mgaudin
AI Native Principles
We found that traditional development practices break down completely under this model. I've distilled our learnings into 11 principles that have made AI-native development practical and significantly boosted our team's productivity (e.g., by focusing on mono-repos, strict typing, and redefining the engineer's role towards documentation and architecture).
Happy to discuss these principles and answer any questions.
The Context Strategy That Beats Outdated LLM Knowledge
First, the level of uncertainty is very high right now, and I can't afford to have a fixed calendar for the whole week. In fact, it's pretty rare that I manage to stick to the same schedule for even half a day. :X Also, it's often extremely difficult to estimate how long certain tasks will take because they involve both spending time with people (who, by definition, are highly unpredictable) and thinking strategically (which can take anywhere from 2 minutes to 2 hours).
That said, I do relate to the idea that "less freedom" can lead to "more happiness"! I try to apply this as much as possible when it makes sense, especially in my personal life.
As for the Ivy Lee method, I'm not familiar with it, but I'll definitely check it out!
Why Saving Your Sanity Requires Embracing an Infinite To-Do List
Ask HN: My hackathon project, a polymorphic API?
Hi everyone,To speed up the prototyping of my apps (and hopefully yours!), I would like to create a polymorphic API, i.e. a full feature API scaffolded from your requests.In other word, like Elasticsearch, one will be able to throw any json to its face and store it. Also, one will be able to search by any field, and use some pagination and sorting automatically. Also, unlike Elasticsearch, we...