Intelligence is becoming cheaper, faster, and more capable. But the institutions around it still look much as they did before language models could reason over software, documents, and decisions.

Most AI is asked to perform a task and then disappear. A person supplies the goal, reconstructs the context, checks the work, and carries the result into the next system. Better models make those moments more useful, but they do not yet change how an organization holds responsibility.

We think the important work is making intelligence durable: able to retain state, work against a commitment, use bounded authority, learn from what happened, and remain legible to the people accountable for the outcome.

This is not a question of replacing people with chat. It is a question of giving people a better way to direct capable systems—through objectives, constraints, policies, and feedback that survive beyond a single prompt.

The resulting organizations will not be automated versions of today’s workflows. They will be designed around a new resource: intelligence that can persist, coordinate, and improve over time.

Impala is building services around this direction. We are developing the infrastructure to make them durable, inspectable, and capable of operating over time. The questions that occupy us include:

• How durable agents should hold state, memory, and responsibility
• How people set boundaries without becoming the bottleneck
• How systems earn trust through inspection, recovery, and feedback
• How organizations can direct work by commitments instead of task queues

Talon is the infrastructure we are open-sourcing along the way: a control plane for durable agent systems. It supports the work, but it is not the whole thesis.

We will share the work as it becomes real. Read our writing, explore Talon, or follow along on GitHub.