Tabstack

[Tabstack @tabstack]

Not every page needs a full browser. 🌐

We’ve added the "effort" parameter to Tabstack! Now you can choose how hard we work to fetch a page:

🏎️ min: <1s for static sites
⚖️ standard: Smart default
🛠️ max: Full JS rendering

Optimize your speed: https://t.co/xP8oH5rNDG

[Tabstack @tabstack]

As we began building Tabstack, we recognized early on that agent native search was critical for our automation layer.

Parallel's ability to consistently surface authoritative, up-to-date information in clean, structured formats that integrate smoothly into our agentic loop.

[Parallel Web Systems @p0]

Mozilla built @tabstack to let AI agents browse the web the way humans do: by clicking, scrolling, form-filling, and extracting page information.

They use Parallel’s Search API to handle what comes before all of that.

[Tabstack @tabstack]

Web automation is broken. Scripts are brittle. The web is chaotic. 🌪️

Meet Pilo: an open-source agentic engine that gives LLMs a steering wheel. 🚗

It plans, observes the accessibility tree, executes, and heals itself.

And today, it's yours to use. ⚡️

https://t.co/M1YurmRhy5

[Tabstack @tabstack]

Extracting data from a URL is an infrastructure problem. Answering "Compare Slack vs Teams retention" is a reasoning problem

We’re launching Tabstack Research to bridge this gap. Multistep discovery, gap detection, and cited synthesis 🚀

https://t.co/gFW23ilg4Z

#LLMs #DevTools

[Tabstack @tabstack]

🚀 Tabstack: Browsing Infrastructure for AI Agents

You built a brilliant agent. Then you connected it to the internet, and everything broke. 💥

Stop paying to tokenize noise. We fixed the infrastructure so you can focus on the intelligence 🧠

https://t.co/gTh5S5uNqj