a product team of one. live, on demand applied ai strategy and engineering
from idea to production in weeks
most AI projects don’t fail because of the models. they fail because nobody owns identity, permissions, or the path to production.
previously aws, dell · harvard, uchicago · github · linkedin · email
i build AI products with founders and teams — live, on-camera, collaboratively, in focused sessions.
from zero to working production system in weeks, not months.
you walk away with a real system your team can use immediately. not a prototype, not slides. ready to deploy or iterate on.
best fit for founders or small operating teams – including those in enterprise and pe-backed environments – serious about shipping ai.
i work equally well with technical and non-technical clients.
book an intro call — 45 minutes, no cost, we’ll build together — live
i also offer fixed-price packages for scoped deliverables starting at $10k
assess → build → harden
assess
genai initiative prioritization
stop guessing which AI projects to fund. source, score, and prioritize as a portfolio
ai architecture audit
a focused review of your AI stack with a prioritized action plan
build vs buy analysis
a structured analysis of whether to build or buy AI capabilities — with cost models and a clear recommendation
build
idea-to-pilot sprint
one week to turn your AI idea into a working pilot — validated, functional, ready to demo
see how this worked for apprentice →
mcp server build sprint
zero to production mcp server in one week. deployed, documented, yours
see how this worked for apprentice →
pilot-to-production sprint
two weeks of half day sprints to ship your stalled AI pilot — or kill it with a clear post-mortem
harden
ai governance layer setup
identity, permissions, and audit trails for your AI systems — powered by gatewaystack
see how this worked for inner →
you're spinning up a genai program and need to decide what to prioritize → genai initiative prioritization
you want to design and architect an internal ai platform or product → ai architecture audit
you're deciding whether to build or buy → build vs buy analysis
you have an AI idea that needs to become real → idea-to-pilot sprint
you need AI tools talking to real systems → mcp server build sprint
you have a pilot that's stalled → pilot-to-production sprint
you're worried about identity, permissions, audit → ai governance layer setup
start with a single sprint session. we'll pick one problem, build live, and you'll see how i work — no commitment beyond the session. if it leads somewhere, great. if not, you walk away with working code.
→ book an intro call
book a slot
→ weekly office hours
inner — emotional memory for LLMs, available as a chatgpt app and on iOS
apprentice — AI-powered art study across 37,000+ masterworks
both run on gatewaystack, the trust and governance layer i built for user-scoped AI access. it handles identity, permissions, and auditability.
apps are the flywheel, data is the asset — building a portfolio of AI apps? bet on the data
the three-party identity problem in mcp servers — the architectural challenge every agent system hits
is claude code secure? — secrets, prompt injection, and the real weak link
notes from building AI-native systems in public.