Teams are already treating AI agents like employees. Their own email addresses. Their own credit cards. Their own authority to act. Nobody does that for software. The infrastructure beneath them was still built for software.
We’ve been building infrastructure for agents as if agents were software. They’re not.
Software does what you told it to do when you wrote it. An agent decides what to do at runtime. It picks tools, chains calls, holds credentials, and creates effects in the real world, effects that don’t roll back. When something goes wrong, it’s a repo modified, a card charged, a message sent.
We recognized this shift happened, but we reused the infrastructure. We took sandboxes built for deterministic code and dropped agents inside them: hard walls designed to contain a process, not govern a decision-maker. They assume the thing inside is predictable. They don’t assume it has its own judgment about what to do next.
Where production agents create runtime friction
The teams building production agents figured this out before the infrastructure did. Watch what they actually do: they give agents their own email addresses, their own credit cards, their own resource budgets. Nobody does that for software. They’re treating agents operationally like employees: delegate authority, set limits, expect accountability. The infrastructure still treats them like software.
Untrusted input triggers destructive actions
A browser task, API call, or package script only needs one scoped capability.
If raw keys live in prompts, files, or environment variables, every tool becomes a trust boundary.
Skyrocket bill on token and compute
Eval fleets sit idle between jobs or reserve memory for peaks that happen rarely.
Runtime overhead creeps toward the model bill instead of staying a small line item.
Long-running jobs crash mid-flight
A network hiccup kills the container while a migration is still in progress.
Hours of work disappear when memory state cannot be recovered and engineers have to restart from zero.
Failures leave no recovery trail
The email was sent, the record changed, and the money moved before the run failed.
Without an effect log, teams cannot tell what already happened or what can be safely undone.
Software is constrained when you write it. Agents have to be constrained while they run.
That changes everything about what the infrastructure beneath them needs to do. You can’t write in all the constraints at deploy time, because an agent’s behavior is determined at runtime. The constraints have to travel with the execution—scoped to the task, enforced where the agent actually reaches out, and a record left behind whether anyone’s watching or not.
The sharpest example is credentials. Software gets API keys baked in: environment variables, secrets managers, keys that exist as long as the service runs. You give agents their own credentials because you know, intuitively, that a shared credential with unbounded scope is wrong. The agent should only be able to reach what it needs, for this task, right now. That intuition is correct. It just needs a runtime that enforces it.
I started Runta because I kept seeing this gap: teams building production agents and discovering that none of the existing infrastructure was designed for the thing they were actually running. The frameworks organize the reasoning loop. The sandboxes give isolation. But no layer beneath the agent takes responsibility for what it does: the authority it exercises, the effects it creates, the record it leaves behind.
Each tool sees a slice. Teams reconstruct failures after the fact.
The evidence needed to explain a failed eval: commands, packages, network calls, credentials used, and effects.
Scoped · Append-only · InvestigableRunta records execution evidence across processes, files, package installs, network connections, and external effects. Because credentials and egress are governed at the same runtime boundary, teams can investigate failures and enforce policy without handing raw secrets to the agent.
Runta is the execution layer built for agents. It sits beneath the frameworks teams already use, with a boundary around every action the agent takes. Agents act—they spend money, change code, send messages on your behalf. That kind of thing should run on infrastructure that knows it’s happening.