In this episode of Just Curious, Stu Willson speaks with Adam Schwartz, Co-Founder & CEO of Parable, about why most companies don’t actually understand how work gets done inside their organizations. Adam explains how Sunrun uncovered more than $80M in hidden costs by gaining real visibility into its operational data—before deciding where AI and automation would actually deliver ROI. The conversation breaks down why better data and context must come first, and how AI becomes powerful only once that foundation is in place.

Chapters:

00:00 – Intro & Adam’s background
01:30 – Why most leaders misunderstand how work gets done
03:45 – The hidden cost of “keep-the-lights-on” work
06:30 – Why AI transformation fails without operational context
09:00 – Why data warehouses can’t explain real work
12:45 – What a contextual knowledge graph actually looks like
16:30 – How executives use Parable to prioritize AI use cases
19:30 – Measuring behavioral change vs. AI adoption
22:45 – The rise of “operational debt” beyond engineering
26:45 – Risks of deploying AI agents without first-principles thinking
29:45 – Sunrun case study: why they couldn’t ship fast enough
33:30 – Quantifying technical debt and operational inefficiency
36:00 – When AI is the answer — and when it’s not
39:30 – $80M in cost savings and 25–30x ROI explained
41:45 – The mindset shift boards and CEOs must make with AI
43:45 – Who Parable is built for and when companies should engage

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