I design and ship AI agents, automations, and command centers for supply chain, logistics, e-commerce and operations teams — turning complex workflows into measurable, autonomous infrastructure.
I work at the intersection of strategy and engineering: meeting with leadership to map the operating model, then designing AI agents, evals and automation that actually move P&L. My background spans computer science, business strategy, and applied research — and I've spent the last decade shipping production systems with operators who can't afford toys.
I'm founder-minded, allergic to over-engineering, and obsessed with the rough edges where models meet messy real-world ops.
End-to-end automation pipelines that wire LLMs, RPA and integrations into the systems your team already lives in.
Tool-using agents with planners, evals and guardrails — designed for narrow operational jobs, not chat demos.
Mapping, redesign and execution of cross-tool workflows — from intake to fulfillment, with audit trails operators trust.
Slotting, dispatch, ETA prediction, anomaly detection — applied AI for the people who actually move the boxes.
Internal tools, dashboards and customer surfaces built on a modern stack — Next.js, edge infra and AI-native UX.
Roadmaps, build-vs-buy, model evals, and exec readouts — translated for boards and operators, not just engineers.
Reinforcement-learning slotting engine for a 380K sqft 3PL — re-locating SKUs nightly based on velocity, affinity and pick-path cost. Cuts pick travel by 31%.
Multi-channel ads agent that pauses, scales and clones campaigns based on ROAS bands and creative fatigue.
Bid, keyword and ASIN-level optimization across SP/SB/SD with weekly playbook adjustments.
Streaming anomaly classifier across order, inventory and ops events — flagging fraud, misroutes and supplier drift.
Single pane of glass for ops leadership — agent activity, KPI swings, exception queues and decision audit, with one-click human override.
Voice + chat agent triaging service requests, dispatching field crews and predicting ETAs across a 200-vehicle fleet.
Mid-size 3PL serving DTC brands. Replaced quarterly slotting reviews with a nightly RL agent reading WMS + order velocity.
Voice + chat dispatch agent, fully integrated with field-service software. Live in 9 weeks, payback in 3 months.
Unified attribution, anomaly flags, and an agent that reallocates spend daily based on contribution margin — not ROAS theatre.
The pattern is uncannily consistent: pilots ship in two weeks, win the demo, then implode against real ops. The cause isn't the model. It's the absence of an evals-first operating model and a clear human-in-the-loop contract. Here's the playbook I run with every enterprise client.
A short take on why operators sleep on slotting and the dollar math behind nightly autonomous re-locates.
How to sequence platform spend so you don't pay a SaaS tax twice when the substrate shifts under you.
If your evals don't reflect production, your agent doesn't ship. A walkthrough of the eval suite I deploy on every project.
If you run an operations-heavy business and you're tired of pilot-ware, let's talk. I take on a small number of engagements per quarter — usually 6–14 weeks, embedded.
Building in public.
Operating in private.
Most of my essays, breakdowns and ops experiments live on LinkedIn — where the operators actually read.