From specification to stress test: a weekend with Claude

Tech Breakthrough: Distributed System Built in 50 Minutes with AI and Specs

In a remarkable weekend experiment, a distributed system with Byzantine fault tolerance, strong consistency, and crash recovery was built using only specifications and AI assistance. The project, called Allium, demonstrates how formal intent can drive autonomous code generation.

The Setup

The system was built using Claude, an AI coding assistant, and 3,000 lines of behavioral specifications written in Allium—a specification language developed by the team. The specifications defined the behavior of core components including Usher (Kafka consumption), Arbiter (event evaluation), Clerk (Byzantine fault tolerance consensus), Registrar (entity caching), Ledger (persistence), and Warden (input deduplication).

From Specs to Code in Record Time

With a simple prompt—”Review the specs in the specs/ directory and implement the system they describe”—Claude generated 4,749 lines of Kotlin code and 103 passing unit tests in just 50 minutes. The specifications were detailed enough that the AI could implement complex distributed systems concepts like Byzantine fault tolerance, where multiple redundant instances process every event independently and compare outputs to catch hardware faults and silent data corruption.

Performance Breakthrough

After 64 commits over several days, the system sustained thousands of requests per second against a strongly consistent datastore with sub-100ms tail latency and zero dropped requests. The team pushed performance targets from 5,000 to 10,000 requests per second, ultimately achieving p99 latency under 100ms.

The Real Test: Crash Recovery

The most impressive achievement was the system’s ability to recover from arbitrary failures. Through resilience testing with 400,000 events across four failure scenarios—killing primary instances, backup instances, both simultaneously, and during recovery—the system proved its correctness. When stock levels went negative or entity state diverged between instances, it revealed subtle distributed systems bugs that were systematically identified and fixed.

Why Specs Matter

The specifications were crucial because they provided formal intent that guided the AI’s implementation. When bugs surfaced during resilience testing, the specs served as the reference point for determining whether the code was wrong or the design needed revision. The team discovered that any decomposition controls for one kind of complexity but introduces another at the boundaries—a perennial problem in software engineering.

The Future of Software Development

This project demonstrates that the skills of software engineering are evolving. While traditional coding skills remain important, the ability to formalize intent through specifications is becoming increasingly critical. The team found that iterative and incremental development hasn’t gone away—it’s just moved up a level of abstraction.

The implications are significant: AI agents can now handle much of the implementation work when given clear specifications, allowing engineers to focus on design decisions and system architecture. As the team notes, “We’ve been telling other industries for decades that they need to adapt to technology. Now the disruption is coming for our own working practices.”

The Allium project is available today through the Claude plugins marketplace, offering developers a glimpse into the future of AI-assisted software development.

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