What to build, how to prototype and ship it, whether it works, and what users experience.
To prototype a mobile-optimized writing app I used LLMs as code generators. The idea isn't new but I got inspiration from reading Simon Willison's experiments creating micro-UIs. The idea is to prompt for whatever functionality you need, and ask for a single HTML file containing CSS and JS as needed. This makes copy-pasting
Whenever I write here, I do it on my laptop, almost never on the phone. I do have a Bluetooth keyboard that connects to my phone, but it's rare that I remember to bring it with me, and have a moment to take it out of the bag. Plus it's un-ergonomic. But I also almost
* "less is more" (proverb) * "perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away" (Antoine de Saint Exupéry) * "omit needless words" (Strunk & White) * "It is vain to do with more what can be done with fewer" (Occam'
Across the many experiments I've made this year (and which I've written about here) I've felt the need for better tools. Specifically, for the past few months I have been building copilots, and doing so from scratch takes a bunch of work every time. So we decided to release OpenCopilot: an OSS framework which
I was building an agent with langchain today, and was very frustrated with the developer experience. It felt hard to use, hard to get things right, and overall I was confused a lot while developing (for no good reason). Why is it so hard to use? Here are some of my observations. 1. Verbose. If I have done something once
Microsoft recently held an event where they announced the "Office 365 Copilot". It was extremely impressive to me, to the extent that (when this launches) I will consider switching from Google's work suite to Microsoft's. Why is this announcement so impressive? In one word, integration. Pretty much every Office app can refer to documents,
There is a massive AI overhang today. The term is analogous to snow overhang. When snow slides down a roof, sometimes a section goes over the edge and is seemingly supported by nothing. You know it will eventually fall; the tension is in the air. It's a question of time. I have the same feeling with applying AI
There's a now-famous classification of different levels of self-driving: * Level 0: No automation * Level 1: Driver assistance * Level 2: Partial automation * Level 3: Conditional automation (human fallback always available) * Level 4: High automation (can safely pull over) * Level 5: Full automation The full definition is more detailed but I won't replicate it here. Now
Probably 80% of (mainstream, non-ML) Twitter is excited about the potential of GPT and ChatGPT. The other 20% is skeptical. Few are indifferent. But both the optimists and pessimists seem to focus on the obvious set of use cases: text generation and chatbots. That is a failure of imagination. Text is just an interface to those models, and chat
I've built around 10 prototypes with GPT over the past couple weeks and it's surprisingly fun. Why is that? Obviously it's a shiny new toy. Whenever I discover a new tech capability, I get excited. I recall discovering D3.js, Bokeh, Keras... These appeal to the Technology enthusiast in me. But there's
