I use points and miles for most of my travel. Every booking comes down to the same decision: use points or pay cash? To answer that, you need award availability across multiple programs, cash prices, your current balances, transfer partner ratios, and the math to compare them. I got tired of doing it manually across a dozen tabs.This toolkit teaches Claude Code and OpenCode how to do it. 7 skills (markdown files with API docs and curl examples) and 6 MCP servers (real-time tools the AI calls directly).It searches award flights across 25+ mileage programs (Seats.aero), compares cash prices (Google Flights, Skiplagged, Kiwi.com, Duffel), pulls your loyalty balances (AwardWallet), searches hotels (Trivago, LiteAPI, Airbnb, Booking.com), finds ferry routes across 33 countries, and looks up weird hidden gems near your destination (Atlas Obscura).Reference data is included: transfer partner ratios for Chase UR, Amex MR, Bilt, Capital One, and Citi TY. Point valuations sourced from TPG, Upgraded Points, OMAAT, and View From The Wing. Alliance membership, sweet spot redemptions, booking windows, hotel chain brand lookups.5 of the 6 MCP servers need zero API keys. Clone, run setup.sh, start searching.Skills are, as usual, plain markdown. They work in OpenCode and Claude Code automatically (I added a tiny setup script), and they'll work in anything else that supports skills.PRs welcome! Help me expand the toolkit! :)https://github.com/borski/travel-hacking-toolkit
FL score
out of 100
Verdict
high confidence
Competition
8
competitors found, emerging market, funded players
Trend
No signal yet
An open-source AI toolkit automating complex travel points/cash comparisons for advanced travel hackers, offering deep integration but needing a clear monetization path.
The pain
The gap
Build angle
Strengths
Questions about this idea?
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Risks
Next steps
Fly Labs Method
Is the pain real, is there a gap, is it the right time, can one person build it.
This idea addresses a real and severe pain for advanced travel hackers, offering a novel 'AI toolkit' approach that differentiates it from existing web-based solutions. While there's a clear willingness to pay for such a solution, the ongoing maintenance and complexity of integrating so many data sources could challenge a solo builder's long-term sustainability.
Value Equation
Dream outcome and how likely it feels, against the time and effort it costs.
This idea has strong market viability and a compelling value proposition, leveraging AI for a growing, complex problem. The unique toolkit approach provides differentiation, but ongoing resource needs could be a challenge.
One-Person Business
Curiosity pull, identity fit, and a path from free value to paid for a solo creator.
A clear problem solved by a passionate creator, leveraging a niche AI toolkit approach. Monetization is a primary concern for this open-source project.
Viral Frameworks
Hook strength, shareability, and how cheaply it can be tested.
A viable micro-SaaS foundation with clear value for a niche, but needs a defined business model and ongoing validation of its AI toolkit approach for the broader travel hacking community.
Builder Lens
Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.
A strong idea with clear demand from a desperate, specific user, offering a novel AI-driven approach to a complex problem that will become more essential over time.
Why this verdict
Five lenses, one composite. How scoring works
The angle
This weekend
Who is already there, emerging market
Searches for award flight availability across many airline loyalty programs and provides step-by-step booking instructions.
Pricing: $5 for a 48-hour pass (first 3 searches free); $129/year; $260/year for concierge service.
An award flight search engine that helps users find and maximize points and miles for flights across major airline loyalty programs.
Pricing: Free tier with live search; Pro plan at $110/year.
A free all-in-one tool that helps you search for flights and hotels you can book using points and miles, scanning real-time award availability.
Pricing: Free plan with unlimited searches and basic features; Premium Plan $11.99/month or $99.99/year.
A fast search engine for award travel that helps users discover award availability on popular airlines and mileage programs.
Pricing: Free for 60-day rolling availability with unlimited alerts; Pro account $9.99/month for full year availability, advanced filters, SMS alerts, and live search.
A search engine that shows live, bookable award seats, prices, and alerts across multiple frequent flyer programs.
Pricing: Free trial; Premium and Diamond plans (specific pricing not found, but noted Diamond plan offers unlimited alerts).
A free website that estimates theoretical miles needed for rewards travel based on old award charts.
Pricing: Free
Shows real-time award seat availability across premium airlines.
Pricing: Free for basic searches; $9.99/month for Pro access.
A Chrome plug-in that integrates point prices next to cash prices in Google Flights search results.
Pricing: Free version; Pro Pricing: $7.99/month or $79.99 per year.
What they charge
Recent news
The Points Guy, April 03, 2026
The Points Guy, April 03, 2026
Miles & Points Daily, March 31, 2026
Miles & Points Daily, March 31, 2026
Miles & Points Daily, March 25, 2026
Market signals
The market for points and miles search and trip planning is growing and increasingly competitive, driven by the desire of travelers to maximize value from loyalty programs. Recent news indicates dynamic pricing is becoming the norm for airlines, and there's a continuous stream of promotions and changes in loyalty programs. The market sees a mix of established players and newer startups leveraging AI to offer real-time availability and enhanced search capabilities, catering to both beginner and advanced travel hackers.
What frustrates people
Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too.The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our own extension appeared daunting. We'd need a small team of sharp engineers and 6-12 months, I figured. And we'd probably still fall short of the performance of a mature system like Parade/Tantivy.Or would we? I'd be experimenting long enough with AI-boosted development at that point to realize that with the latest tools (Claude Code + Opus) and an experienced hand (I've been working in database systems internals for 25 years now), the old time estimates pretty much go out the window.I told our CTO I thought I could solo the project in one quarter. This raised some eyebrows.It did take a little more time than that (two quarters), and we got some real help from the community (amazing!) after open-sourcing the pre-release. But I'm thrilled/exhausted today to share that pg_textsearch v1.0 is freely available via open source (Postgres license), on Tiger Data cloud, and hopefully soon, a hyperscalar near you:https://github.com/timescale/pg_textsearchIn the blog post accompanying the release, I overview the architecture and present benchmark results using MS-MARCO. To my surprise, we were not only able to meet Parade/Tantivy's query performance, but exceed it substantially, measuring a 4.7x advantage on query throughput at scale:https://www.tigerdata.com/blog/pg-textsearch-bm25-fu
AI
Hi HN!I recently switched from a Fedora/GNOME laptop to a MacBook Air. My old setup served me well as a portable workstation, but I’ve started traveling more while working remotely and needed something with similar performance but better battery life. The main thing I missed was a simple taskbar that shows the windows in the current workspace instead of a Dock that mixes everything together.I built boringBar so I would not have to use the Dock. It shows only the windows in the current Space, lets you switch Spaces by scrolling on the bar, and adds a desktop switcher so you can jump directly to any Space. You can also hide the system Dock, pin apps, preview windows with thumbnails, and launch apps from a searchable menu (I keep Spotlight disabled because for some reason it uses a lot of system resources on my machine).I’ve been dogfooding it for a few months now, and it finally felt polished enough to share.It’s for people who like macOS but want window management to feel a bit more like GNOME, Windows, or a traditional taskbar. It’s also for people like me who wanted an easier transition to macOS, especially now that Windows feels increasingly user-hostile.I’d love feedback on the UX, bugs, and whether this solves the same Dock/Spaces pain for anyone else.P.S. It might also appeal to people who feel nostalgic for the GNOME 2 desktop of yore. I started my Linux journey with it, and boringBar brings back some of that feeling for me.
AI
### Describe the project you are working on Godot C# bindings ### Describe the problem or limitation you are having in your project For the past weeks, I've been discussing with several Unity users intending to move to Godot C# regarding dealing with the C# garbage collector. The most common complaint I hear from users is that, in Unity, allocations can trigger unexpected GC spikes into the game. In Godot, we target to make all of the high performance APIs (those that intended to be called every frame) not allocate any memory, so theoretically the GC should not be a problem. Additionally, Godot starting from 4.0, uses the Microsoft CoreCLR version of .net, which also supposedly has a better garbage collector than Unity. But in all, after several discussions with Unity users, neither is enough reassurance for them, and they would really feel safer if Godot exposed a zero allocation API. ### Describe the feature / enhancement and how it helps to overcome the problem or limitation The idea of this proposal is that Godot exposes zero allocation versions of many functions in the C# API, that users can use if they desire. Technically, this could be done from the binding generator itself, without breaking compatibility, and without doing any modification to Godot itself. ### Describe how your proposal will work, with code, pseudo-code, mock-ups, and/or diagrams **WARNING** I am not familiar with C#, so take this as pseudocode. Imagine you have two functions exposed as to C#: ```C# void MyClass.SetArray( Vector2[] array); Vector2[] MyClass.GetArray(); ``` This works and is pretty and intuitive. However, it has two problems: * GC is allocated on return * Memory is copied to Godot native formats every time there is a call. The idea is to add NoAlloc versions, which can be generated directly by the binder automatically when required: ```C# void MyClass.SetArrayNoAlloc( Godot.Collections.PackedVector2Array array); void MyCl
AI