Water bills spike and nobody knows which controller settings or zones are responsible. Short answer: use Claude (the source example used Claude to analyze controller settings). Free option: ChatGPT. The workflow has 4 steps and 2 copy-paste prompt(s); expect a list of suspect settings and high-use zones, an on-site checklist and a client note. Main caution: AI can't see leaks, pressure problems or coverage; verify on site.
The problem
Water bills spike and nobody knows which controller settings or zones are responsible.
Recommended tools
ClaudeThe source example used Claude to analyze controller settings.
Free; Pro $20/mo ($17/mo annual); Max from $100/mo
ChatGPTFree plan works with pasted settings.
Free; paid plans per user - see https://chatgpt.com/pricingEditorial opinion based on the vendor capabilities and prices listed in our tools directory. Not paid placements; prices as checked Oct 2026 and may change. Compare all use cases →
All tools mentioned
Step-by-step workflow
- Export or screenshot schedules, zone settings, weather/seasonal adjustments and run history, plus the water bills.
- Ask AI to compare settings and run times with water use and point to likely causes.
- Verify on site: run each zone; check for leaks, broken heads and overspray.
- Change one setting at a time and track the next bill.
Copy-paste prompts
Here are my irrigation controller settings [zones, plant type, sprinkler type, run times, days, weather/seasonal adjustments] and monthly water usage [paste]. Identify settings most likely to over-water, estimate which zones use the most water, and list what to check on site. Flag assumptions.
Turn these findings into a short client note explaining the changes we recommend and why: [paste].
What to expect
A list of suspect settings and high-use zones, an on-site checklist and a client note.
Limits & safety
- AI can't see leaks, pressure problems or coverage; verify on site.
- Follow local watering restrictions.
- The source's gallons and dollar figures are one person's self-reported result.
Source / inspired by
- Post on X about analyzing a Rachio system — Josh Pigford (@Shpigford), Sep 2026. Reports Claude found an automated "heat wave" setting had used far more water than needed (self-reported). Summarized in our own words.