Mark by Airtop

I tried Mark (beta), and it put together a really solid go-to-market plan for me. The recommendations were practical and well thought out. Looking forward to seeing how it evolves. Congrats on the launch!

How does it handle sites that require two-factor authentication or have aggressive bot detection? Curious how reliable it is in practice on those kinds of tricky logins.

Finally gave it a real test by asking it to grab shipping rates from a courier site and it just logged in and pulled the data without me touching anything. Genuinely surprised how well it handled the login step.

The demo site where it just logs in and pulls data on its own is wild. Love that you kept the interface to plain words instead of piling on dashboards.

How does it handle sites with heavy bot protection or CAPTCHAs that block most automation tools?

Tried having it grab some shipping updates from my carrier portal and it actually logged in and pulled the info without a hiccup. The plain-English setup feels really natural.

this is genuinely impressive. told it to grab flight prices from a few sites and it actually logged in, navigated, and pulled clean data back. setup took maybe two minutes.

How does it handle sites with strict bot detection or CAPTCHAs when the agent tries to log in and grab data?

The "chatbots that ideate then leave you with all the work" line is exactly why I stopped trying to use AI for marketing planning early on. Getting a strategy back that reads well but has no path to execution is worse than having no help at all, because now I feel obligated to try it before admitting it was theater.The compile-to-deterministic-code angle is where this gets interesting. Most agent frameworks I've seen have the same flaw as the strategy chatbots, they generate a plan every run, which means the plan drifts even when the task hasn't. Compiling once and re-running the compiled artifact is the pattern I keep wishing existed. Curious how you handle the case where the underlying page/site changes and the compiled agent breaks, do you re-compile on failure, or does Mark flag it and ask?Also honest question, for someone running solo who already has a rough GTM shape they trust, does Mark benefit them, or is the biggest value for people who need help figuring out the plan itself? Trying to figure out if I'd get more value from the planning side or the execution side.

"no APIs, just words" is a strong claim for browser agents specifically because most sites don't have an API to begin with. that's the actual gap browser automation fills, the long tail of internal tools and dashboards that were never built with integration in mind. how does it handle sites with heavy bot detection though? logging in and browsing like a human is exactly the pattern most anti-bot systems are tuned to catch.

Compiling intent into code is the right instinct, we landed in the same place: re-deriving the same plan with an LLM on every run is what kills reliability. Where it got hard for us was the genuinely non-deterministic steps, like 'is this reply a real lead or a bounce', you can't compile the judgment out. So the interesting line is compiled-vs-LLM: does Mark let the author pin certain steps as always-LLM, or does the compiler decide that itself?

Interesting idea. Does Mark let you adjust targeting criteria before the agents actually go live?

The GTM plan is the part that demos well, but generating a plan is the easy 20%. The thing I'd want to know building this kind of agent: does Mark close the loop on what actually converted, weeks later and through noisy attribution, and revise? Or is it generate-once? A plan a solo marketer can't measure against gets abandoned by week two.

the part that stands out to me is compiling into deterministic code instead of running an LLM call on every step. that's the actual fix for the reliability problem most agent tools have, cost aside. curious how it handles a site that changes its layout after the automation was compiled, does it silently break or re-detect and recompile

This looks super useful for automation workflows. How reliable is it when you scale multiple browser tasks at the same time?