Money, Bills & Benefits: top AI agent use cases
This page collects real examples of people using AI agents for money: unclaimed funds, refunds, cancelled subscriptions, lower bills, taxes, and insurance. There are 105 use cases in this category, each a job someone reported doing, with a link to the original post. The ones readers have voted for most are listed first.
105 Money, Bills & Benefits use cases, from every agent.
Top Money, Bills & Benefits use cases
Let AI models trade stocks autonomously with $1k each
Poster ran four AI models on a weekday pre-market prompt to trade $1,000 portfolios each for nine weeks; ChatGPT came out ahead.
How it went After nine weeks, ChatGPT led at +21.1%, helped by healthcare picks including IOVA doubling and ACHC rising 52%. Perplexity was +1.1%, Gemini -6.6%, Claude -11.5%, and the poster stressed it was paper money and too early to trust blindly.
Find unclaimed money and start the claim
Meta's Muse agent found over $1,500 in unclaimed funds in about five minutes and helped fill out paperwork; the claim was filed but unpaid.
How it went Muse found more than $1,500 in about five minutes. Grous had not received any money when the article ran, because government offices still have to verify and approve the claim.
Meta Muse4 accounts
Run an 11-agent team for trading prep
A trader runs 11 Grok Bot agents, each with one job and a scope document, with a Red Team agent that must approve a trade first.
How it went They say the persistent browsing setup fixed most of the scraping breakage from the earlier system and was easier to set up than Claude Agent Teams. The post gives no performance numbers or P&L, and it leaves open problems around pinning models to agents and understanding Cursor integration.
Generate investment analysis from live market data
The poster built a personal wealth advisor in Claude Code that feeds live market data, macro indicators and news into investment analysis.
How it went They say the goal was analysis beyond generic stock tips, but the thread excerpt gives no performance numbers or verified investing results. What’s shown is a personalized research workflow, with the strongest claimed benefit being better output from retained memory.
Claude Code2 accounts
Run overnight memecoin checks and alerts
Grok Bot ran a taught 4-minute memecoin check 3,140 times overnight across several sites, wrote reports, and generated 160 alerts; the user claims $9,320 profit.
How it went Over 30 days the system checked 3140 coins, skipped 2980, generated 160 alerts, and supported 52 trades for +$9320 profit.
Find cheaper car insurance
A startup founder said Muse found car insurance costing $3,500 less per year than his original plan.
How it went Devoy said the insurance Muse found cost $3,500 less per year than his original plan, and he called it a killer product. The figure is his own claim, and many other posted wins came from Meta staff.
Meta Muse3 accounts
Teach an agent to trade with signals and logging
@mufasadubai had Manus write a Python script using ProjectX APIs for realtime charts, set up Telegram signals and log trades to Google Sheets and CSV.
How it went The system is now running and will be tested the next day; the user plans to review logs later with Manus to refine the strategy.
Cancel and refund subscriptions by searching email and calling
Grok Bot read email across two accounts, logged into systems, phoned providers and sent emails, cancelling and refunding two long-pending subscriptions in about ten minutes.
How it went About ten minutes later both subscriptions were cancelled and refunded. The author doesn't give the refund amounts.
Grok Bot2 accounts
Questions
- Is this financial advice?
- No. These are reports of what someone else did with an agent, such as looking for a refund, a benefit, or a lower bill. They are not a recommendation, and an agent can be wrong about money.
- How many Money, Bills & Benefits use cases are there?
- There are 105 use cases in this category on the site right now. This page shows the top ones, not the full set.
- Which agents show up most for this kind of work?
- The named agents used most often here are Claude Code, Claude and Meta Muse. Other entries use a custom-built or unnamed agent.
- How does a use case get onto this page?
- It has to be something a person reported doing. We re-read the source before it is shown. Reader submissions are reviewed by a person first. An approved submission is checked against its source and added in a later update. A rejected one is not added.
- How is this list ordered?
- By votes from people on this site. More votes means higher on the list. Ties go to the use case described in more separate accounts.