David Khachatryan

For Organizations

Leading Through AI Adoption

Two teams buy the same AI tools and get opposite results. The variable is almost never the tooling. It's whether anyone led the change.

This is a five-session program for engineering leaders and the people who manage them. It treats AI adoption as what it actually is: a change-management, measurement, and trust problem that happens to involve a new tool.

What the evidence actually says

The program is built on published research, not vendor optimism.

Amplifies dysfunction

Google DORA

Multi-year data found AI adoption raises delivery throughput while still degrading stability, and amplifies team dysfunction as often as capability.

19% slower

METR randomized trial, 2025

Experienced developers took 19% longer on real tasks using AI tools, then estimated they had been 20% faster. Self-report and reality pointed opposite directions.

9% vs 61%

Workforce AI trust surveys

The share of workers who trust AI for business-critical decisions, against the share of executives who do. Mandates are issued across that gap.

~60% fewer

Entry-level postings, 2022 to 2024

Junior engineering roles have collapsed while it still takes five to nine years to grow a senior. That arithmetic arrives on a delay.

The five sessions

Every session is free to read in full. Delivered live, each one is worked through as a group against your team's actual situation.

Who this is for

Engineering leaders mid-rollout

You've bought the licenses. Usage looks fine on the dashboard. You can't tell whether anything actually improved, and you suspect the honest answer is no.

Leaders facing quiet resistance

Your strongest engineers are the least enthusiastic, and you're not sure whether that's conservatism or a signal you should be reading more carefully.

Organizations under a mandate

Adoption targets arrived from above. You need them met without trading away code quality or the trust of the people who maintain it.

Teams thinking past this quarter

You've noticed the junior pipeline problem and want a deliberate answer rather than discovering the consequences in five years.

Bring this to your team

Delivered live and customized to where your organization actually is in its rollout. Tell me a bit about your team and I'll follow up to scope it.

Prefer to work through it yourself? See the self-paced programs.