Your engineers
stop writing code.
They start commanding it.
A 3-6 month embedded engagement that transforms how your engineering organization builds software — with humans firmly in control of every change that ships.
AI tools exist. Adoption doesn't.
Every CTO has read the same headlines. AI can write code. Engineering velocity can double or triple. And yet most engineering teams — even excellent ones — are not using AI in any meaningful way.
It's not because the engineers aren't smart enough. It's because adopting AI-assisted development is not a tooling change. It's an organizational transformation. You can't hand someone a Copilot license and expect results.
The repositories aren't structured for it. The review processes don't account for it. The testing strategies don't leverage it. And engineers have spent their entire careers building muscle memory that actively works against effective AI collaboration.
The result: CTOs who know they need to move, paralyzed — because it feels like the only option is to stop everything and start over.
Within a year, paying engineers to write code by hand without AI assistance will be the equivalent of paying someone to do long division instead of using a calculator.
We've delivered measurable wins at every scale.
The AI Adoption Accelerator
A 3-to-6 month embedded engagement where we retool your engineering organization to develop software with AI. We don't teach theory. We sit with your people, change how they work, and make sure the changes stick after we leave.
Your engineers stop being the people who produce code and start being the people who ensure the right code gets produced. AI handles wholesale generation, testing, and iteration. Your engineers become the planners, the reviewers, the quality layer that decides what ships.
Four phases. One transformation.
Five skills that compound.
The cost of inaction is higher.
What You're Spending Already
For a 10-person engineering team, you're spending $1M-$2M per year in fully loaded compensation. The Accelerator acts as a multiplier on that existing spend.
What You Get Back
Even a conservative 20-30% improvement in engineering velocity on a $1.5M annual payroll represents $300K-$450K in delivered value per year, every year after the engagement ends.
We leave. The velocity gains don't.
What's Included Every Month
We've operated at the highest stakes.
$750M in Hedge Fund Assets
Our team managed $750M in assets where being wrong meant real losses — not missed KPIs. We bring that accountability to every engagement.
Visa Fraud Detection at Scale
We built fraud detection systems that process millions of live transactions. We understand what it means to build AI that cannot fail.
Autonomous Vehicles at Uber
We developed systems where the cost of error is measured in lives. We know what safety-critical, human-in-the-loop AI looks like in production.
Four profiles. One common thread.
Engineering organizations of 10+ developers
You want to adopt AI but don't know where to start. You have real engineers, real codebases, and real delivery pressure. This is built for you.
CTOs and CIOs who understand the urgency
You know you need to move. The organizational change feels too daunting to undertake internally. We've done this before.
Teams where AI "didn't work"
Engineers tried Copilot, watched it make mistakes, and went back to writing code by hand. The tool wasn't the problem. The workflow was.
Compliance-sensitive organizations
You need to adopt AI without removing human oversight from your release process. Our model keeps humans in control of every change that ships.
The companies that retool now gain a compounding advantage.
Most engineering organizations are 12-18 months behind the current state of the art. The gap is widening. Schedule a free discovery call with our team.