Creative Producer

Brands worked with 20+ brand portfolio · 30+ campaigns a year

Selected work

Dog Food Launch Hartfelt · Kevin Hart Creative Development Specialist · 1st AD
Morning Restore Terra Mare · Marisa Tomei Creative Development Specialist · 1st AD
Rescue Story Badlands Ranch · Katherine Heigl Creative Development Specialist
Rodeo Couple DebtClear USA · Robert Herjavec Creative Development Specialist · producer
Grandpa's Day Out AMC × Coca‑Cola Producer · story & concept development
Valet Stand DebtClear USA · Robert Herjavec Creative Development Specialist · 1st AD

Decks

Concept and visual research, designed start to finish

Private · available on request

Numbskull™

Co-founder & creative director Cover only

AI integration

I build custom AI agents to out-engineer operational friction.

In daily use Pre-production agent AI systems trained directly on data from real, complex shoots produced from the ground up. 15 min total Pre-production agentone shoot, start to packet You For the Kevin Hart shoot next week, can you build a shoot packet for me? Agent That is the Hartfelt spot, Thursday the 18th. Checking readiness. Talent confirmedScripts lockedLocation set Agent Reading six sources. SlackGmailGoogle CalendarJiraGoogle DriveGoogle Sheets Agent Building the packet. Call sheetShooting scheduleCrew and cast emailsAccounting updated Agent Set up post-wrap billing? From 4 hours to just 15 min
Other agents I have built

About

Some brands disappear when you cross a border; a few do not. Moving from Ethiopia to the Dominican Republic and then to Laos taught me that the brands able to travel with you are the ones that feel like home.

That global perspective anchors my production approach. After earning my BFA in Producing from the University of North Carolina School of the Arts (UNCSA), I cut my teeth on indie features ($0 to $10M), but today I produce high-velocity DTC commercials at Golden Hippo with A-list talent. Here, the slate moves fast, and spots must prove their value against live data within a week.

I love the strategy behind that speed. The real thrill is tracking performance metrics from a live campaign, deconstructing why they worked, and immediately pivoting the operational and creative strategy to optimize the very next shoot.

Dario Seastedt

Credits

Feature and short film work alongside the commercial slate

Features
  • Haunted Hookers — Unit Production Manager
  • Local Haunts — Line Producer
  • Earth, Wind & Fire — Production Assistant
Shorts
  • Everythingeater — Producer
  • Bigger/Better/Harder — Producer
  • Box — Producer
  • The Final Cut — 2nd AD
  • Summer's End — 2nd 2nd AD
  • Good Boy — 2nd 2nd AD

Building a shoot used to mean assembling the same five documents by hand from six different places. It now runs from one command, and the time it takes went from about four hours to about fifteen minutes.

The approach

Trigger

/build-call-sheet [Shoot Name] on [Date] once talent is confirmed, scripts are locked, and the location is set. The agent checks that readiness before it starts rather than producing a half-built sheet.

The pipeline

  1. Gather from chat, the production schedule, issue tracking, mail, calendar, and the prep and script docs
  2. Confirm the shooting address against the source of record
  3. Ask clarifying questions only where something is genuinely missing, front-loaded in one message
  4. Calculate cast call times backward from the schedule
  5. Apply smart defaults for the fields that are the same every time
  6. Build the call sheet, including weather, nearest hospital, and the ticket link
  7. Build the schedule tab with the correct colour coding
  8. Export the sheet as a PDF
  9. Draft the crew email and every talent email individually
  10. Write talent and hair-and-makeup rows into the freelancer payment record

Source priority

Six systems disagree constantly. The workflow declares an explicit priority order, so when two of them contradict each other the agent resolves it the same way every time instead of guessing.

Delegation

A casting-researcher subagent reads Gmail casting threads end to end and returns a clean table of confirmed talent with roles, scenes, and reps. It never passes raw email bodies back. That keeps the main context small enough to finish the build, and it means far less personal data moves around than if the whole thread were pulled in.

Integrations

Google SheetsGoogle DocsDrive GmailCalendarIssue tracking SlackWeb searchPDF export

Templates

Crew and talent emails render from HTML templates with named variables. The template headers carry the formatting rules, so the tone stays consistent whoever runs it.

Most ad scripts get written from taste. This one is only allowed to build from creatives with real evidence behind them, and it is explicitly forbidden from treating a subjective rating as proof that an ad worked.

The pipeline

  1. Pick the production path, polished spokesperson or clean user-generated
  2. Pick the target offer
  3. Harvest internal winners from the reporting available to me
  4. Harvest external winners from competitors
  5. Name the mechanism, the actual reason the winning ads persuade
  6. Add a recency layer so the script is anchored to now
  7. Write the script as a two-column script and visual table
  8. Secure a production slot and log the outcome

Research subagent

An ad-performance-researcher subagent reads the internal reporting end to end and returns a compact brief instead of a raw dump: which creatives are worth learning from, the angle each one uses, and what is queued for testing.

Finding competitor winners without a paid tool

A written playbook using the public ad library and a longevity heuristic. An ad still running after months is being paid for because it works, and that is a signal available to anyone willing to look properly.

The guardrail I am proudest of

Every source gets audited before the agent is allowed to lean on it. Where a signal cannot actually support the conclusion someone wants to draw from it, the agent is instructed to say so rather than imply otherwise. A tool that quietly launders a weak signal into a confident claim is worse than no tool.

Post-wrap paperwork arrives in the inbox in no particular order, from people who invoice differently every time. This closes the loop without ever being the thing that sends money.

How it runs

The sequence

Layered mail search, a pre-flight check for which documents are actually missing, download into the forms folder, then update only the document-tracking columns.

Where it stops

The agent gathers and files documents. It never drafts the email that forwards them to accounts payable, and it never touches the release, status, or approval columns. I write that email and mark those columns myself. Anything that moves money keeps a person in it.

I wanted to know whether I could take a product idea the whole distance on my own, so I built it. Point a phone camera at a barcode and it returns a score, the reasoning behind it, and something better to buy instead.

The idea

Scan, score, swap. Dr. Gundry's audience already reads labels and mostly cannot tell which products actually fit the philosophy they follow. The app rates any scanned product from 0 to 100 with a plain red, yellow, or green verdict, explains which ingredients were flagged and why, and recommends an alternative. Every poor score is a place a customer can be helped and a product can be sold, which is the same moment.

Built, not mocked up

React and TypeScript on Vite, styled with Tailwind, routed across five screens: onboarding, scanner, result, food guide, and history. Barcode decoding runs in the browser through the ZXing library, so it works from a phone browser with no app store in the way. The dev server runs over HTTPS because camera access requires a secure context, which is the sort of thing you only learn by actually shipping it.

ReactTypeScriptVite TailwindReact RouterZXing

The scoring rubric is a document, not buried in the code

I wrote the rubric as a separate reviewable spec so someone qualified on the nutrition side can check the logic without reading a codebase. I am confident about the build. I am not the right person to be the final word on what counts as a good ingredient, and the architecture says so.

Educational, not alarmist

The tone rule is written into the product spec: explain why something is flagged in Dr. Gundry's voice, and never manufacture a concern to land a sale. A scanner that scares people into buying works once. One that teaches them something is the one they keep on their phone.

Why it is on this page

Not because a producer needs to write React. Because taking something from an idea to a spec, a rubric, a working build, and a pitch is the same job as taking a brief to a finished spot, and the second one is easier to believe once you have seen the first.