SMALL

About SMALL

SMALL is a state protocol designed to make AI systems legible, deterministic, and safe to operate at scale.

Modern AI-assisted workflows often fail in the same way: intent is implicit, state is ephemeral, and execution decisions disappear once a session ends. This makes systems difficult to audit, resume, or trust.

SMALL does not add intelligence or features. It introduces structure.

By externalizing intent, constraints, progress, and handoff into explicit, machine-readable artifacts, SMALL makes execution inspectable in the same way modern infrastructure and data systems are.

SMALL is intentionally minimal by design. Its goal is not convenience, but correctness.

About the Author

SMALL was created by Justyn Clark, founder of Justyn Clark Network, a systems-focused development studio building execution-first software at the intersection of AI, infrastructure, and media.

Professional name (legal / employment): Justin Johnson

Justin's work spans full-stack application development, backend systems, schema-driven architectures, and tooling for long-running, failure-tolerant workflows. His focus is on systems where determinism, recoverability, and auditability are not optional.

Across projects, a consistent pattern emerged: modern tools make it easy to start work, but difficult to resume it safely. Intent is implied, state lives in memory or chat history, and execution context is lost when systems or sessions fail.

SMALL was built to solve that problem directly.

Engineering Focus

Justin's engineering work centers on systems where:

  • Execution must be auditable and reproducible
  • State must survive crashes, context loss, and handoffs
  • Constraints must be explicit and enforceable
  • Humans and automated agents must collaborate without ambiguity

This includes experience designing and implementing:

  • Schema-driven platforms
  • Deterministic workflow tooling
  • Infrastructure-adjacent systems with real safety boundaries
  • Media and content pipelines with strict lifecycle requirements

Why SMALL Exists

Most AI workflows today rely on ephemeral context: prompts, chat history, and undocumented assumptions. This works for experimentation, but breaks down under sustained use.

SMALL treats execution as a first-class artifact. By externalizing intent, constraints, progress, and handoff state into a structured, verifiable format, it makes AI-assisted work inspectable in the same way modern infrastructure systems are.

In practice, SMALL functions like a flight data recorder for execution: when something goes wrong, the system leaves evidence rather than guesses.

About Justyn Clark Network

Justyn Clark Network (JCN) is a development studio focused on execution-first systems across software, AI, and media.

JCN builds tools and platforms designed for longevity, where decisions are traceable, systems are explainable, and work can survive handoffs between people, teams, and automation.

SMALL is a flagship system created and maintained by JCN.

GitHub: https://github.com/justyn-clark
Studio: https://justynclarknetwork.com