Ep 128: Owning Your AI and Capitalizing on Proprietary Data with Andrew Brooks

Andrew Brooks, CEO and Founder of Contextual.io, joins Bob to trace a career that runs from early-internet consulting through three exits (Seven Space to Sun Microsystems, a marketing company to ReachLocal, and SmartThings to Samsung) before landing on AI. Andrew explains Contextual's "own your AI" philosophy, why businesses should design, build, and operate their own systems rather than lock into a single model provider, and how real transformation comes from deepening a company's data, process, or relationship moats rather than chasing cost takeout alone. They dig into real client stories, from a commercial refrigeration estimator's tacit knowledge to a vacation rental company that discovered unexpected revenue recovery through AI-audited work orders. The conversation closes on what's shifting for engineering talent, why "human in the loop" needs more precision, and why waiting for the perfect model is a losing strategy.

Keywords

Contextual, Andrew Brooks, own your AI, agentic AI, AI orchestration, mid-market businesses, AI moats, model selection, Digital Greg, tacit knowledge, automation vs facilitation, human in the loop, agent sprawl, AI governance, private equity, Southfield Capital, system design, engineering talent, responsible AI by design, SmartThings, Seven Space, MCP, rational optimism

Takeaways

"Own your AI": build a system-agnostic layer instead of locking into one model or provider
Durable AI investments deepen an existing moat, whether data, tacit knowledge, or relationships, not just cut costs
Automation builds trust and adoption, but resist treating AI as a hammer for every problem
Well-designed systems surface second and third order value nobody planned for
Talent is shifting toward system designers who can spot edge cases and challenge AI outputs
Waiting for a "perfect" model is a losing strategy given the pace of change

Quotes

"The phrase we use is own your AI. Do not become too embedded in a single provider or a single model, because you need to be able to react to what's happening in the space."
"Not everything's an AI problem. Some things are process, and some things are just workflow."
"You can't wait for the perfect model. The models are revving every ten, fifteen days. The pace of change is just too fast. You need to get into the river."
"AI can be confidently wrong, and very confidently wrong. You've got to be able to see that and flag it."
"I'm in the rational optimist camp here. AI might change jobs, but we've been changing jobs for many, many years."

Chapters

00:01 Welcome and introducing Andrew Brooks

00:35 From Accenture to entrepreneurship: Seven Space, Reach Local, and SmartThings

03:45 Landing on AI and founding Contextual

04:41 Design, build, operate: how Contextual works with clients

08:33 Choosing the right model without over-committing to one provider

10:04 Beyond chatbots: agentic systems and finding your AI moat

12:36 Automation as an on-ramp to bigger AI thinking, and avoiding the shiny-hammer trap

17:58 Systems thinking, from Smart Things to agentic infrastructure

21:27 Responsible design, client collaboration, and unexpected value from clean data

28:19 Bad data, bad processes, and why waiting for the perfect model is a mistake

30:00 Where humans stay central and what "team superpowers" means