I build AI that makes it to production.
Demos are easy. Production is hard. I design and build custom AI agents, automated workflows, and data pipelines that are reliable, maintainable, and actually used by the people they were built for.
The gap between AI demo and AI product is enormous.
An AI demo can be built in a weekend. A production AI system — one that handles edge cases, degrades gracefully, respects your data privacy requirements, and that your team trusts enough to actually use — takes real engineering.
I've watched companies spend months and significant budget on AI builds that never shipped, because the people building them didn't understand the business context, or the people defining requirements didn't understand what was technically feasible.
Having 20 years of product experience means I sit at both sides of that table. I can have the honest conversation about what's realistic, what isn't, and what needs to change in the spec before we write a line of code.
“The best AI system is the one your team actually uses every day — not the most technically impressive one.”
My implementation process
Built around getting something real into your hands quickly, then iterating toward what actually works.
Technical discovery
Before writing code, I audit your existing data, systems, and constraints. I map the integration points, assess data quality, and identify the failure modes that will matter. This prevents surprises later.
Architecture & design
I design the system with production in mind from day one — not just the happy path. This includes error handling, fallback behavior, logging, and the human-in-the-loop touchpoints your team needs to trust it.
Iterative build
I deliver working software in short cycles — usually 1–2 week sprints. You see real progress early. We catch misalignments before they become expensive. The build adapts as we learn.
Evaluation & testing
AI systems need different testing approaches than traditional software. I set up evaluation frameworks that measure what matters for your use case — not just whether the model runs.
Deployment & handoff
I don't disappear after launch. I deploy to your environment, document the system clearly, train your team on how it works and what to watch for, and stay available during the critical early period.
What I build
AI Agents
Autonomous agents that reason, plan, and execute multi-step tasks. Built for reliability, not just demos.
Workflow Automation
End-to-end automation of repetitive, high-volume processes using AI at the decision points that matter.
RAG Systems
Retrieval-augmented generation — AI that reasons over your documents, databases, and proprietary knowledge.
LLM Integrations
Production integrations with OpenAI, Anthropic, and open-source models — with proper prompt engineering and evaluation.
Data Pipelines
Clean, reliable data infrastructure that feeds your AI systems with the right inputs at the right time.
Monitoring & Evals
Systems to track model performance, catch drift, and alert you when something unexpected is happening.
Is this the right engagement?
You have a clear use case but need someone to build it
Strategy is done. The problem is defined. You need a builder who understands the business context, not just the tech stack.
Your internal team doesn't have AI engineering depth
You have great engineers, but AI systems require specialized experience your team is still building. I fill the gap.
You need to move fast without cutting corners
Speed matters — but not at the cost of a system that breaks in production. I build both fast and right.
An existing AI build isn't working
You built something and it isn't performing. I can audit, diagnose, and fix — or tell you honestly if it's time to rebuild.
Have something to build?
Tell me what you're working on. Even if it's just an idea, I'm happy to give you a straight read on what's feasible and how I'd approach it.
Let's talk