped in yet.
I am still testing both, and I am open to Atlas improving. But for this particular real-world job, Comet solved a problem Atlas could not touch.
Key Takeaways
- Comet successfully worked through a real Kit.co product description cleanup task.
- The workflow required opening product links, summarizing descriptions, returning to Kit.co, editing fields, and saving changes.
- Comet was not perfect and eventually needed guidance, but it completed multiple products before stopping.
- Atlas struggled because it could not reliably chain repeated agent tasks in the same way.
- For now, Comet feels better suited for practical browser automation, while Atlas feels stronger for lighter browsing and summarizing tasks.
- AI browsers are most useful when the task is repetitive, easy to verify, and low-risk if something needs correction.
Watch the Video
The video above for the full walkthrough of Comet working through the Kit.co page, where it succeeded, where it slowed down, and why Atlas was not able to handle the same workflow.
