Agentic AI Governance: Tips from VP of Engineering

The margin for dropping the ball on governance in financial services is basically zero.

One bad decision can quickly turn into a public failure that erodes trust.

So we put together a field guide on building proper guardrails before you scale.

Our VP of Engineering weighed in with insights from the front lines—the kind you only get when you learn by building inside a real company with real consequences.

If you’re in financial services and you’re not thinking about this yet? You will be.

Might as well be early:

This Week: Strategic Venture Insights ft. Sam Nasser

How do enterprise giants like ADP stay innovative while managing legacy infrastructure and massive scale?

What does it take for an AI startup to land a strategic investment, and a shot at 60,000+ enterprise clients?

Sam Nasser, investor at ADP Ventures, shares how his team identifies startups with staying power and turns internal business needs into innovation pipelines.

We covered:

• How ADP Ventures bridges startup innovation with business unit demand

• What it takes for an AI startup to scale inside an enterprise like ADP

• Why speed, defensibility, and go-to-market edge matter more than ever

• How partnerships like Nayya and Thatch became ADP success stories

• A Centaur view of AI: augmenting workers, not replacing them

The Biggest Risk in AI Right Now? Waiting.

Velocity of learning is the most important success metric for AI adoption. The companies winning with AI aren’t the ones with the perfect roadmap.

They’re the ones learning the fastest. Not everything will work, but every test reveals what’s worth scaling.

The message is clear: move fast, experiment often, and learn while your competitors hesitate.