Who I am
I’m Jeremy Dill, a Creative Technologist and Senior Multidisciplinary Designer with 18+ years across brand, web, motion, 3D, and digital production. I understand the creative work first, then turn the repeatable parts into software.
Add Your Heading Text Here
Add Your Heading Text Here
Add Your Heading Text Here
Add Your Heading Text Here
Add Your Heading Text Here
Add Your Heading Text Here
AI Creative Producer · Commercial Product Systems
48 products. 60 minutes. One source.
Hi, I’m Jeremy. I build novel AI creative pipelines that deliver massive throughput from minimal source material, at remarkable speed and very low cost.
The reel shows 48 product directions developed from one Playcio character in a single 60-minute production run.
Inspect the complete product lineSource character → product family → campaign-ready visual system
Problem I solve
Creative teams are being asked to produce more work, across more formats, without adding more production drag. AI can generate output. The harder problem is making that output repeatable, controllable, and usable at scale.
What I build
I build AI-powered creative systems that turn source material, briefs, and constraints into repeatable production. The systems can handle direction, generation, variation, validation, and reuse so people spend less time repeating production work.
Commercial production reel
Finished commercial work · concept through final delivery
AI Commercial Production
Commercials Have never been faster or easier.
I turn product briefs into campaign-ready commercials.
Built for teams that need more high-quality video without more vendors, handoffs, or production drag. The reel on the left shows the finished work.
AI Creative Decision Assurance
I make AI-assisted creative work safer to trust, easier to inspect, and less painful to run.
AI Creative Control
Creative chaos gets expensive fast.
I’m a Creative Technologist building control and automation systems for AI-assisted creative production. When teams generate more work, they also create more to review, validate, approve, track, and fix. I build the layer that catches weak output, preserves decisions, connects ownership, and turns repeat creative work into production systems a team can actually run.
Catch weak work before it ships.
Claims, assumptions, and outputs are challenged before they become revisions, rework, or client problems.
Failure to proof
Make decisions inspectable.
The system records what survived review, what changed, and why, so important decisions do not disappear between tools and conversations.
Decisions to evidence
Keep ownership attached to the work.
Briefs, assets, reviews, blockers, approvals, and owners stay connected so every deliverable has a status, a reason, and a next action.
Chaos to control
Turn repeat work into software.
Once a process works, its rules, checks, handoffs, and recovery logic become reusable instead of being rebuilt every time.
Repeat to system
AI can scale bad work just as easily as good work. Control is what makes the speed useful.
Fewer
manual review loops
Faster
brief-to-approved delivery
Cleaner
validated deliverables
Safer
repeat AI production
“ Less production babysitting because the system shows what survived, what was decided, who owns it, and what happens next. Proof to inspect ScopeLogic is a working reasoning and decision-control system built to pressure-test output, preserve decisions, expose unresolved issues, and make AI-assisted work easier to trust. Inspect ScopeLogic
The operating layer
□
Stress
○
Decisions
✦
Systems
△
Status
#
Ownership
↻
Flow
Tools
The AI Creative Control Problem
AI creative output is exploding. Teams cannot control it. They cannot repeat it. They cannot QA it. They cannot safely hand it off.
AI output is exploding. Teams can’t control, repeat, QA, or safely hand it off.
Interactive role-to-proof map
Choose a role. See the proof.
Select one or more roles in the top row. The lines reveal the projects below that prove each capability.
1 — Choose a roleSelect more than one to combine them
Selected roles / 01
What changes for the team
Controls exploratory AI output until it becomes consistent and reproducible.
2 — Inspect the projects that prove it
Tek Sports Insights
Product architecture, naming, seven homepage directions, and a branded sports asset system.
Inspect proofScope Logic
Variation architecture, prompt controls, QA gates, rejection logic, and approved output families.
Inspect proofEmotion + Motion
A repeatable translation layer from emotional intent to motion behavior and production rules.
Inspect proofPlaycio
Concept development, visual systems, interactive prototyping, and production-ready experiments.
Inspect proofDesign, Motion & 3D
Direct evidence of taste, execution range, finishing standards, and hands-on craft.
Inspect proofWeb + Production
Customer-facing interfaces and campaign systems carried from idea through delivery.
Inspect proofAI Execution Control
360° audit before agents run
Scope Logic · system proof
Bad direction gets caught before production starts.
AI is moving faster than people can inspect what it produces. I built Scope Logic to use AI as an auditing system before it becomes a production engine.
Four-quadrant reasoning creates a complete view of the problem, while an equation layer converts linguistic ambiguity into deterministic decision data before anything runs.
Unclear
Audited
Ready
Loose Brief
Messy Notes
AI Prompt
Client Request
360°
Four-Quadrant Audit
Builds the full view
Forces the model to inspect the problem from four angles before it acts.
Objective Locked
Ambiguity Resolved
Ready to Run
Live
Problem mapped
Reasoning quadrants
4
Control gates
5
Source of truth
1
360°
Problem view before execution
A→D
Ambiguity converted into deterministic data
Any
Domain, workflow, or decision type
Use intelligence to audit the work before automation accelerates it.
