Lucas Cioffi — Agentic Operations for Mid-Sized Companies

§ 01 — About

A senior engineer who shows up, ships, and gets out of your way.

I've spent two decades building software for companies that depend on it. Netflix's creative team uses tools I built. Mudflap's fintech systems run on code I wrote. I co-founded an event platform that grew to 200,000 users, and built a generative-AI concierge with retrieval augmented generation (RAG) and vector search.

Starting my career, I was an Infantry Captain in the US Army, graduating from West Point and Ranger School. I served as the executive officer for a 125-person headquarters company, and led soldiers on their first combat mission, a three-day, 500-kilometer convoy from Kuwait to Baghdad. I was assigned as base security officer for a forward operating base of 1,200 American soldiers and 100 civilians which experienced elevated rifle, RPG, and mortar attacks.

Now I'm focused on something more direct: helping the mid-sized companies and family businesses that actually run America — distributors, manufacturers, trade contractors, regional logistics operators — bring practical AI into the office without the hype, the consulting bloat, or the year-long implementations.

“
That experience is why I build software the way I do — for systems that have to actually work, under real-world stress, with consequences if they don't.

Education

West Point, B.S.
Systems Engineering

Service

US Army Ranger
Combat Veteran

Tech Stack

Rails · Python
Claude · RAG

Based In

Hartsdale, NY
NYC Metro

§ 02 — The Problem

Your operations team is doing by hand what software should do.

Your team is buried in paperwork

Shipping documents, invoices, purchase orders, customs paperwork — all flowing in from different sources, all needing to match. Someone on your team spends days each month making sure they do.

ii.

Errors cost real money

A missed mismatch becomes a chargeback. A wrong invoice becomes a customer dispute. The work to prevent these errors is exactly the work nobody wants to own.

iii.

Off-the-shelf software doesn't fit

You've tried it. It either does 10% of what you need or 1000% of what you need, and the rest is still your team's problem to solve.

§ 03 — What I Build

Production systems, not proofs of concept.

01 / 04

Automatic paperwork matching

Shipping docs match orders. Invoices match POs. Customs paperwork ties out. The work your team used to spend days on each month happens overnight — and a person only gets pulled in for the handful of exceptions that actually need a human call.

02 / 04

Plain-English business reporting

You ask “what did we ship to our top ten customers last month, and which ones are trending down?” and get an answer in seconds. No more waiting on a report, pulling exports out of QuickBooks, or building another spreadsheet just to know what's going on.

03 / 04

End-to-end office workflows

The full back-office process — order in, paperwork checked, invoice cut, exceptions flagged, customer updated — running on its own. The people who used to babysit it get promoted to the work only humans can do.

04 / 04

AI strategy for your business

A senior engineer in the room with you and your leadership team, telling you the truth about what AI can and can't do for your business right now — what's worth building, what to ignore, and where to start so you see results in weeks, not years.

§ 04 — The Approach

A four-week path from idea to running code.

Week 01 — Discovery

Find the real bottleneck

I sit with your operations team and trace the actual workflow. Not the org-chart version — the real one, with all the workarounds. We identify the highest-leverage process to automate first.

Week 02 — Design

Architect the system

I map the agent design, data flow, exception cases, and integration points. You get a clear architecture document and an honest assessment of what will and won't work.

Week 03 — Build

Ship a working prototype

A real, running system — Ruby on Rails dashboard, Python agents — handling your actual documents, your actual edge cases. Not a slideware demo.

Week 04 — Handoff

Deploy and document

Production deployment, runbooks, monitoring, and a knowledge transfer to your team. You own the code, the data, and the system from day one.

§ 05 — What an Engagement Looks Like

The kind of work I take on, in plain terms.

The scenarios below describe the shape of a typical engagement — the kind of business, the kind of problem, the kind of result. Specifics vary, but the pattern holds: a few weeks of focused work, a system that runs quietly in the background, and hours back for the people doing the work that actually matters.

A regional distributor

The shipping paperwork matches itself.

An 80-person wholesale distributor whose AR team spends three days each month matching shipping documents against customer orders and invoices. We build a system that auto-matches the routine 85–90% and flags the rest for a human to review in minutes, not days. The team gets two full weeks back per quarter.

Typical timeline — 4 weeks

A family-owned manufacturer

The owner asks a question, and gets an answer.

A second-generation manufacturer where the owner waits days for the bookkeeper to pull custom reports out of QuickBooks and the production system. We build a plain-English dashboard the owner can use directly — “Which jobs are running over budget this month?” — with answers in seconds. The bookkeeper stops being a bottleneck. The owner stops flying blind.

Typical timeline — 4 weeks

A specialty trade contractor

The job-cost reconciliation just happens.

A trade contractor with 40 field employees whose office manager spends every Friday reconciling subcontractor invoices, material costs, and labor hours across active jobs. We build a workflow that ingests the paperwork, matches it to job codes, and flags discrepancies. What used to take a full Friday now takes thirty minutes — and the discrepancies actually get caught.

Typical timeline — 4 weeks

A logistics operator

An advisor in the room who's actually built this stuff.

A regional 3PL whose IT lead has been asked by the owner to “figure out the AI thing.” They have an engineer but no agentic experience. I work with them as an embedded advisor for 6–8 weeks: architecture, tool selection, design reviews, and a working prototype the team can take from there. They get to production without the false starts.

Typical timeline — 6 to 8 weeks

§ 06 — Behind The Work

My Team

Design & delivery, handled.

Every engagement is supported by a small team of specialists I trust. They handle design, project management, and delivery rigor — so the systems we ship don't just work, they're actually adopted by the operations teams that need them.

Sandra Nam

Design & Project Delivery

Sandra leads design and project delivery — translating messy operational reality into interfaces that real teams adopt on day one. She partners with me on every client engagement to ensure scope is clear, work ships on schedule, and the dashboards we build are ones operations teams actually want to use.

Get your team's time back from work the computer should be doing.

A senior engineer who shows up, ships, and gets out of your way.

Your operations team is doing by hand what software should do.

Your team is buried in paperwork

Errors cost real money

Off-the-shelf software doesn't fit

Production systems, not proofs of concept.

A four-week path from idea to running code.

Find the real bottleneck

Architect the system

Ship a working prototype

Deploy and document

The kind of work I take on, in plain terms.

The shipping paperwork matches itself.

The owner asks a question, and gets an answer.

The job-cost reconciliation just happens.

An advisor in the room who's actually built this stuff.

My Team

Design & delivery, handled.

Boring tech, built well.

Tell me about the work that's eating your week.