Engagements built around outcomes — not hours.

Founders and product teams shipping their first serious AI feature.

I take a vague AI ambition ("we should add an assistant") and turn it into a system that actually survives real users — with evals, guardrails, and a clear path from prompt to production.

• Workshop scope, success metrics, and failure tolerance
• Prototype → eval harness → hardened production build
• Hand-off includes runbooks, eval suite, and observability

Teams with an existing product who want grounded retrieval done right.

Drop-in retrieval and reasoning that respects your data model, your latency budget, and your team's ability to maintain it after I leave.

• Audit existing data, embeddings, and retrieval quality
• Design hybrid retrieval + reranking + grounded generation
• Ship with monitoring, citation enforcement, and refusal logic

Solo founders or seed-stage teams who need a v1 they don't have to throw away.

End-to-end product engineering — from data model to deployed app — built on React + Django with the boring parts (auth, jobs, payments) handled correctly.

• Discovery sprint to nail down the smallest shippable v1
• Engineering with weekly demos, not month-long silences
• Deploy + monitoring + handoff documentation

Marketing teams who've outgrown what the standard activity catalogue allows.

Custom Journey Builder activities, AMPscript / SSJS systems, and integrations that let your marketers ship campaigns without engineering tickets.

• Map current journey gaps and integration debt
• Build custom activities and reusable AMPscript components
• Document for the marketing team, not just developers