Then Is Now: How a Black Technologist Is Using AI to Reclaim What History Tried to Erase

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Want to see your PDFs think like a database and your chatbots answer with context, not guesses? We sit down with technologist and entrepreneur Max Riggsbee Jr., co-founder of Gadget Software, to unpack how compute-ready documents—what he calls semantic twins—turn unstructured content into structured, queryable knowledge that both humans and machines can trust. Max explains why simply chunking PDFs into a chatbot loses meaning, and how deep descriptors, QA pairs, and entity maps let you navigate ideas, not just pages.

We go inside directed AI, where you choose the exact slices of content a model can touch, then generate summaries, outlines, or tables grounded in that selection. Max shares results from work with Signal65, Dell, and Broadcom showing fewer hallucinations, faster token throughput, and better energy use when AI is fed structured, contextual data. From there, we get practical about agentic workflows: the validator checks you need before any output ships downstream, and why human-in-the-loop review still matters. Max’s “Georgia” test—person, state, country, or font—reveals how ambiguity explodes without metadata. He also breaks down a real failure in a political cartoon pipeline where an agent inferred a story from SEO slugs instead of reading the article, and how guardrails caught it.

Our conversation widens to legacy and Black history. Grant traces family records from enslavement to land ownership, underscoring how caricatures like Jim Crow distort truth when they calcify into the story we’re told. Maxwell introduces Then Is Now, the audio diary project he runs with his 90-year-old father, using authentic voice recordings and AI to frame the surrounding historical context. We talk about scanning non-digital originals like the Pentagon Papers as a stepping stone to microfiche, county archives, and the overlooked documents that can restore names, places, and property to the record. On the technical edge, Max shows how rich textual descriptions can stand in for heavy images, enabling vision models to re-render diagrams on demand, making insights lighter and more scalable.

If you work with unstructured data, lead AI projects, or care about preserving the story with accuracy, this conversation gives you a roadmap: structure your sources, validate your agents, and keep humans in charge of meaning. Subscribe, share this episode with a friend who needs better answers from their data, and leave a review to help others find the show.

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And don’t miss Grant McGaugh’s new book, First Light — a powerful guide to igniting your purpose and building a BRAVE brand that stands out in a changing world. - https://5starbdm.com/brave-masterclass/

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