Smart leaders are stuck on AI. I get their teams unstuck.

You've purchased the licenses. You've made the proclamations. You may even have an internal champion. Nothing has changed. I take a hands-on approach to showing your team what's possible and how.

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The problem

10-15%

Copilot seats in use across the Fortune 500, two years in

— Tim Kellogg

6%

Executives who can point to org-wide AI ROI. 89% say AI made work faster

— Atlassian State of Teams, via SVPG

30%

Gain in shipped releases, from a 180% gain in code written

— MIT Sloan / Wharton, 100k developers

50x

What the top decile of firms spends per employee on AI, against the median

— Ramp data, via a16z

The tools exist. The results don't. The gap is not access. It's knowing what to aim for.

What you've already tried

The internal champion.

A senior PM or engineer gets tapped as the AI person. But they have a day job. The old way is easier and less risky. AI stays a side project. This is my only job.

The one-off training.

Everyone learns generic prompting tricks. Nobody goes back to work and knows what to do next. It doesn't stick because it's not connected to your actual processes. I work on your real data, your real sprint work, your real pipeline.

The status quo.

You feel the pressure. You bought the licenses. You keep talking about it. Nothing changes.

All three fail for the same reason. There's no one showing your team what good looks like in the context of your actual business.

What changes

Product teams operate on live intelligence.

Customer support signals, sales conversations, competitive moves, and usage analytics synthesized as fast as the data comes in. Not every six months when someone has time to do a research cycle. Fewer sprints wasted building the wrong thing.

elsewhere_

Midjourney's product team runs one to three user interviews a week through a shared research skill. Interview start to company-wide insight takes 45 minutes.— The Skip

Engineers build systems instead of grinding through tickets.

Routine work gets executed by agents. Engineers focus on architecture, strategy, and the decisions that actually require judgment. Output per engineer increases because the nature of the work changes, not just the speed.

elsewhere_

Self-reported by each company. Four independent teams, output up and defects down in every one.

When I leave, the systems are already running.

I embed with your team and work on your actual processes. The environment is set up. The workflows are built. Your team has done it, not just watched it. The capability is theirs.

Services

Talks, advisory, sprints, builds, and embedded leadership.

Five shapes of engagement, from a single talk to ongoing technical leadership. Each one stands on its own and earns the next. For CEOs facing decisions they can't delegate, a standing weekly advisory session is the usual starting point.

How I work →

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About

Saadiq Rodgers-King
name_ Saadiq Rodgers-King
location_ Brooklyn, NY
education_ Princeton CS, MIT Sloan MBA
experience_ 20+ years
exits_ Facebook, GoDaddy, Gerber Life, Yuga Labs
focus_ AI transformation

I've spent my career at the intersection of product, engineering, and strategy. Four of the companies I built and led were acquired, by Facebook, GoDaddy, Gerber Life, and Yuga Labs. I know what high performance with these tools looks like firsthand.

If you're a CEO or CPO at a tech company where the AI mandate landed but nothing's changed, let's talk about what's actually possible.

More about me →

> saadiq — available for engagement