AI‑Native Delivery Lab

Redesigning How Solutions Are Built

This Is Not Optimization.

It Is Operating Model Reinvention.

Executive Intent

Establish a leadership-funded, isolated AI‑Native Delivery Lab to redesign the full lifecycle of software and data solution delivery for the AI-agent era.

Not a productivity initiative.
A structural transformation experiment.

Structure: 7 AI Commanders

No fixed legacy roles. No traditional functions.
Every human is an AI Commander. Capabilities evolve around agent orchestration and outcome design.

1

1-Person + Agents

Solo commander orchestrating a fleet of AI agents for rapid delivery.

2

2-Person + Agents

Paired commanders splitting orchestration and review for balanced throughput.

3

3-Person + Agents

Small team tackling complex builds with layered human oversight.

Objective: Determine the minimum human structure required for high-quality complex delivery.

Continuous High‑Velocity Experiment Engine

Projects scoped in days to 3 weeks. From Day 1: real delivery, real metrics, real iteration.

Velocity compounds as infrastructure matures.

⏱ Time-to-delivery
👤 Human hours per outcome
🤖 Agent utilization ratio
✓ Quality stability
🚀 Learning acceleration

Why This Is Urgent Now

AI agents have crossed from assistance to execution.
The strategic question is no longer "Should we use AI?" — It is "Who redesigns the operating model first?"

Delay Risks

  • Structural cost disadvantage
  • Talent obsolescence
  • Competitive inertia

Early Action Creates

  • Operational leverage
  • Institutional learning curve
  • Transformation authority

6–9 Month Accumulated Outcome

After continuous project cycles, we expect:

15–30
Completed AI-native builds
50–80%
Reduction in human effort per deliverable
↑
Stable or improved quality metrics
✓
Validated AI-native operating model

Strategic End State

The Lab becomes the AI Operating Model Authority for the organization.

A repeatable blueprint for transforming how the group builds, delivers, and scales solutions.