AI-assisted development is real, capable, and already inside your organization. An analyst can prototype a data pipeline over lunch. A trader can spin up a dashboard without writing a line of code. So when a subscription proposal hits the budget conversation, the response is predictable: why are we paying for this when we could build it ourselves?

Here's what that question misses. AI lowers the cost of starting a build. It does nothing about the cost of running one — through every ISO schema change, every revision edge case, and every 2 a.m. failure for as long as your organization operates.

Garrett Lodewyck, director of product, data delivery at Yes Energy, breaks down where the build vs. buy line actually sits across the five layers of your data and analytics stack — and where building genuinely creates competitive advantage.

Download your copy to explore:

• - Three illusions about AI-assisted development that get expensive fast in a live trading environment.

• - The five layers of power market data infrastructure, and which ones are worth building yourself.

• - The 80% of total cost of ownership that never shows up in a build estimate.

• - Four questions to pressure-test any internal build proposal.

• - Where to point your AI investment so it compounds instead of stalls.