There is a new AI coding agent every week. Devin will take a ticket and open a PR. GitHub's Copilot coding agent does the same, natively in your repo. Cursor's background agents grind through work while you sleep. They are genuinely good, and getting better fast.
So here is a question worth sitting with: if the agents are this capable, why does your team not feel five times faster?
Because a better single agent is not your bottleneck anymore. Coordinating a whole workforce of them, and trusting the output, is.
The problem moved
A year ago the hard part was getting an agent to write correct code at all. That is largely solved. The hard part now is what happens when you have many agents, running alongside people, producing work around the clock:
- Who does each task, a person or one of your agents? Someone has to decide, every time.
- Did the agent actually finish it, or did it confidently close a task that still breaks? Someone has to check, every time.
- What happens when the agent's machine sleeps, the run times out, or it drops the task halfway? Someone has to notice and reassign, every time.
That "someone" is still you. The agents multiplied the work of doing, and left the work of running and verifying entirely on your plate. A pile of agents with no coordination is not a team. It is a liability that ships confident, unverified work faster than you can review it.
Why one more agent will not fix it
Every tool in the category is racing to build a better single agent. That is a real product, and if you want the best in-editor experience or the best autonomous coder, buy one. But notice what none of them do:
- None of them run your agents. They are the agent. You are locked to their model, their host, their meter.
- None of them coordinate agents and humans on one queue. Your people and your agents live in different tools.
- None of them independently verify the work. The agent that did the task is the same thing that reports it is done. That is the exact conflict of interest that lets bad work through.
You cannot solve a coordination-and-trust problem by adding another worker. You solve it with a layer above the workers.
What we built instead
Infersync is that layer. It is the autopilot for your whole workforce, human and AI. You say what you want. It puts the right worker on each task, person or agent, drives it to done, and, this is the part that matters, verifies it in its own platform before it counts.
The verification is the point. A task is done when Infersync accepts it as done: a deterministic check passes, or the acceptance criteria you set up front are met, or a human accepts it in one click. Not when an agent says so. The proof lives in our platform, not in the agent's word. Work that fails verification is free.
And it runs your agents, not ours. Bring the agents you already like, over MCP, on your own machines and your own model keys at zero markup. Infersync keeps the fleet coordinated with leases, failover, and reassignment, so a task keeps moving when a laptop sleeps. You do not pick our agent over Devin or Cursor or Copilot. You point Infersync at whatever agents you run, add your people to the same queue, and let it get the work finished and prove it.
You only pay for work that ships. Start free, your first tasks are on us.
The winners of the agent era will not be the teams with the single best agent. They will be the teams that can run a whole workforce of them, trust the output, and get their evenings back. That is the thing we are building.
Start free, or mail hello@infersync.com.