AI product engineering.
Brief to shipped software, by a team that has done it five times for itself in twelve months. Your accounts, your IP, no lock-in.
What the practice does
-
Discovery & a scoped, priced brief
Week one ends with a written brief, a capability map, and a pilot scope with a price. You know what you're buying before you buy it.
-
Full-stack build, agent-accelerated
Agents draft code, tests and documentation; engineers direct and review. The acceleration is real and so is the accountability.
-
Working software every week
Not decks — deployments. You see the product grow weekly, and the decision log records why it grew the way it did.
-
Launch, measure, iterate
Ship, watch the real numbers, adjust. Handover is documented — or we keep operating it with you.
The stack this practice runs on
Marks are the honesty grammar: ● in production in our products or our own shop · ◐ under evaluation. Beyond these: the major model providers — vendor-honest, not vendor-loyal.
The same discipline that shipped five products in twelve months, applied to yours. Read the method →
Asked about this practice
Who owns the IP?
You do. Your accounts, your repositories, your IP — from the first commit. No lock-in is a design decision, not a discount.
How fast is "agent-accelerated" really?
Our own record is public: five products shipped in twelve months, self-funded. Client timelines depend on scope — which is why week one ends with a written plan and price.
Do you take over from an existing team or vendor?
We start where the practice starts: the legacy audit and integration map show what exists, and the decision log keeps any handover honest in both directions.
What do we see during the build?
Working software every week, test runs, and a decision log. If a week produced nothing you can click, we owe you an explanation.
Five self-funded products are the audition. Open any of them. Open the products →
Tell us what you're building.
Made with love in Naya Bharat