Outside operator on your
AI roadmap.
Three ways to work together. Advisory for teams that need to apply AI to a specific use case fast. Transformation for operators rewiring entire processes and orgs around AI. Forward deployment when you want an engineer embedded in your team, shipping in your own stack. All three deliver working systems — not slide decks.
Pick the depth that matches the problem.
Apply AI where it actually moves the business.
Most AI projects stall in slide decks. I work shoulder-to-shoulder with founders and ops leads to ship the right AI use cases — agents, copilots, NL-to-data, internal tools — to production in weeks, not quarters.
- 1 week TO FIRST WORKING PROTOTYPE
- 3–5 USE CASES PRIORITIZED
- 60–80% TYPICAL OPS-COST CUT
Redesign your business around AI — without breaking what works.
I help operators rewire entire processes, teams, and product surfaces around AI: from internal tooling and data infrastructure to customer-facing agents and the org chart that runs them.
- 8–12 wk FROM AUDIT TO ROLLOUT
- 3 layers PROCESS · DATA · ORG
- Real PRODUCTION SYSTEMS
Embed an AI engineer in your team — shipping in your own production environment.
Forward deployed engineering, not slide decks: I join your Slack, your repo, and your CI, then build and deploy AI systems straight into your cloud or VPC. One accountable operator working shoulder-to-shoulder with your team — leaving behind runbooks, evals, and an in-house owner.
- On-site EMBEDDED IN YOUR TEAM
- Your stack PROD IN YOUR INFRA
- Handoff RUNBOOKS + TEAM UPSKILL
I ship AI products for a living.
Most consultants advise from PowerPoint. I advise from the same code I deploy on Monday morning.
Not sure which one fits?
Just send a sketch.
Drop a paragraph about what you're trying to do — I'll reply within one business day with a recommended path (advisory, transformation, forward deployment, or "you don't need any of them yet").