Service
I take an idea to a deployed product you can put in front of real users — frontend, backend, auth, payments, and deploy, built by one person who owns the whole thing.
A working product at a real URL that real users can sign up for, not a prototype that demos well and cannot take payment. That means authentication, user roles, a database design that will not need replacing at month six, billing if you are charging, and a deploy pipeline from week one.
You get one developer owning frontend, backend and deployment, so nothing falls between contractors — which for a product at this stage is a feature rather than a limitation. The handoffs between a designer, a frontend contractor and a backend contractor are where small projects usually lose weeks.
The main job at this stage is deciding what not to build. Most first specs contain about three products, and the fastest way to miss a launch date is to build all of them at forty percent. I scope to the features that prove the idea and skip the rest — and I tell you when a feature is a bad idea before building it, not after.
I push back on features that exist because a competitor has them. A settings page with twenty toggles, a notification system nobody asked for, and an admin dashboard for a userbase of zero are all common ways to spend a month without learning whether the product works.
What I do not cut: authentication and tenancy done correctly, because retrofitting them is genuinely expensive; error handling on anything touching money; and a deploy pipeline, because a product you cannot ship on a Tuesday afternoon is one that stops improving.
CodexGenAI is an AI content studio I designed and built solo in six weeks — LLM generation with validated output contracts, cross-platform scheduling, Postgres with row-level security, and sentiment analytics. HireOS is an AI resume-optimization platform with a Chrome extension and a multi-provider LLM backend.
ChicagoDrivers is a two-sided marketplace with separate rider and driver surfaces, vehicle and maintenance tracking, and its own content and email systems. Different domains, same shape of problem: decide what matters, build that properly, ship it.
A focused MVP is typically a four-to-twelve week engagement depending on how much of the product is settled when we start. If the spec is still moving, I would rather run a short paid discovery than write a fixed quote against a brief that will change in week two — you get a scoped plan and an estimate out of it, and you are free to build it with someone else.
I work remote-first from Lahore and overlap daily with US, UK, Canadian and Australian founders, and I take on two new projects at a time so each one gets real attention. You get weekly demos of working software rather than status documents.
Scope decides it, so I price per engagement rather than off a rate card. What moves the number is how settled the product is: a clear spec with decided flows costs a fraction of one we are discovering as we go. If you are not ready to commit, a short paid discovery gives you a scoped plan and a real estimate, and you can take that plan elsewhere if you prefer.
Four to twelve weeks for a focused product. CodexGenAI — LLM generation, multi-platform scheduling, Postgres with row-level security, and analytics — took six weeks as a solo build. The range is wide because the variable is scope discipline, not typing speed.
In: the core flow that makes the product worth showing someone, auth and user roles done properly, payments if you are charging, and a deploy pipeline. Out, usually: admin dashboards for a userbase of zero, settings pages full of toggles nobody requested, and features that exist because a competitor has them. Auth and tenancy never get cut, because retrofitting them later is one of the genuinely expensive mistakes.
Yes, and it is a fine outcome. You keep the repo and the deployment account — there is no lock-in to me or to agency tooling. I write commits that explain themselves and a written handover at the end, specifically so bringing it in-house is a decision rather than a rescue project.
Yes, though I will ask what the feature is allowed to get wrong before agreeing it belongs in a first version. AI that is core to the product — generation, extraction, matching — earns its place. AI bolted on because it is expected usually adds cost and latency to a product that has not yet proven the basics work. I have shipped two AI products of my own, so this is not a first attempt on your budget.
Whatever you need. Some founders take the handover and continue with their own team; others keep me on a weekly retainer while the roadmap is still moving. I do not require an ongoing commitment to hand over a finished product, and I will say so if a retainer is not worth your money.
An AI content studio for creators and teams: generate multi-slide carousels, schedule posts across platforms, and track engagement with sentiment analysis.
Read the case study →An AI resume-optimization platform — tailors resumes to target roles, renders clean PDFs, and ships with a Chrome extension.
Read the case study →A driver marketplace for Chicago — airport transfers and event bookings on the rider side, vehicle and maintenance tracking on the driver side, with blog, newsletter, and announcement email built in.
Read the case study →A 15-minute call is usually enough to scope it. If I am not the right fit, I will tell you on the call.