Editor's Note
Building a company requires ruthless prioritization. Choosing to execute on one thing means intentionally saying no to a hundred other viable ideas.
Over the last 15 years of defining, building, launching, and scaling new products as a Founder, CEO, and Product Leader, I've kept a running backlog of product blueprints. This newsletter is an open-source archive of the concepts I have deliberately chosen not to pursue.
These are ideas that feel obvious once you say them out loud, but non-trivial once you map out the details. I am publishing them because I believe these products should exist. I want to explore why an idea might work, the strategic trade-offs of building it, and who is actually best positioned to win the market.
An idea only has value when it meets execution. If this aligns with your focus, take the blueprint. It is yours to build.
The Complexity Tax
Booking travel used to be a simple question: "Who has the cheapest flight at the time I want to go?"
Today, it is a complex algebra equation.
If you are a modern traveler, you don't just have a bank account. You have a highly fragmented portfolio of depreciating assets. You hold currencies (100k Chase Ultimate Rewards, 50k Delta SkyMiles), coupons ($200 Amex airline fee credits, $50 Marriott statement credits), and status benefits (free checked bags, priority boarding).
When you book a trip, you aren't just spending money. You are managing a personal balance sheet. I mapped out a solution to automate that balance sheet. Here is the blueprint.
The Breakage Problem
Airlines and credit card issuers rely on "breakage," the industry term for benefits, points, and credits that go unused. They literally model it into their profit margins. They want you to forget about your expiring credits.
Currently, to book a trip optimally and defeat breakage, a user has to manually cross-reference their options across multiple platforms. They check Google Flights for the baseline cash schedule, the Chase portal to check direct redemption rates, the Delta website to hunt for award seat availability, and their Amex dashboard to see if a specific travel credit is about to expire.
The Bottleneck: The friction in modern travel isn't finding the flight. It’s optimizing the payment.
Because the mental math required to optimize that balance sheet across so many fragmented portals is exhausting, most of us just book the cash fare. As a result, hundreds of dollars in personal value expire every year.
The Blueprint: A Wallet-Aware Travel Agent
The Idea: A travel agent that actually knows what's in your wallet. Instead of just searching for flights, it does the exhausting mental math to figure out the absolute cheapest way for you to pay for them.
The problem with sites like Google Flights or Kayak is that they optimize for the open market. They show you what a flight costs a complete stranger, not what it costs you based on the points and perks you already own.
You securely connect your accounts (Chase, Amex, Delta, Marriott) once. Then, when you search for a trip, the engine doesn't just show you the schedule. It calculates the true "out-of-pocket" cost based on your specific points and expiring credits, and then handles the actual booking for you.
The Optimization in Practice: To see the difference between a standard search engine and a wallet-aware agent, look at the exact same flight through both lenses:
Standard Search (Google Flights) Result: Delta Flight 412. Cost: $450 Cash.
Wallet-Aware Booking Result: Delta Flight 412. Net Cost: $250. Logic applied: Agent triggers your expiring $200 Amex airline fee credit via the Amex Portal. Click to execute.
The Scope & Engineering Logic
Building another trip-planning app is a trap. To actually capture value, this engine must ignore the discovery phase entirely and act purely as a financial checkout layer for people who already know exactly where they need to go.
The Core MVP (Must-Haves for Validation):
The "Burn" Algorithm: A strict logic layer that automatically prioritizes using statement credits, free night certificates, and status benefits that are closest to expiration.
Real-Time Point Math: The user does not have to guess what their points are worth. The engine automatically pulls the real-time cash baseline of points based on the user's connected cards (e.g., knowing a Chase Sapphire Reserve gets 1.5 cents per point) to do apples-to-apples math against cash.
Smart Point Transfers: The highest-value feature. The engine calculates cross-program transfers (e.g., identifying that transferring Chase points to Virgin Atlantic to book a Delta flight is mathematically cheaper than booking through Delta directly).
AI Browser Execution: The engine uses client-side AI automation (like MultiOn) to execute bookings locally on the user's machine. This bypasses the enterprise bot-protection (like Datadome) that instantly kills traditional server-side scrapers.
How It Works In Practice
To understand the exact value, look at these two workflows through the lens of the people who feel the friction most:
1. Persona: The Hotel Hacker A user is booking a five-night stay in Miami and has 200k Marriott points. Normally, they might just book the cheapest cash option on Expedia. Instead, the AI Agent knows two things: Marriott offers a "5th night free" rule on point redemptions, and the user has Platinum status (which guarantees free breakfast and late checkout). The Agent filters for Marriott properties, recommends paying with points to trigger the free 5th night, and executes the direct booking to lock in the status perks. This saves the user $400 in cash and $150 in breakfast costs.
2. Persona: The Point Hoarder The user has 200k Chase points and wants to fly to London. Instead of logging into the Chase portal and getting a flat 1.5-cent value, the AI Agent runs the smart transfer logic. It calculates that transferring 45k points to British Airways offers a massive 3.2-cent value, executing the point transfer and the booking in one seamless flow.
Beyond the MVP: The Strategic Horizon
Any feature built after the MVP must serve one purpose: owning the complex transaction. If I were scaling this, here is where the product would go next:
Multiplayer Math (Group Travel): Optimizing a solo trip is hard. Optimizing a bachelor party where five people have different points, statuses, and cash constraints is a nightmare. Integrating a split-booking optimization layer bridges this into a high-growth multiplayer product.
The Corporate B2B Pivot: Selling this engine to mid-market companies. If an employee has a corporate card with travel perks, the engine automatically applies the perks, reducing the cash burden on the company. The employer keeps the breakage savings.
Explicitly Out of Scope:
Discovery & Inspiration: This is not a tool for figuring out where to go on vacation. It assumes you already know you need to be in NYC on Friday.
Credit Card Recommendations: It does not exist to sell affiliate links for new credit cards. It is strictly an execution layer for the assets the user already holds.
The Market Logic & Monetization
This is a high-utility product targeting anyone holding a premium travel card, from road warriors to the casual traveler taking three trips a year.
The Wedge: A monthly SaaS subscription creates massive friction for intermittent travel. But more importantly, if this product is going to act as an objective fiduciary for the user's wallet, the monetization model must perfectly align with their success.
The Math: This is a pure Success-Fee (Gainshare) model. The engine is completely free to use for search. You only pay when it executes an optimization. It charges a flat $10 execution fee per optimized booking, or a 10% cut of the cash saved.
The Alignment: If the tool intercepts a booking and applies a $200 expiring credit the user had forgotten about, a $20 success fee is a frictionless, joyful conversion. You only make money when the consumer actively saves money. At 500,000 optimized bookings a year, you have a highly profitable $5M to $10M business built entirely on consumer trust.
Why Existing Tools Fail
Flight Aggregators (Google Flights, Kayak): They optimize for market cash price, not your wallet. They do not know you have 100k points sitting idle or an expiring credit.
Award Search Tools (Point.me, Roame): These are excellent for finding award seats, but they assume you only want to use points. They do not factor in credit card statement credits, and they force the user to manually execute the complex transfer-and-book math.
Wallet Trackers (MaxRewards, CardPointers): Great for tracking benefits, but they are entirely disconnected from the actual booking workflow.
Why I Am Not Building This
The product logic is elegant, but the operational mechanics are heavy. Here is the strategic math on why I am leaving this blueprint on the shelf:
Adversarial Incumbents: Airlines and banks protect their portals fiercely. Even if you use client-side AI browsers to mask the automation, you are signing up for an ongoing game of cat-and-mouse with enterprise security teams. You have to build this with an appetite for platform risk and structural friction.
The Acquisition Math: Let us assume you solve the technical routing. You are still building a B2C fintech product, a category known for steep Customer Acquisition Costs (CAC). Educating consumers to change a deeply ingrained habit, like how they book flights, requires significant capital and patience.
The Authentication Hurdle: Operating as a financial delegate means navigating steep security and UX trade-offs. Storing credentials centrally is a massive liability, while relying entirely on local session cookies introduces friction the second a user clears their cache. It requires a flawless security posture from day one.
Maintenance Debt: Every time Delta updates a redemption table or Chase tweaks a transfer ratio, your routing logic breaks. The engineering bandwidth required just to maintain parity with dozens of shifting reward programs is a heavy, ongoing lift.
The Call: Who Should Build This
A Fintech Founder looking for a high-frequency wedge into a broader "Super Wallet" product.
An engineering team building on the absolute frontier of client-side AI browser automation.
A founder playing the "User Agent" game, someone who wants to own the consumer demand to eventually force the suppliers to play nice.
(And who should not): Risk-averse founders. You will be fighting a constant, exhausting cat-and-mouse game with incumbent bot defenses. You need the stomach for legal friction.
I am sharing these blueprints because I want to see them exist, even if I am not the one building them. Stop letting your credits expire. It is exactly what they want you to do.
If you know someone who is actively exploring the consumer fintech or AI browser space, send them this blueprint.
If you’d like to discuss the concept further or share any feedback (e.g., how you’d approach the client-side execution, how you’d challenge my market math, or just to empathize with the frustration of travel booking), simply reply to this email.
Talk soon!
-Munir