Before you book

SaaS means you adapt to the software — you sign up for a tool that thousands of other businesses use the same way, and you change your workflow to fit how it works. Custom means the opposite: I build a system around your existing workflow, not the other way around. "Couture" is the same idea borrowed from fashion — a tailored suit built to your measurements instead of buying off-the-rack. No two emrAnI builds are identical because no two businesses run identically.

Try it yourself. Open ChatGPT and type "make me an app that handles customer invoices." You won't get an app. You'll get instructions — open Terminal, install this, run that command, paste this config, sign up for that service. ChatGPT is a teacher, not a builder. It can explain anything you want to learn; it cannot deliver a finished product. The real work is taking what AI can teach and turning it into a deployed, monitored system running 24/7 — which requires hours of organization, a structural and ethical framework that keeps the AI from going off the rails, and the human creativity to actually solve the problem. AI is excellent at deterministic, binary decisions. It is terrible at multi-fork subjective decisions that require taste — and almost every real business decision requires taste.

You could. ChatGPT will absolutely teach you how. The question is how much your time is worth. A basic setup — email, payments, automation — is 80 focused hours minimum, including the learning curve on email authentication, OAuth admin policies, payment processor verification, deployment, and monitoring. If you'd rather spend those 80 hours running your actual business, hiring is cheaper than learning. If you'd rather learn, my Guide page lays out every step free. I get paid to deliver the outcome — not to gatekeep the knowledge.

Zapier and Lindy are great when your workflow fits a pre-built block. They connect well-known apps using templates — Salesforce to Slack, Gmail to a spreadsheet — and they handle that cleanly. They break when your workflow doesn't fit a template, when decision logic needs to read nuance from an email, or when AI judgment needs context a pre-built block can't see. Those platforms also lock you in: monthly subscription forever, and if their pricing or product changes, your business changes with it. Custom builds are yours. They run on your own cloud account, you own the code, and you don't pay per task or per workflow.

Fair question. Vibe coding is when someone pastes ChatGPT output into a file, hits run, and ships whatever happens — no review, no testing, no monitoring. It works for a weekend prototype and falls apart in production. Real engineering work today is different: I direct AI to write code, then I review every piece, test it end-to-end, deploy it on infrastructure I understand, and add monitoring so I know within minutes if something breaks. The skill is knowing what to ask for, what to reject, and what to make fail loudly when conditions change. Fifteen years of creative-studio work is where I learned to spot when something is almost-right but actually wrong.

Twenty-five years across tech and creative work means I've held every role an agency staffs — designer, developer, QA, project manager, copywriter. That's the unicorn part: I know each field well enough to direct the AI inside it, recognize when something is off, and suggest a different path when the obvious one is wrong. AI collapses the team because I am the team — just running each role through AI instead of five different people. No Slack threads, no handoffs, no account managers translating between client and developer. One brain holds the whole project from first call to deployed system, decisions land faster, and nothing gets lost in translation. The tradeoff is fewer clients at a time — which is the point of couture.

You own everything. The code lives in your own cloud account (Google Cloud, AWS, or whatever fits your stack). The data lives in your own spreadsheets, your own database, or your own Workspace — never on a server I control. The credentials are yours. If you ever want to take it to another developer, hand them the cloud account and they can pick up where I left off — that's the whole point of building on standard infrastructure instead of a proprietary platform. There is no subscription to me, no per-task fee, no kill switch. If I disappeared tomorrow, your system keeps running.

Yes, AI can break things — which is exactly why most of what I build does not have AI running in the live system. Lazy developers stuff AI into every layer of a product because it sounds good in the pitch, then surprise you with monthly API bills, slow response times, and breakage every time a model updates. My default is the opposite: AI does the heavy lifting at build time, then human-written deterministic logic runs the system day to day. Where AI does belong in the runtime — reading nuance from an email, classifying messy input — I tell you upfront, show you the API cost, and build fail-loud safety so a shifted model output creates an explicit error you can see instead of silently corrupting your data. You always know what AI is doing in your system and what it costs.

Because the work isn't a SKU. Custom AI automation scales by scope — what you actually want built, the data sources it touches, the failure modes that matter to you. Pricing it from a webpage would be like a tailor listing suit prices without measurements. The $99 Google Workspace setup is the exception, and it's right on the homepage, because that one is a fixed product I deliver the same way every time. Custom websites start at $5,000. Custom AI automation is scoped per project — a 20-minute conversation tells me what it actually takes to build.

You are who I work with most. I specialize in people who are AI-curious — they sense the technology will matter for their business but can't picture what it actually does for them yet. The first and most important thing I do is help you identify the problem itself. Most clients come in with a vague "I should be using AI somewhere" and leave the first call with a specific, named workflow worth automating. Sometimes it's the thing they thought it would be. Often it's something they never noticed because the friction had become invisible. There is no homework before the call — the diagnostic conversation is the deliverable.