For technical teams

AI Adoption for Engineering Teams

Bring in a lead engineer who has shipped across some of the largest and toughest problems in big tech, health, energy, consumer software, logistics, and platform systems, then taught teams how to use AI in their daily engineering practice.

Plan an AI Adoption Session

Engineering Team AI Adoption

Hands-on workshops, developer workflow design, code-level examples, and team playbooks that people actually use.

AI Architecture Review

A practical review of where AI belongs in your platform, where it does not, and what should ship first.

Fractional AI Engineering

Senior implementation help for teams that need strategy, architecture, code review, and delivery support.

Useful when the stakes are higher than a lunch-and-learn

This is for teams that need adoption patterns, architecture judgment, implementation examples, and a clear bar for what is production-worthy. The point is not a polished strategy deck. It is helping capable people feel the leverage of AI, learn faster, and ship better work.

✓ Lead engineer on some of the largest and toughest problems in big tech

✓ I helped cure a disease with Android for the CDC

✓ I helped the National Renewable Energy Laboratory test theories

✓ Recognized by a Facebook / Meta VP for Better Engineering / AI impact

✓ Reduced a team bug backlog by 40% and saved 120+ engineering days with automation

✓ Built across health, energy, consumer, logistics, and platform systems

✓ Taught weekly AI workshops and delivered a 3-day AI engineering seminar

Typical engagement shape

Audit

Review workflows, tools, code touchpoints, and team readiness.

Workshop

Hands-on implementation patterns with your actual engineering context, tools, and constraints.

Implement

Build or pair on the first useful workflows and review the technical approach.

Adopt

Document team practices, review risks, and set the next delivery loop.