A shared agent beats a private one. That's multiplayer AI.

The best work tools of the last two decades won the same way. A file that only one person could open at a time became a file a whole team could sit inside together.

Sourabh RakhyaChief Product Officer, Kryttle

Aug 26, 2026

The best work tools of the last two decades won the same way. A file that only one person could open at a time became a file a whole team could sit inside together. The tool didn't get smarter. It got shared, and that's what actually changed how the work got done.

AI hasn't had that moment yet. Working with AI is still single-player. You open a chat, type a prompt, get an answer in a box only you can see. If a teammate needs it, you send them a screenshot or a read-only link to something they can't touch.

That's about to matter a lot more than it used to. Agents today aren't answering one-off questions anymore. An agent that reads a vendor's inbox, checks it against a contract, and updates a shared sheet is already normal work, not a demo. Work at that size was never meant to sit inside one person's private history. It pulls in whoever owns the data, whoever owns the decision, and whoever has to act on the result, and right now none of them can actually touch the thing together.

We think there's a version of this for every kind of work we've watched up close. Coordinators managing vendors as a group instead of one person's inbox. Finance teams building reports on data someone else's agent already collected. School staff tracking student records without five separate spreadsheets. Loan teams reviewing covenant documents as one shared trail instead of five inboxes.

What this means for Kryttle

We saw the shape of this clearly with a client who runs event operations. A coordinator built an agent that reads vendor mail and keeps a sheet current. She shared it with her team. A second coordinator looked at it and added a job, fetching each vendor's rating, without rebuilding anything or asking her how it worked. Within the week, finance had layered a spend report on the same data, and operations had added a compliance check on top of that.

Nobody scheduled a meeting about any of it. Nobody sent a screenshot. One agent, four people, and the thing kept getting more useful with every person who touched it. That's the bet behind Kryttle: not a smarter model, but a place for a team's work with AI to actually live together instead of scattering across four private chat histories.