About
Building agents got easy. Running them didn't.
AgentWay exists to close that gap — to make an autonomous agent something you can supervise rather than something you hope about.
The problem we kept running into
In the space of a couple of years, building an AI agent went from a research project to an afternoon. Frameworks, model APIs, tool calling, memory — the construction problem is largely solved, and getting better fast.
Operating one is still where it was. You write an agent, deploy it to a server, and immediately lose all visibility into it. Its interface to you is a log file. Its interface from you is a code change and a redeploy. If it gets stuck at 2am, it either guesses or dies, and you find out in the morning.
That asymmetry is strange when you name it plainly. We would never accept it from a human team member — no way to ask what they're working on, no way to say "hold on a moment", no way for them to ask a question. Yet we deploy software that acts with real autonomy and give it none of those channels.
What we're building
A control plane. One screen where every agent you run is visible, directable, and pausable — and where an agent that needs a human decision can actually get one.
Deliberately, AgentWay is not a framework. It doesn't want to own how you build agents, which model you use, or where you host them. It attaches to the loop you already wrote in about three lines and stays out of the way. Neutrality is the point: a control plane that only worked with one vendor's agents wouldn't be a control plane, it would be a lock-in strategy.
What we believe
Honesty over polish
A dashboard that implies control it doesn't have is worse than no dashboard. When AgentWay can't guarantee something — pausing an agent mid-API-call, making an agent obey — it says so, in the product, at the moment it matters.
Your agents keep running
If AgentWay goes down, your agents carry on working. A control plane that takes the fleet with it during its own bad deploy has failed at the one thing it's for.
Adoption should be nearly free
If wiring up an agent takes a refactor, nobody does it, and then the dashboard is empty. Every design decision gets measured against how much work it puts on the developer.
Humans stay in the loop
Instructions come from people, and every one is attributable in an audit trail that can't be edited. Agents can observe each other; only humans can direct them.
Where we are
AgentWay is early. The first version focuses entirely on human-to-agent communication, because that's the problem people have today — not agent-to-agent orchestration, which is mostly still anticipated rather than felt.
If you're running agents in production and any of this sounds familiar, we'd genuinely like to hear how you're coping with it right now. Get in touch.
Try it with an agent you already run.
Three lines of Python. Nothing to rewrite.