About
Docktor Labs is the consulting practice of James Docktor — a Senior Instructional Designer and AI systems builder with 10+ years of experience at Silicon Valley's most demanding technology companies, including Google, Apple, VMware, Amazon, Facebook/Meta, Atlassian, and Waymo.
The practice sits at a rare intersection: deep instructional design expertise combined with hands-on AI systems building. James doesn't just teach AI adoption — he builds the infrastructure that makes it stick. Every engagement is grounded in a simple conviction: organizations don't need more AI awareness. They need systems that make the right behavior the easy behavior.
Before Docktor Labs, James spent 13 years as a mathematics teacher. That background informs everything — real understanding is structural, not superficial. You either see why something is true or you've memorized a procedure that will fail you at the boundary. That same principle governs how Docktor Labs designs AI capability programs.
Proprietary Framework
Think • Integrate • Pair & Share is a multi-model consensus architecture invented by James Docktor to solve a fundamental problem in enterprise AI: how do you trust an LLM recommendation when you can't verify it yourself?
The TIPS Framework routes every query through multiple Claude models simultaneously. A separate LLM Evaluator microservice scores outputs against each other before anything surfaces to the user — flagging honest uncertainty rather than projecting false confidence.
Production-deployed on Render & Vercel. The IP core of every Docktor Labs engagement.
Services
Half-day or full-day team enablement grounded in 10+ years of L&D expertise. Designed for teams moving from AI awareness to AI operation. Role-differentiated tracks for individual contributors, managers, and technical leads.
Half-day • Full-day • Custom
The TIPS Framework applied to your AI stack. Multi-model consensus validation, confidence-scored findings, and prioritized recommendations for improving LLM reliability, governance, and output quality across your organization.
Assessment • Report • Roadmap
End-to-end engagement: discovery, build, enablement, and handoff. Your team owns what we build together. Phases cover needs analysis, AI workflow design, champion network activation, and measurement infrastructure.
Discovery • Build • Enablement • Handoff
Background & Credentials
Contact
Whether you're running your first AI pilot or scaling adoption across a global team — let's talk about what you're building and where the friction is.
james@docktorlabs.com