Building Verifiable Shared‑State Infrastructure for Decentralized AI Agents
Imagine a network of autonomous AI agents operating across different processes and infrastructure. One agent updates shared data, another makes a decision based on that data, and a third executes the next step in a workflow. What happens if a process crashes, a message is retried, or two operations conflict? These are not problems that better models alone can solve. They are distributed-systems challenges involving persistence, coordination, recovery, and state integrity. As AI applications become more distributed, these infrastructure concerns become increasingly relevant. Agents need dependable ways to access shared information, recover from failures, and determine whether recorded state changes can be verified. HyperStack is an attempt to make the underlying infrastructure reusable. Rather than building a database exclusively for AI, it is developing a distributed database and compute stack on AO and HyperBEAM. Decentralized AI is one potential application of this infrastructure, alongside other real-time distributed workloads.
The Problem:...
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