Hey, it’s Jeffrey — back again!
I’ve been earning points for years for airlines, hotel programs, and credit cards. But earning points is the easy part. The credit card does it automatically, the airline credits your account, the hotel adds the stay. You don't have to think about it.
What most people never get around to is everything after. What are they actually worth? Which programs are about to expire them? And if you wanted to redeem them for something real, where would you even start?
I track my points pretty closely, so I already had a rough sense of the answers. What I wanted to see was whether AI could do the analysis layer quickly enough to be worth building into a regular habit. Turns out it can.
I want to audit my loyalty points and miles across all my programs.
Here's my current inventory:
Program | Balance | Notes (optional)
[Program name] | [Balance] | [e.g., "haven't used in a while" or leave blank]
[Program name] | [Balance] |
[Program name] | [Balance] |
(add more rows as needed)
Please do the following:
Estimate the total cash-back value vs. total travel redemption value across all programs. Lead with the gap between the two — this is what I'd lose by cashing everything out instead of redeeming for travel. For context, also frame the travel value roughly in terms of what it could represent (e.g., approximate number of economy round trips at average redemption rates — keep this general, not route-specific).
Break down each program individually — estimated cash value, estimated travel value, and a one-line note on redemption flexibility (e.g., transferable to multiple partners vs. locked to one airline).
Flag any programs where inactivity expiration is a known risk based on typical program rules. Note the general inactivity window and one simple action that would reset the clock.
Give me a priority action list — what to deal with first based on value at risk or biggest redemption opportunity.
Keep output simple and scannable. Use approximate figures where exact rates vary, and note where rates are especially variable.
Here's what came up when I ran it on mine.
The total travel redemption value across my programs came out to roughly $15,700, against a cash-back value of about $7,400. That's an $8,300 gap I already knew existed in theory. Seeing it calculated across my full inventory in one output made it more concrete and easier to act on.
The more useful part was the expiration flags. One airline program with a significant balance showed up as inactivity risk. I knew the rule existed, I just hadn't verified my status recently. Worth a quick check.
The prompt won't tell you anything you couldn't figure out manually. It just does in five minutes what would otherwise take an hour of cross-referencing program rules and doing math across eight different apps.
One practical note: AI applies general program rules here, not your account-specific data. After you run the prompt, log into each flagged program to check your actual last activity date. Most programs show it on your account dashboard or in a recent statement email.
Want to dig further? For checking award availability before you commit to a redemption strategy, tools like Point.me and Seats.aero let you search across programs in one place.
Keep going? Want to go further? Try these follow-up prompts after you get your initial result:
If you want to check expiration dates: "I flagged [Program] as an expiration risk. My last activity date was [date]. Based on the standard inactivity window for this program, how much time do I have, and what's the simplest action to reset the clock without spending money I wasn't planning to spend?"
If you want to build a redemption plan: "Based on my points inventory above, I'm planning a trip to [region] in [timeframe] for [number] people. Which programs give me the best shot at a strong redemption for this trip, and what should I transfer or book first?"
If you want to track this going forward: "Create a simple points tracking template I can update twice a year. Include columns for program, balance, estimated cash value, estimated travel value, last activity date, and expiration risk level.
AI tip worth trying this week: Proofreading a PDF
I used Claude to proofread my wedding seating chart before it went to print. I’m honestly not patient enough to be a copy editor, and I’m lazy when it comes to tedious tasks.
I uploaded the PDF and asked it to flag any name spelling inconsistencies, check for duplicate entries, and note anything that looked off. It caught a real one: a name misspelling of a married couple. It also flagged a handful of other names with unusual spellings worth double-checking. The whole thing took about 30 seconds.
One quick note: This newsletter is for educational purposes only and does not constitute financial advice. I'm not a financial advisor — just someone sharing ideas and tools I've found useful. Use what works for you, skip what doesn't, and always do your own research. Some links may be affiliate links or sponsored content for which I may receive compensation.