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A row of identical machined metal parts laid along a dark workshop bench under a thin ascending band of light.

AI-native delivery

Productivity gains we can show.

What assisted engineering actually changes on a project, how we count it, and the places it costs more than it saves. Written without a vendor benchmark.

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Every tool vendor has a percentage. None of them measured your project. Here is how we count it on ours, and what we have found.

Identical machined metal parts laid in a measured row along a dark bench beside a pair of callipers.

Where projects like this go wrong

  1. What we count

    Cycle time from ticket to merged, review time per change, defect escape rate, and rework — the share of shipped work that comes back after release. A short set of numbers, collected from the tools we already use, before and after a change in tooling.

  2. Why we do not count lines of code

    Because assistance produces more of them, and more code is a cost. A measure that rewards volume will reward the wrong behaviour within a sprint.

  3. Where the gain is real

    Test coverage, migrations, repetitive refactors and documentation. Work with a known shape, where the bottleneck was typing and recall. Junior engineers get unblocked faster, which shows up as fewer stalled tickets rather than as faster individual output.

  4. Where it costs more than it saves

    Reviews get longer, because plausible-looking code takes more attention than obviously wrong code. Unfamiliar domains get worse, not better. And any task where verifying the answer costs as much as producing it is a net loss, every time.

  5. Summary

    On our own delivery the reliable gain sits in review throughput and in the boring half of a sprint. It does not compress a discovery phase, it does not reduce the number of engineers a hard problem needs, and it has never once made a deadline that was wrong to begin with.

  6. How this reaches your invoice

    It does not, directly. We do not bill by keystroke. It shows up as more shipped in the same sprint, and as fewer weeks spent on the parts of a build nobody wanted to pay for anyway.

    The tooling behind these numbers is the AI engineering kit. Everything else we build with models is on the AI map.

Discuss the next step

Tell us what you want to build or improve. We reply with a plan, an indicative budget and a start date.

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