“A working prototype in days” sounds, to anyone who has commissioned enterprise software, like a claim that should come with an asterisk the size of a contract. Builds take months. Discovery alone takes weeks. Where, exactly, did the time go?
Here’s the honest walkthrough — a composite of how our recent engagements have actually run, so you can judge for yourself what’s faster and, just as importantly, what isn’t.
Monday: the discovery call
Thirty minutes, with engineers. You describe the problem — say, your operations team spends two days a week reconciling deliveries against orders across an ERP, a warehouse system and a spreadsheet that has become load-bearing.
We ask the unglamorous questions: where does the data live, who touches it, what are the exceptions, what would “working” mean in numbers. You get a straight answer on feasibility before the call ends.
What’s different from the old world: nothing. This part was never the bottleneck. It stays human because it’s where the judgement is.
Tuesday–Thursday: scope, in writing
A short document: what we’ll build, what it connects to, what the prototype will prove, an indicative price. Not a 40-page functional spec — those exist to manage the cost of change, and when change is cheap, they’re mostly ceremony.
The next week: the prototype
This is where AI-assisted delivery earns the name. A senior engineer — one who has integrated ERPs since before your current one was installed — works with AI tooling to stand up a working system against a copy of your real data. What took a team a quarter now takes that engineer days.
The judgement calls stay with the human at every step: the architecture, the security model, what the exceptions queue should do, which of your three “duplicate” supplier records is canonical. The AI produces the volume — scaffolding, integration code, tests, the hundredth variation of a data-mapping function. The engineer reviews and owns every line, the same way they always have.
You see it on a screen at the end of the week, running on your actual problem. Not wireframes. Not a deck. Software.
The decision point that didn’t used to exist
Here’s the structural change. In a traditional build, the first time you see working software, most of the budget is spent. Misunderstandings surface at the most expensive possible moment.
Now the prototype lands when you’ve risked days, not quarters. If it’s wrong, it gets corrected — or killed — for the price of a week. The most dangerous failure mode in bespoke software, confidently building the wrong thing, gets caught at the cheapest possible point.
Weeks two to six-ish: production
The prototype graduates: hardening, security review, integration testing, exception handling, monitoring, documentation, training. This is deliberate engineering and it is not where we cut corners — it’s where 25 years of enterprise habits do their work. AI accelerates it; it doesn’t skip it.
Then it goes live, with our team supervising — and supporting it for as long as you want us to.
What this means if you’re buying
The two questions worth asking any firm claiming AI-assisted speed: who reviews the code (the answer should be senior engineers who own it), and show me the prototype step (the answer should not be a slide). Speed without the second is marketing. The second without the first is risk.
We’re happy to be asked both. Monday’s available.