What Should I Eat | ByACommonThread I didn’t know of any apps out there that crowdsource what the best dish at a restaurant is or a ranking of the best dishes. I’ve also never published browser plugins, I was interested in how that works. So I made this plugin.

This v1 version is for Chrome and Firefox (as of writing the draft of this blog post only the Chrome version is published).

This will probably be more useful as an android/ios app, so I’ll get around to that, but I figured I could fill in some details here about how it works and my workflow in building this.

UX

Very simple, v1 only works in Google Maps, you select a restaurant on the map, click the plugin. If the restaurant has never been clicked before, we add it automatically, then you can input what you think the best dish is. If the restaurant has been clicked before, you will see other people’s votes and you can either enter something new or click one of the dishes displayed. The UI uses a “pill cloud” where the text size grows based on how many votes a dish has, so the heavy hitters bubble up visually.

There’s no authentication, no validation on dishes entered. This was partly to keep things simple, but it’s also a feature: there is zero friction to contribute. You don’t have to sign up for yet another service just to say the lasagna is good. Yeah, you can get duplicates. Yeah, users can clear their local data and vote multiple times on a dish.

But, I don’t want to deal with data privacy, plugin approvals, etc. So I chose to make it super simple and basic.

Technical decisions

I had a tough time figuring out how exactly to manage restaurant entries. I want this to work in more than just google maps in the future, so I decided against using a google place id. Relying on Google’s IDs also makes you a bit of a hostage—if they change their internal ID system or you want to support Apple Maps or Yelp later, you’re starting from scratch.

Ultimately, I landed on using GPS coordinates. GPS coordinates will work well for mobile app functionality later, so that’s a plus. And I create a hash/uuid based on those gps coordinates, and these are deterministic based on the coordinates, so it’s easier to lookup in our single table dynamodb design. I’m also using Geohashing to bucket restaurants into ~5km squares (5-character prefixes). This lets the API query the database for just the nearby “bucket” instead of scanning the whole table, which keeps the DynamoDB costs at basically zero. Once I have the nearby results, I use the Haversine formula to calculate the exact distance in meters and sort them. (Here’s where I should note, I had/have no idea what the Haversine formula is, that’s what the LLM came up with)

To handle the “clustering” problem and GPS drift, I round the coordinates to 3 decimal places before hashing. This gives us about 110 meters of “fuzzy” snapping. It means even if you’re standing on the other side of the restaurant, it should still resolve to the same ID. It’s a little worse for locations where a lot of restaurants cluster close to each other in a tiny footprint, but it’s a trade-off I’m willing to make for platform agnosticism. In the future, I’ll add a way to select a specific restaurant if they’re clustered. At some point I’ll also have to think of a way to rename restaurants for when spots close and re-open as something new too.

Infrastructure

The backend is also pretty simple. It’s all in AWS running as a serverless api. All compute is in AWS Lambda, Apigw handles requests, Dynamodb for the datastore. There’s no authentication, no user accounts, it’s a really simple API. It will scale up automatically to a point and it’s pretty much free to run.

Cost to run

Well, there are very few people using this right now, so currently it’s free (besides the hosted zone, but I run multiple things off of that and it’s only $.50 a month). If this thing even gets to the point of costing me money I’d consider it pretty successful. Once it rolls over from the free tier on my stack, it will scale linearly with the number of users.

Monetization

There’s no monetization and I’d only consider monetizing this if my costs exceed my appetite. If it costs me $100+ a month, I’d try to find a simple, non-intrusive way to monetize to cover my costs. Right now, I don’t see that being in the cards so it’s not really a concern.

How I built it

I wrote almost zero code for this personally, I had an LLM do most of it. Gemini, Claude, ChatGPT all had a hand. I think this one was mostly Gemini (which at the time of writing this, June 2026, I’d say it’s the worst tool of the bunch). I don’t stay completely hands off and vibe code, I give guidance, gate the llm at certain points, manually run certain verification steps/tools. It feels more like having a conversation with a Jr Engineer who is eager to please.

I start by explaining what I want to build and telling the LLM to help me build an AGENTS/CLAUDE/GEMINI markdown file. This part usually takes...