Binoculars around my neck, standing at the edge of a marsh — that’s how I started this morning, and it’s also how I want to start this episode, because today is about something practical: what AI actually looks like when you use it for a hobby you love, when you’re not a technical person and have zero interest in becoming one.
Turning 15 Years of Data Into Something Usable. My friend and I have logged over 800 birding trips and 12,000 entries in eBird. This winter I moved all of it into Notion — not by writing a single line of code, but by describing in plain English what I wanted (a timeline by species, by location, by date) and letting Claude build the structure and populate the data. No programming required, just asking it real human questions about my own data.
Telling Similar Species Apart. Every birder has a story about getting an ID confidently wrong. Mine involves snow geese and Ross’s geese — nearly identical to the casual eye. I had AI build me a side-by-side infographic comparing bill shape and markings, something I now keep on my phone and pull up in the field. It’s saved my birding buddy and me real misidentifications.
Voice Logging on the Move. When I’m hitting multiple locations in a single outing with 40 species to keep track of, I log sightings out loud through CarPlay between stops instead of trying to hold it all in my head.
Real-Time Identification Help. When I see something unfamiliar, I can describe it out loud or photograph it and ask AI to walk through the possibilities with me — and just as importantly, ask it to explain why, so I get better at identifying that species myself next time instead of just getting handed an answer.
From “What Is This Bird?” to “Why Is This Happening?” This is the shift that surprised me most. Blue feathers stuck to a Canada goose, an unusually tired eagle being harassed by red-winged blackbirds, a strange concentration of loons, crayfish migrating overland — these moments used to just be “huh, that’s odd.” Now they turn into real conversations about behavior, migration, and habitat that genuinely shape what I want to talk about on this podcast.
You Don’t Have to Be Technical. The point isn’t birding specifically — it’s that you can describe what you want in plain English, whether that’s a birding database, a yarn inventory, or anything else tied to a hobby you love, and AI can build the tool without you needing to understand anything about how it works under the hood.
If you have a hobby with years of scattered data or recurring questions you’ve never had a good way to track, this is exactly the kind of campfire conversation worth starting.
Jill’s Links
http://jillfromthenorthwoods.com
https://www.youtube.com/@startwithsmallsteps
https://www.buymeacoffee.com/startwithsmallsteps
https://twitter.com/schmern
Email the podcast at [email protected]
By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.
