Statewright – Visual state machines that make AI agents reliable
Agentic problem solving in its current state is very brittle. I fell in love with it, but it creates as many problems as it solves. I'm Ben Cochran, I spent 20+ years in the trenches with full-stack Engineering, DevOps, high performance computing & ML with stints at NVIDIA, AMD and various other organizations most recently as a Distinguished Engineer. For agents to work reliably you either need massive parameter counts or massive context windows to keep the solution spaces workable. Most people are brute forcing reliability with bigger models and longer prompts. What if I made the problem…
Statewright – Visual state machines that make AI agents reliable launched on May 12, 2026 with 126 votes, #216 of 20,538 launches that month and more than 95% of that year's launches.
In plain words
Statewright is a tool for building visual state machines that constrain AI agent behavior and decision-making. It addresses the reliability problems of current AI agents by using formal state machine structures to limit tool and solution spaces, allowing smaller language models (13-20B parameters) to solve complex problems more reliably. The product is designed for developers and engineers working with AI agents who need dependable agentic problem-solving without relying on massive models or extended context windows.
written from the facts on this page · September 2026
From the sources
State machine guardrails for AI agents. Contribute to statewright/statewright development by creating an account on GitHub.
In the maker’s words, at launch
Agentic problem solving in its current state is very brittle. I fell in love with it, but it creates as many problems as it solves. I'm Ben Cochran, I spent 20+ years in the trenches with full-stack Engineering, DevOps, high performance computing & ML with stints at NVIDIA, AMD and various other organizations most…
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