Working with me
Forward-deployed engineering is a simple idea borrowed from how the best technical companies deploy their own engineers: instead of advising from a distance, the engineer goes to where the problem lives. I work inside your operation — your tools, your data, your constraints — and ship working systems, not recommendations.
It fits operations-heavy teams especially well, because the real spec of an operational workflow never survives a requirements document. The truth lives in how your team actually does the work. Being embedded is how you find it.
The arc of an engagement
- 01
Scope
A short working session to find the workflow that actually hurts — not the one that sounds impressive. We pick one, define “done,” and fix the boundaries.
- 02
Embed
I work inside your stack and sit close to the people who do the work today. The spec comes from watching the real workflow, not a requirements doc.
- 03
Ship
A production system — typed, guardrailed, observable — running on your infrastructure. Demos are a milestone, not the deliverable.
- 04
Hand off
Runbook, docs, and a walkthrough so your team owns it. The engagement ends with the system running without me — that’s the point.
Engagement types
Engagements come in three fixed-scope shapes — clear deliverables, defined boundaries, no open-ended retainers:
Operations Automation Build
Take a repetitive, error-prone workflow and turn it into a system that runs itself.
You have a workflow a person runs by hand every day — reconciling numbers, moving data between tools, chasing the same exceptions. I map it, then build it into a system that runs itself: guardrails where they matter, errors that fail loudly instead of silently, and a runbook so it’s yours to operate — not a black box.
- Workflow audit + written spec of the target automation
- Production build with guardrails and error handling
- Runbook + handoff so your team can operate it
AI Agent / Pipeline System
A multi-step AI pipeline with typed contracts between stages, not a brittle prompt.
When one prompt isn’t enough, you need a pipeline. I design multi-step agent systems with typed contracts between every stage, so each step is independently testable and the whole chain is observable — not a hopeful guess. Built to run unattended, on a schedule, with an evaluation loop that makes it sharper over time.
- Architecture: staged pipeline with typed inputs/outputs per step
- Evaluation + feedback loop so quality improves over time
- Deployed, scheduled, and monitored — not a notebook
AI Readiness Audit & Advisory
A clear-eyed look at where AI actually pays off in your operation — and where it does not.
Before you build anything, a straight answer: where AI actually pays off in your operation, and where it’s a distraction. I rank the opportunities by effort against payoff and tell you what to build, what to buy, and what to skip — a prioritized 90-day roadmap instead of a pile of hype.
- Opportunity map ranked by effort vs. payoff
- Build-vs-buy recommendation per opportunity
- Prioritized 90-day roadmap with owners and risks