imagile
AI Writes Code. Creativity Writes Software.
When AI handles construction, the skill that matters isn't typing speed or syntax knowledge. It's taste.
For founders & domain experts
You know the industry. I build the software.
You've spent years inside a business and can see the product it's missing. I turn that into working software — scoped, built, and launched by one senior engineer, explained in plain English the whole way.
Who this is for
People who know exactly what should exist — and need someone to build it
Most often that's a domain expert with a startup idea. You've spent a career in insurance, logistics, healthcare, construction — some industry where you can see the product everyone needs and nobody has built. You don't need to learn to code, and you don't need to gamble on a technical co-founder on day one. You need a first version real customers can use, built by someone who's shipped software for over a decade and can explain every decision without the jargon.
It's also for established businesses past the strategy conversation — an internal tool nobody else will prioritize, an integration between systems that don't want to talk to each other, a customer-facing product that has to hold up under real load. If the deliverable is working software, this is the service.
It's not for teams that want a headcount-shaped hire, or a body to sit in standups indefinitely. One senior engineer, scoped work, a defined handoff — that's the shape.
What happens
Scope it, build it, ship it — same person the whole way
Every build starts with the scope: what it needs to do, who uses it, and what "done" actually means — written down in plain English before any code gets written. The big decisions get made up front and explained, not discovered three months in. Then it gets built, with the ability to ship updates continuously from day one, so version two costs a fraction of version one.
Under the hood it's the same enterprise-grade technology large companies run on (.NET, Azure, AWS) — but you don't have to care about any of that. What you have to know is that it launches, holds up, and can grow with you.
This isn't theoretical. Imagile-app and Context Overflow are public — you, or any engineer you trust, can read the code and judge the work directly instead of taking my word for it. That's the standard the software you're paying for is held to as well.
If your product needs AI inside it, I bring in the industry standards from OpenAI and Anthropic — the technology behind ChatGPT and Claude — and pick the setup that fits your costs, your customers, and your compliance requirements.
What you walk away with
Production software, not a prototype
Working, deployed software
Running in your environment, under your control — not a demo folder or a Figma file.
A way to keep shipping
The next improvement releases as easily as the first — no rebuild, no starting over.
Documentation your next hire can run with
Every decision and how-it-works written down in plain language, not left in one person's head.
How pricing works
A number in writing before any code gets written
| Engagement | How it's priced |
|---|---|
| Advisory / hands-on hourly | Hourly, rate quoted up front |
| Day engagements, remote or on-site | Day rate, quoted up front |
| Production build with integrations | Scoped after discovery |
| Ongoing retainer | Scoped to your cadence |
Advisory and hands-on work is hourly; a build gets a fixed scope and a fixed number, both agreed before any code is written. Most engagements start with a short AI transformation strategy session — a focused conversation and a written recommendation, credited toward whatever comes next. Remote work is priced the same as the work; on-site carries a day-rate premium plus travel at cost, never a surprise change order. Ask and you'll get the number the same day, in writing.
Related reading
From the blog
Azure and .NET: The Boring Stack That Wins
Performance, talent pool, and secretless authentication. Why we default to Azure and .NET for almost every client project.
Your Cloud Migration Failed Because You Skipped the Hard Part
Cloud-native isn't an infrastructure problem. It's a development problem. Most migrations fail because they treat it like the former.