01Solution

Agentic P/SDLC transformation

Agents across the product and software development lifecycle. Humans steer planning, building, testing and shipping

Copilot made typing faster.

The queue just moved upstream.

Capabilities
Workflow Redesign
Agentic Engineering
Roles & Responsibilities
Team Enablement
The landscape

A faster editor does little for a lifecycle whose constraint sits somewhere else. Teams that add AI to an unchanged workflow settle around 1.3x, because the queue forms where work gets specified and verified. Typing was never the slow part.

  • 30–50%

    throughput gain when agents are native to the SDLC

  • Day one

    AI in the lifecycle, from planning to release

  • Every stage

    planning, building, testing, shipping

  • Humans

    steer; agents do the heavy lifting

Shift

So we rebuild the lifecycle around that constraint: plans an agent drafts and a human sharpens, review that runs continuously instead of batching at the end, and evals that gate quality automatically as throughput climbs. Your teams keep intent and judgment. Agents take the volume.

DimensionBeforeAfter
Planningmanualagent-drafted
Buildingline by lineagent-accelerated
Testingbottleneckautomated
Reviewslowcontinuous
Why us

Everyone codes

No junior handoffs. Senior engineers on the work, end to end.

AI as force multiplier

AI amplifies our engineers. It does not replace judgment.

Observed failure modes

We bring the failure modes we have already hit on prior transformations.

Aligned incentives

We price the outcome. Speed is our margin.

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