Young Reacts #52

These two graphs clarified the value of my GraphQL project at work though they are from the worlds of data science and server infrastructure. Both showcase the leverage of managed services: data scientists focusing on model development and backend engineers on application code. The same applies to UI engineering.

As a UI engineer, I don’t care to spend time optimizing build pipelines, or learning how to use different backend APIs. I instead want to focus on differentiating activities like understanding business needs and translating those needs to a good UI. GraphQL is one such technology that hides backend implementation details from me.

from Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

what you do and don't manage in a serverless system

from Serverless – Lessons learned


People ❤️

One on One Meeting Opening Lines

I recommend reading this and maybe using this if you are new to one-on-one meetings. But I believe that managers should personalize their approaches for every report. If they just stick to the same tool, it will eventually feel impersonal and distant.

Software Engineering 🌐

The introductory guide to AssemblyScript

I was a little annoyed before that Typescript’s type information gets thrown away at compile time, only to be re-discovered by Javascript’s engines. Not anymore. AssemblyScript will take the type information and generate WebAssembly, saving the engines’ work.

Blogged Answers: Learning and Using TypeScript as an App Dev and a Library Maintainer

An article from a Redux maintainer on the pros and cons of Typescript. I agree that Typescript makes you want to write a more straightforward code with a simpler type system (think High-Order Components vs. Hooks in React).

Business 💸

Memos

This is a list of internal memos by various executives that somehow got out to the public domain. I haven’t read everything yet, but I found the Facebook memos on their Ads business intriguing. I also liked Microsoft’s postmortem on its Word 1.0.

AI Dungeon 2: Creating Infinitely Generated Text Adventures with Deep Learning Language Models

The game may look simple but is super cool. Players can type any text, and the game will react to it based on the model, considering both the context and the text content.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s