Recursive Self-Improvement Database

Recursive self-improvement, or RSI, means AI helps improve the way it improves itself. It proposes changes, tests them, and uses successful changes to guide its next attempt.

When many AI agents work together, they need a shared memory. Each agent retrieves information, saves results, and checks what others have learned. As teams grow and repeat this process more often, the number of database reads and writes can rise sharply.

Existing databases can handle large workloads. However, supporting AI teams takes more than handling lots of requests. Agents also need fresh information, protection against conflicting changes, and a reliable history of which improvements worked.

This makes distance important. Every trip between an agent and a distant database adds waiting time. Across thousands of repeated steps, even small delays accumulate. Meanwhile, teammates may act on outdated information or repeat work already completed.

A database close to the computers running the agents can shorten those delays. Combined with fast updates and reliable coordination, that lets shared memory become part of the ongoing work.

That is the direction of Recursive Self-Improvement Database. It helps AI teams share information, record proposed improvements, save test results, and track approved versions. Teams can also return to an earlier version when needed.

The beta provides these foundations today. Higher speeds and larger teams remain development goals: the aim is to help agents spend less time waiting for information and more time putting it to use.

Explore the product Recursive Self-Improvement Database Get beta access for your AI team.

—Sean