Resources for journalists and podcasters

Andrew Templeton, co-founder. Bayesian engineer.

Self-taught technologist. Group CTO at a $1B+ retail holding company in a private equity portfolio, where he runs an AI-native operations stack across about 300 technologists. Builds production AI systems solo as his fun side; the Bayesian preference engine that runs underneath Bibbly is one of those. Andrew is the founder voice for Bibbly and the contact for all press, podcast, and partnership conversations.

Christina Templeton, co-founder and clinical advisor. Pediatric nurse practitioner.

Fifteen years in pediatrics. Twelve in pediatric ER. Currently a surgical nurse practitioner at Dell Children's in Austin, working primarily with cleft kiddos. Works with speech-language pathologists every day on feeding and early language. Christina speaks publicly about Bibbly as a peds NP and a parent who uses it; she is not a Bibbly employee and her employer does not endorse Bibbly. We route press on her behalf to keep her workplace neutral.

Full duo bios at https://bibbly.ai/about/.

On a vacation in 2025, Andrew made a board book for the Templetons' ten-month-old daughter Mara. Crayon drawings on cream paper, ten pages, Mara as a happy dinosaur with the rest of the family as her cast. He printed five copies and surprised Christina with them.

Mara slept with that book, kissed the pages, screamed when offered any other book. Four months later they were still the dinosaur family at every bath time. Bibbly was the answer to the question "why doesn't every kid have one of these."

High-resolution lifestyle photos and product imagery are available on request via support@bibbly.ai. The OG hero image is publicly accessible at bibbly.ai/og-image.png.

When using lifestyle photography from https://bibbly.ai/gallery/ or the homepage carousel, please note in caption that lifestyle previews are AI-rendered. Printed books ship in 2-3 weeks via Pint Size Productions in Atlanta.

For interviews involving the technical engine (Bayesian preference, dual-judge soft-gate, image DAG), see https://bibbly.ai/under-the-hood/.

• The collapse of personalized-content production cost (artist-day to under a dollar) and what changes when generation is cheap and the bottleneck moves to taste extraction.
• Pairwise preference elicitation as a UX pattern for any aesthetic or taste-driven decision (names, books, design, brand identity).
• The dual-judge soft-gate pattern: independent LLM critics with content-addressed rollback as a way to ship AI output without a human in every loop.
• Christina's clinical voice on board books, language development, and the 0-3 reading window. (Christina is reachable for clinical-voice interviews; we route requests.)
• The retail / PE operator perspective on AI-native operations at scale (Andrew's day job context).
• What family co-design tools look like when both parents have product input and the kid is the customer.