Build AI agents that ship — safely.

AI Operator is the execution track: practical workflows for turning AI into real outputs (not demos) with security + reliability guardrails.

The promise

• Ship outcomes: playbooks, templates, checklists, and “what breaks” notes.
• Safety boundaries: privacy-aware, threat-modeled, controlled integrations.
• Operator mindset: repeatable systems you can run again next week.

Start here

• Quickstart: /videos/ — short demos you can copy.
• Patterns: /blog/ — workflows, design notes, and failure modes.
• Building blocks: /projects/ — tools and components.

What you’ll find here

1) Operator playbooks

Step-by-step workflows (inputs → process → outputs) with constraints, tradeoffs, and validation steps.

2) Reliability + evaluation

What “good” looks like, how to test it, and how to keep it from drifting.

3) Safety architecture

Practical threat modeling for AI workflows: data boundaries, permissions, logging, and blast-radius control.

4) Templates

Copy/pasteable scaffolds (checklists, prompts, runbooks) designed to survive real use.

Work with me

If you want help building or hardening an AI workflow (privacy, security, reliability, shipping), email: [email protected]