Definitions and patterns for teams building AI systems where accessibility, evidence, and review matter. These notes explain how we think about visible procedures, semantic structure, review gates, and systems your team can inspect.
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An AI-powered pattern that extracts author intention from page context to create equivalent experiences through accessibility metadata
Capabilities
Reusable scripts combining deterministic code with AI agents to orchestrate autonomous engineering workflows.
The practice of creating technology that helps people climb to expertise and capabilities previously out of reach—machines adapting to humans, not humans to machines.
The practice of providing AI systems with the minimum viable context needed to make grounded decisions—not everything, the right things, at the right time.
The practice of building AI systems that extend human capability without hiding their reasoning—built for domains where trust isn't a feeling, it's documentation.
An AI system architecture where every decision, reasoning step, and procedure is visible and reviewable by humans.
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Bring us the workflow, the content, and the failure modes. We will help decide whether discovery is the right next step.