dpim

Since coding with Cursor, I’ve spent a lot of time thinking about how much computing interfaces have changed in such a short period of time.

Just as we saw a paradigm shift from imperative to declarative interfaces, LLMs have opened the door to new kinds of interfaces.

Intent-driven interfaces are already everywhere - from AI assistants processing raw data, to Arazzo for defining how APIs map to human-scale workflows, to agents capable of handling complex tasks.

While the doomer view is “robots will take all our jobs”, my optimistic take is we finally have a human-centric way of interacting with machines and it’s going to supercharge our abilities

I built Lttrs.co to make it easy to publish content to the web. From personal websites, to that pesky terms of service you need hosted for launching your iOS app. All your content is one-way synced from Google Docs so there's a clear source-of-truth (No more copy-pasting!). After you share your folder and hit publish, Lttrs builds an optimized, statically generated site (with a perfect 100 Lighthouse score for performance).

It's still early and I'd love to hear what you think!

From cursory googling it looks common for programs to expect you to work right up to the legal limit (80 hours/week based on 4-week averages) during residency. Having 16 hour days for ~7-8 years means that you probably have to get used to being a bit sleep deprived all the time.

A possible explanation could be based on research suggesting that regular lack of deep sleep increases risk of Alzheimer’s. Given that Neurosurgeons have a grueling 7-8? year residency period after medical school, it would be possible that they undersleep far more than the control group.

I would like to see how the prevalence of Alzheimer's among Neurosurgeons compares against a population with similar work/sleep schedules (eg. finance)

I think this is a bit cherrypicked. The example you're using is a fully qualified bound function. OData support for actions and functions explicitly exist to provide affordances for how to do RPC within OData. You can easily model this API in OData without requiring a function (eg. having a navigation property reference called "favoriteAirline"). Moreover, you can typically invoke functions without a fully qualified prefix (save cases where there is ambiguity).

For the most part, OData does a good job at letting folks opt into complexity, allowing integrators to make full use of APIs without needing to know anything about $metadata, inheritance mechanics, functions, etc.

This looks a lot like OData - a REST-ful API standard with schema introspection, patterns for defining and traversing resource relationships, well-defined guidance around mechanics, tooling support. In particular, the "Microtypes" concept resembles how entities work in OData - rich query support for collections (eg. sorts, filters, order by), "expansions" on related resources, even inheritance semantics (ie. being able to request a derived entity as its parent type).

Twilio hit profitability last quarter FWIW

On iOS, checking deep link url schemes (does user X have 'Gmail' installed on their phone?) is pretty straightforward albeit rate-limited.

I hear you. This was a fun project to adapt an existing standard (OData) to be compatible with GraphQL and get a sense of what that looks like over a really big API (hundreds of types, thousands of facets). Part of this is also to see whether as a developer, it makes integrating with Microsoft Graph easier or faster. I'd love to hear your thoughts.