On the other hand, it may take that engineer less time to create a page-specific endpoint than it would be to create something more generic that might serve other purposes (that may never come to pass), which may also involve talking to other teams, checking what future plans are, etc.

And that's assuming it's a new endpoint; if there's an existing endpoint that does almost what's necessary, they may need to check in with that team about what modifications to the endpoint would be acceptable, etc.

Single-page endpoints aren't great, but often times they're acceptable because they end up being a half-day task instead of a week-long slog.

That backend engineer wrote a single SQL query that joined some tables, ensured indices were used, and always executed in <1ms.

In graphql land you'd be doing multiple SQL queries, "joining" in the API layer, and spending 50ms per API call.

Is the flexibility worth the tradeoffs? Maybe in a company where you are adding new pages all the time with deeply nested relational data needs. But I would argue this is more rare than not. And I often find that frontend engineers aren’t as familiar with database queries and the load they are putting on the system with some of the graphql queries they are making. Flexibility for frontend has its own tradeoffs and I totally understand why a frontend engineer doesn’t want to have to wait for an endpoint to be finished. But this article outlines some of the issues you encounter later as you scale your team and system.

We use a schema first design where I am at and if a frontend person needs a new endpoint because the resource-only endpoints aren’t enough then they submit a pull request to the schema repo with a design for their endpoint they need. It gets approved and boilerplate is auto generated. Yes you have to wait longer, but 90% of the time (for our software) the resource endpoints work great.

Every page is special. Using generalized API is waste of resources. Generalized APIs are hard to use and develop. It takes a genius to create a good generalized API (say SQL) and even those generalized APIs are not usable in web context (because of authorization and DDoS issues).

It's better to think about optimizing of creation specialized APIs.

This is like, an hour per endpoint. For maybe 30 endpoints (high figure for many apps) throughout the lifespan of your application. But let's say 3 hours: you're talking about 90 hours in total, over a period of 2 or more years. It's really not that much.

And GraphQL isn't free either; you need to actually implement that. It pervades your entire stack, too – it's not something you can just "put on top of it".

I think that in many cases, perhaps even most, GraphQL is a "spend 8 hours to automate a half hour task" kind of affair. Are there cases where that's not the case? Probably. Maybe your specific use case is one of them. But for the general case? I'm entirely unconvinced.