Things worth writing down

Writing with AI

I’ve finally crossed a threshold where some parts of what I write - particularly memos at work - has some degree of content generated with AI.

NYT Test

The past week hasn’t been a very good one for Google. The cultural issues, though, go well beyond Gemini.

Investor updates template

Sharing a template from a portco that I really love. They’ve set a high-bar, particularly when combined with the consistency of their updates.

Copilots

It's counter-intuitive, but for now it looks like _less_ automation is better than more automation. And we need dedicated copilots for each problem, with each copilot needing its own interaction paradigm that suits each individual's workflows.

Building again

It's been a year and a half since I wrote something here at all. While I moved over somewhat to Substack, I never quite enjoyed it, while writing on this page via Github was a bit of a hassle.

However, I finally find myself in VSCode on a weekly basis, tinkering more and more as ChatGPT's fueled my desire to explore, prototype quick hacks, and ship. For real – I actually shipped something! This tweet below describes the mental change I've been trying to make that's been paying dividends.

Given the rapid decline in idea 🔁 prototype time, I *really* hope we see a change in mentality where we all swap "I wish there was a solution to X" to "How might we solve X".

— Raveesh Bhalla (@raveeshbhalla) March 26, 2023

On top of that, need to give major kudos to Vercel for making the developer experience of building for the web so much better than what I last remember (circa 2013). I mean this about both their own platform, as well as NextJS (which I'm finally getting the hang of). Putting together this new site as a replacement for my old Jekyll driven one was actually fun – though I still need to get around to finally getting comfortable with CSS!

Hopefully you all see me write more often. And more importantly, ship more often.

Intimate computing

I wrote the following post on my then Medium blog. Listening to Ben Thompson’s post on his conversation with Sydney (a persona of Bing’s GPT-based chatbot that some folks have managed to unlock) made me want to revisit it, and I thought it was worth sharing 9 years on.

Zero sum

From Awareness: Conversations with the Masters by Anthony de Mello, SJ

“Would you want me to love you at the cost of my happiness?” “Yes,” she answered. Isn’t that delightful? Wouldn’t that be wonderful? She would love me at the cost of her happiness and I would love her at the cost of my happiness, and so you’ve got two unhappy people, but long live love!”

I was trying to think why this didn't resonate with me. After a few minutes, I realized that it was because it positions the choice as zero sum, and I hate zero sum frameworks of decision making because it's lazy and not representative of the real world.

This applies to relationships, to personal wellbeing, to even capitalism (also why I detest companies that want to "crush the competition").

Pillars of AI product development

1. Objective: seems obvious, but it’s vital to document your objectives clearly so you can ensure everything you do afterwards is set up to drive towards this. Your objectives are going to be iterated on over time – as they should be – as you get more and more granular about the outcomes you want from your AI products.

2. Tracking & labelling: the saying goes “your models are only as good as your data”, which is 💯. However, a vital subpoint here is that your data might be wasted if you lack a quality labelling strategy (i.e. what labels you use, how you collect them and ensuring they’re not adding noise to your system).

3. Infrastructure: Investments here can help boost reliability, performance, efficiency and productivity. If your product is a vehicle, this is your engine.

4. Monitoring: the fact that AI models are black boxes makes this space so vital – when things break, you may not even realize that it has. And the impact can be disastrous. Easily one of the most underinvested spaces.

It’s on top of this that you layer on your feature engineering and models itself. Invest in all four pillars to have compounding returns.

Shane Parish on reading better

Highly recommend Shane Parish's blog on reading. Some notes/takeways below after diving into the rabbit hole.

Travelling to Rome

Two of my colleagues asked me for my recommendations about their travel to Rome, so I thought id write down some highlights from earlier in the year!

Why I write decision-making frameworks

Over the past several months, I have found myself to have written a fairly large number of internal decision making frameworks. These have ranged from defining a means to think about the information architecture on LinkedIn's Job Search components to recommendations on how to evaluate A/B tests. Why do I do it?