An AI-native development & operations leader.
Bolting a chatbot onto an old operating model isn't AI strategy. I help companies become genuinely AI-native, rebuilding how products are built and how the organization runs so that AI is the default, not an add-on.
Not AI features.
An AI-native operating model.
The difference between a company that uses AI and a company that is built around it shows up everywhere, from the backlog to the org chart.
Same process, new toy
- , A copilot license and an "AI feature" on the roadmap
- , Workflows unchanged; AI lives at the edges
- , Pilots that never reach production
- , Spend without measurable leverage
The model is redesigned around AI
- →Business, product & engineering processes rebuilt AI-first
- →AI in the SDLC, code, review, testing, ops
- →Agentic systems doing real production work
- →Leverage you can see in cost, speed & quality
I lead the whole cycle.
AI-Native Development
Shipping AI deep in the product and the pipeline, not as a demo, but as production infrastructure that holds up at scale.
- →LLM-powered data & product systems in production
- →AI woven through the SDLC: generation, static & security review
- →Agentic & retrieval architectures, with the right guardrails
- →Eval, observability & cost control for AI systems
AI-Native Operations
Changing how the organization actually works, so teams, decisions and processes are built around AI from the ground up.
- →Redesigning business & engineering workflows AI-first
- →Upskilling teams & setting AI usage, safety & data policy
- →AI for BI, decision support & operational visibility
- →A roadmap that ties AI investment to revenue, not hype
Continuous Optimization
AI moves too quickly to rest on a launch. What was state of the art last quarter is table stakes today, so the work never finishes, it compounds.
- →Tracking model, tooling & cost curves, and adopting what is genuinely better
- →Re-running evals as models and prompts drift, so quality never quietly regresses
- →Tightening cost and latency as usage scales and cheaper paths appear
- →Feeding production signals back into the product and the operating model
The companies that win the next decade won't be the ones that added AI. They'll be the ones that rebuilt themselves around it, in the product and in the org.
From audit to operating system.
AI-Native Audit
A clear-eyed read on where AI creates real leverage in your product and operations, and where it's a distraction.
Build & Ship
Hands-on architecture and delivery of production AI systems, with eval, observability and cost control built in.
Operating-Model Redesign
Rewiring workflows, teams and decision-making so the whole organization runs AI-first, and it sticks.
What founders & boards ask.
What does "AI-native" mean in practice?
It means the operating model is redesigned around AI rather than having AI bolted on. Business, product and engineering processes are rebuilt AI-first, AI runs inside the SDLC for code, review, testing and ops, and agentic systems do real production work, with leverage you can measure in cost, speed and quality.
We already have a copilot license. Isn't that AI-native?
Not on its own. A copilot license and an "AI feature" on the roadmap is AI bolted on, workflows stay unchanged and AI lives at the edges. AI-native means the workflows, teams and decision-making themselves are rewired around AI.
Is this just consulting, or will you build?
Both. I work hands-on, architecting and shipping production AI systems with eval, observability and cost control, as well as redesigning the operating model so the change sticks after I leave.
How do you keep AI systems reliable and cost-controlled in production?
Every system ships with evaluation, observability and cost controls built in, plus guardrails on agentic and retrieval architectures. I've run LLM-powered pipelines processing ~250M records a month on a 75-node cluster, so the patterns are battle-tested, not theoretical.
Where do you start with a company that's new to this?
With an AI-Native Audit: a clear-eyed read on where AI creates real leverage in your product and operations, and where it's a distraction, followed by a roadmap that ties AI investment to revenue rather than hype.
Ready to become
AI-native?
Whether you're shipping AI into the product or rebuilding how your teams operate, let's map the path that actually moves the business.