For funded teams with complex AI/ML delivery

Ongoing fractional AI leadership, inside your team.

Machine Wisdom works with companies that already have real AI/ML work, real engineering effort, and a need for sustained principal judgment as the product, team, and system evolve. I embed with your team to set direction, make hard architecture and sequencing calls, review the work that matters, and create continuity across the technical decisions that shape the system.

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The judgment comes from production ML at Roblox and Google, plus client safety architecture for a mental-health AI system. See the proof

Ways to bring me in

Fractional AI Lead is the default shape. Sprints and reviews are narrower entry points when the need is specific.

Ongoing fractional engagement

Fractional AI Lead

You have funded AI/ML work, a team already building, and a need for sustained AI leadership while the product, team, and system evolve. I embed as your fractional AI lead for complex delivery: setting technical direction, making architecture and build-versus-buy calls, reviewing the work that matters, and staying close enough to the code that the decisions hold. The shape is ongoing because the value is continuity across architecture, delivery, evaluation, and technical decisions.

6 weeks

AI Initiative Recovery Sprint

You need concentrated principal attention on a defined AI/ML initiative, architecture decision, or delivery path. I work inside the current product, codebase, data, and team constraints to separate the real delivery problem from noise, then reshape the highest-leverage part of the work alongside your engineers. Your team gets owners, sequencing, and decision criteria they can keep using.

Focused review

Production Readiness Review

You need an experienced principal read on whether an AI/ML system is ready for the role the business needs it to play. I review the product promise, system architecture, data path, model behavior, evaluation, and operational ownership together, then separate launch blockers from ordinary engineering follow-through. You get a clear recommendation on what to ship, improve, limit, or sequence next.

The first call

The call is for fit.

The call is for fit: whether you have the owner, budget, team, and complex delivery need that make ongoing fractional AI leadership useful.

A good engagement starts when the work is important enough to fund, concrete enough to attach to real engineering, and senior enough to need principal judgment.

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1 What AI/ML work needs principal-level direction? So we anchor the engagement in a concrete delivery need.
2 Who owns the budget and technical decision? So the work has authority behind it.
3 What team is already in place? So the engagement strengthens the people who will keep owning the system.
4 What sustained outcome would make this worth the investment? So progress is defined in business and engineering terms.
5 Which decisions need principal judgment now: architecture, build-versus-buy, evaluation, sequencing, ownership, or delivery risk?

What you can count on

Principal judgment inside the work.

The value is not a deck from the outside. It is technical direction, review, and implementation judgment applied where the team is already building.

Your team keeps ownership.

The point is shared operating clarity: your people keep owning the system while the hardest technical decisions get sustained senior attention.

Part of the operating model.

The engagement gives funded teams principal-level direction without requiring them to build the whole AI leadership function in-house.

What I don't do

Engagement-shape filters

These filters keep the engagement attached to real delivery work, real authority, and a team that keeps owning the system as the engagement evolves.

Hourly staff-aug with no named outcome.
Advisory-only work with no connection to what ships.
Exploratory calls when there is no budget for senior engineering involvement.
Engagements with no internal owner who can make or carry decisions.
Roadmaps and decks disconnected from the actual product, codebase, data, or delivery path.
Replacing the team you should be building; the work is designed to make your existing team stronger.

Bring the work that needs principal judgment.

The useful conversation starts with the team, the system, the delivery pressure, and the decisions that need to hold as the engagement evolves.

Book the call