I used Google NotebookLM to turn my AncestryDNA ethnicity results and ancestral journeys into a single visual infographic. By uploading my screenshots and downloaded files and prompting it to focus on aesthetics and storytelling, I was able to transform static percentages into a cohesive ancestral narrative. In this post, I walk through the exact workflow and explain why keeping the AI grounded in your own uploaded sources matters for responsible genealogy.

When a name is common, adding more ancestors can create more confusion. This post explains why I often build short, focused “test trees” to rule people out instead. Using a real case involving multiple Mary Magee candidates in 19th-century Illinois, I walk through how tracking each possibility forward in time helps eliminate the wrong individuals, document decisions, and avoid forcing connections that do not hold up.

In this case study, I trace a client’s family line to determine whether it truly connects to the historically documented Blue Fugates of Kentucky. Working without DNA, the research relied on careful record analysis, extended family reconstruction, and solving a challenging census problem where key relatives appeared to vanish. The result is a grounded look at how unusual family stories can be tested and, sometimes, confirmed using evidence-based genealogy.

Tree hygiene becomes critical once DNA enters the picture. This article covers practical best practices for maintaining clear tree structure during DNA research, including how privacy settings affect hints, when to use separate research trees, and why small structural choices can have big downstream effects on Ancestry’s DNA tools.

A short look at why I built “Gina the Genealogist Chatbot,” an evidence-first research assistant designed for real family history problems. This article explains how Gina avoids guessing, stays grounded in reputable sources, and helps researchers understand records, gaps, and DNA results with clear next steps.

When DNA suggests a different biological parent than the one shown in records, many family trees start to break down. This article explains why tree structure matters for Ancestry’s DNA tools, how algorithms like ThruLines interpret relationships, and the two main ways to organize a tree so DNA evidence produces clearer, more reliable results.

AI can be a powerful genealogy tool, but only if you know how to ask the right questions. This post explains the difference between weak and strong prompts and shows how small changes can dramatically improve the quality of genealogy answers you get from AI.

A family rumor passed down for generations, a grandmother’s DNA test, and a surprising 1860 census discovery. This post walks through how I solved a long-standing family mystery and identified the biological father of my great-great-grandfather. A reminder that DNA, records, and geography work best together—and that in genealogy, the answer is sometimes literally next door.

Most genealogists use Ancestry ThruLines to confirm what they already believe. I use it to find what is missing. In this post, I walk through a real example where ThruLines showed only five children for an ancestor who clearly had more. That gap was not an error. It was a research prompt. I explain the most common reasons children do not appear in ThruLines, how to tell the difference between weak trees and real family mysteries, and why missing lines often point to adoptions, NPEs, or undocumented branches. If you want to use ThruLines as a diagnostic tool instead of a confirmation badge, this post shows you how.

A DNA search angel helps people uncover biological parents and missing family connections using DNA and careful research. In this post, I explain what search angel work really involves, why it has been the most meaningful part of my genealogy work, and how I have helped individuals find answers about their origins. I also share why I now offer this work as a focused professional service and what can realistically be accomplished in a short, targeted DNA analysis session.

How did a late-19th-century farm family actually move across the Midwest? In this post, I use historical records and modern research tools to reconstruct how A. J. Copeland moved his wife and three children from Illinois to rural Missouri in the 1890s, and why they later returned. By analyzing period rail routes, travel costs, and economic conditions, this case study shows how combining traditional genealogy with careful contextual analysis can turn dates and locations into a realistic, human story of movement, risk, and decision-making.

Genealogy research depends on context, continuity, and long-running questions. In this post, I explain why using AI tools without an account limits their usefulness for genealogy, and how simple continuity across sessions can change the way complex family histories are analyzed. Using real examples from my own research, including alias-heavy cases, I show how returning to an ongoing line of reasoning allows deeper insights without starting from scratch each time.

Handwritten records demand accuracy, not interpretation. In this post, I walk through a real example using Cursive Curator my CustomGPT to transcribe a mid-1800s handwritten family record, showing why strict, literal transcription matters in genealogy. You will see how preserving original spelling, marking uncertainty, and avoiding guesswork protects evidence and keeps research honest, and how a purpose-built Custom GPT can support disciplined genealogical work.

A clear, methodical approach to DNA match analysis can make the difference between confusion and answers. This article explains why building and comparing trees comes before messaging matches, and how structured analysis leads to better results when identifying an unknown parent.

Genealogy gets difficult when the easy records run out. Duplicate people, incorrect parents, and misread DNA results can quietly derail years of research. This post explains when hiring a professional genealogist makes sense, what common mistakes to watch for, and how expert review can restore clarity and momentum to your family tree.

Missing children in a census record do not always mean a missing family. In earlier records, children often lived with relatives and were listed under different surnames or nicknames. This post shows how understanding historical context and adjusting search methods can reveal children who appear to have disappeared.

When a relative vanishes from the records, the answer is not always death or distance. Sometimes it is reinvention. This post explains one of my most reliable genealogy techniques for uncovering hidden identities using Social Security SS-5 applications. Through real cases, including an outlaw who rebuilt his life under an alias, I show how small inconsistencies in parent names can reconnect fractured paper trails and reveal the truth behind long-standing family mysteries.

DNA testing has made it possible to answer one of the most difficult questions in family history research: identifying an unknown biological parent. This article explains how DNA evidence, traditional genealogy, and personal context work together to build a well-supported answer. It walks through the process of analyzing DNA matches, separating known and unknown family lines, and using records and timelines to reach clear conclusions.

What happens when decades of genealogy research are turned into a single visual? This post shows how Google NotebookLM can transform dense source material into clear, meaningful infographics without inventing facts. Using a real family history project as an example, I explain where AI genuinely helps genealogists see patterns, timelines, and connections, while keeping original records at the center of the work.

AI photo “restoration” can look convincing, but it does not recover history. It generates new images based on patterns and guesses. In this post, I explain why AI-edited photographs are illustrations, not evidence, how unlabeled images can quietly distort family trees, and what responsible genealogists should do to protect the historical record while still using modern tools.