You will get an AI product audit that finds why your AI feature isn't production-ready
Rising Talent
Project details
You shipped an AI feature, or an agency shipped one for you, and something is off. Wrong outputs reaching users, costs creeping, no way to tell if a prompt change made things better or worse.
I audit the whole pipeline: prompts, model choice, output validation, failure modes, cost structure, monitoring. You get a written report with the three to five changes that matter most, ranked by impact, in plain language you can hand to your team (or back to your agency).
My own production pipeline runs an eval-gated editorial system at catalog scale for under a dollar a month in model spend. I hold audits to the same standard: specific, measurable, no hand-waving. Day to day I work with Claude, OpenAI, Llama, Whisper, and Apple Intelligence, in Cursor, Claude Code, and VS Code.
Background: 25 years of design-led product work, Apple Design Award winner, a native macOS app currently live in the Mac App Store, and ten years running my own consumer brand, so I know what it is like to be the operator paying for technical work you cannot fully evaluate.
I audit the whole pipeline: prompts, model choice, output validation, failure modes, cost structure, monitoring. You get a written report with the three to five changes that matter most, ranked by impact, in plain language you can hand to your team (or back to your agency).
My own production pipeline runs an eval-gated editorial system at catalog scale for under a dollar a month in model spend. I hold audits to the same standard: specific, measurable, no hand-waving. Day to day I work with Claude, OpenAI, Llama, Whisper, and Apple Intelligence, in Cursor, Claude Code, and VS Code.
Background: 25 years of design-led product work, Apple Design Award winner, a native macOS app currently live in the Mac App Store, and ten years running my own consumer brand, so I know what it is like to be the operator paying for technical work you cannot fully evaluate.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, Automatic Speech Recognition, Conversational AI, Natural Language GenerationAI Development Language
PythonAI Tools
Hugging FaceAI Models
ChatGPT, GPT-4, LLaMA, WhisperWhat's included $2,500
These options are included with the project scope.
$2,500
- Delivery Time 7 days
- Number of Revisions 1
- Model Documentation
- Model Testing & Optimization
- Prompt Engineering
About Aaron
Product Designer + Builder | Production AI | Apple Design Award
Chattanooga, United States - 10:42 pm local time
Most recent build is a production AI pipeline, the Steadcast Knowledge Engine. Queue-based Whisper transcription on a self-hosted GPU, an eval suite that gates every model output before it persists, mixture-of-models routing, cost ceilings, monitoring. It runs autonomously at catalog scale for under a dollar a month in model spend. That is the difference between a demo and production, and it is the standard I hold client work to.
What I do for clients:
- AI features that have to work in front of real users (eval gates, fallbacks, cost control)
- Native macOS and iOS product design and build (SwiftUI, App Store review passed)
- Product strategy from someone who has run a P&L, not just a design file
- Rescue work: "we built it with AI tools and it's broken" is a brief I like
I have been the non-technical founder trying to evaluate a technical quote. I will not do that to you. Plain language, working software, no jargon walls.
Steps for completing your project
After purchasing the project, send requirements so Aaron can start the project.
Delivery time starts when Aaron receives requirements from you.
Aaron works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff call
30 minutes. You walk me through the pipeline and the symptoms; I confirm scope and what access I need.
Pipeline audit
I review prompts, model choice, output validation, failure modes, cost structure, and monitoring against production standards.