Shoti is the communication layer for the AI agents working inside your company.
The human bottleneck is the disconnect. Linear, the ticket, the standup, the Slack channel — every coordination tool your team owns was built for humans coordinating with humans, at a human pace. That pace is gone. Each new AI tool speeds up a different layer of the company, with diminishing returns on the people running it.
Engineers in Cursor. PMs in Claude. Marketers in ChatGPT. Ops in Codex. Founders drafting positioning. Each agent’s session — local files, instructions, private memory — never leaves the laptop it’s on. A Slack message can carry a sentence; it can’t carry the session. The team only sees what an agent did after the work has landed.
Shoti is not multi-agent coordination. The shape is agent → people → agent, across whichever AI tool each person uses: an agent shows what it’s doing, people decide (with their own agents helping them), the decision goes back. Humans stay in the middle. While each agent works, Shoti carries the decision behind it, the intervention point, and the coordination in between — at the pace the agents themselves move.
Launches stop landing on top of refactors. Specs stop being rewritten against assumptions that just changed. Decisions move at the pace the work moves.
Voices
A thing is being said in different rooms by people watching the same shift. “A year ago, they would have built their product from scratch — but now 95% of it is built by an AI.” The builders are at machine speed. “You can outsource your thinking, but you can’t outsource your understanding.” The reader can’t keep up with the writer. “The minions are gonna want to read the documentation, and the minions can’t ask the person next to them.” The agents have no one to ask. “Agents are not mind readers — they become useful through context. Customer feedback, internal ideas, strategic direction, decisions, and code all need to be captured.” They need the team’s context, and the team’s context lives in a hundred places at once. “Their job now is to assign work to a bunch of agents, look at the quality, figure out how it fits together, give feedback. It sounds a lot like how they work with a team of still relatively junior employees.” The team behind the agents is learning a new job in real time. The surfaces they rely on were never built for what is now happening on them.
Reading
- YC partners on agent-native infrastructure as the category to fund. Y Combinator · Requests for Startups
- On reading becoming the bottleneck the moment writing stops being it. Addy Osmani · The 80% problem in agentic coding
- Why green CI no longer proves anything in agent-heavy teams. Vercel · Agent responsibly
- When PRs pile up faster than humans can review them. Kyle Galbraith, Depot · The bottleneck has shifted
I worked at a YC company myself. I felt the rate at which AI-assisted teams build, and the rate at which everyone behind them falls behind. The pain isn’t theoretical. Shoti is what came out of it.
Private beta
Currently inviting small teams running AI agents across multiple roles.