[daviding]

A nice idea and good luck! My lawn is dead as our local data center took all the water (I'm kidding!).

We do home property and inventory services using AI on photos as well and the key thing we've found so far is that the biggest rival to those features is just people dragging photos into chatgpt and asking away. So the key here is differentiating from that and making something better and more accurate. What we did was to basically build a better and deeper prompt and history, e.g. context is king in a vertical. So that means the other info the user has put about the property, the memory of previous things asked or seen, combining with publicly available property info we already gather - this would make the information more valuable than straight gpt usage.

So what more can you bring to the bare prompt on the photos to help? What can you build in terms of info about the zip, so you do more 'vertical stuff' before the api call.

[andrewbr]

Great callout, I saw something similar on another site. Essentially instead of just entering your ZIP, you can also enter your estimated lawn size as well as various other parameters to generate a better prompt. I think that would be helpful to build in the next iteration, both to strengthen the results and also differentiate ourselves from GPT. Another thought I had was to potentially build a database of specific, authoritative lawn care information, such as industry journals, textbooks, university extensions, etc from which the GPT must draw upon and reference, rather than using context clues from the internet to try and invent some kind of analysis or treatment.